Hybrid Bee Ant Colony Algorithm for Effective Load Balancing And ...
African Journals Online (AJOL)
PROF. OLIVER OSUAGWA
Ant Colony algorithm is used in this hybrid Bee Ant Colony algorithm to solve load balancing issues ... Genetic Algorithm (MO-GA) for dynamic job scheduling that .... Information Networking and Applications Workshops. [7]. M. Dorigo & T.
An efficient dynamic load balancing algorithm
Lagaros, Nikos D.
2014-01-01
In engineering problems, randomness and uncertainties are inherent. Robust design procedures, formulated in the framework of multi-objective optimization, have been proposed in order to take into account sources of randomness and uncertainty. These design procedures require orders of magnitude more computational effort than conventional analysis or optimum design processes since a very large number of finite element analyses is required to be dealt. It is therefore an imperative need to exploit the capabilities of computing resources in order to deal with this kind of problems. In particular, parallel computing can be implemented at the level of metaheuristic optimization, by exploiting the physical parallelization feature of the nondominated sorting evolution strategies method, as well as at the level of repeated structural analyses required for assessing the behavioural constraints and for calculating the objective functions. In this study an efficient dynamic load balancing algorithm for optimum exploitation of available computing resources is proposed and, without loss of generality, is applied for computing the desired Pareto front. In such problems the computation of the complete Pareto front with feasible designs only, constitutes a very challenging task. The proposed algorithm achieves linear speedup factors and almost 100% speedup factor values with reference to the sequential procedure.
GENETIC ALGORITHM BASED CONCEPT DESIGN TO OPTIMIZE NETWORK LOAD BALANCE
Directory of Open Access Journals (Sweden)
Ashish Jain
2012-07-01
Full Text Available Multiconstraints optimal network load balancing is an NP-hard problem and it is an important part of traffic engineering. In this research we balance the network load using classical method (brute force approach and dynamic programming is used but result shows the limitation of this method but at a certain level we recognized that the optimization of balanced network load with increased number of nodes and demands is intractable using the classical method because the solution set increases exponentially. In such case the optimization techniques like evolutionary techniques can employ for optimizing network load balance. In this paper we analyzed proposed classical algorithm and evolutionary based genetic approach is devise as well as proposed in this paper for optimizing the balance network load.
Static Load Balancing Algorithms In Cloud Computing Challenges amp Solutions
Directory of Open Access Journals (Sweden)
Nadeem Shah
2015-08-01
Full Text Available Abstract Cloud computing provides on-demand hosted computing resources and services over the Internet on a pay-per-use basis. It is currently becoming the favored method of communication and computation over scalable networks due to numerous attractive attributes such as high availability scalability fault tolerance simplicity of management and low cost of ownership. Due to the huge demand of cloud computing efficient load balancing becomes critical to ensure that computational tasks are evenly distributed across servers to prevent bottlenecks. The aim of this review paper is to understand the current challenges in cloud computing primarily in cloud load balancing using static algorithms and finding gaps to bridge for more efficient static cloud load balancing in the future. We believe the ideas suggested as new solution will allow researchers to redesign better algorithms for better functionalities and improved user experiences in simple cloud systems. This could assist small businesses that cannot afford infrastructure that supports complex amp dynamic load balancing algorithms.
Dynamic load balance scheme for the DSMC algorithm
International Nuclear Information System (INIS)
Li, Jin; Geng, Xiangren; Jiang, Dingwu; Chen, Jianqiang
2014-01-01
The direct simulation Monte Carlo (DSMC) algorithm, devised by Bird, has been used over a wide range of various rarified flow problems in the past 40 years. While the DSMC is suitable for the parallel implementation on powerful multi-processor architecture, it also introduces a large load imbalance across the processor array, even for small examples. The load imposed on a processor by a DSMC calculation is determined to a large extent by the total of simulator particles upon it. Since most flows are impulsively started with initial distribution of particles which is surely quite different from the steady state, the total of simulator particles will change dramatically. The load balance based upon an initial distribution of particles will break down as the steady state of flow is reached. The load imbalance and huge computational cost of DSMC has limited its application to rarefied or simple transitional flows. In this paper, by taking advantage of METIS, a software for partitioning unstructured graphs, and taking the total of simulator particles in each cell as a weight information, the repartitioning based upon the principle that each processor handles approximately the equal total of simulator particles has been achieved. The computation must pause several times to renew the total of simulator particles in each processor and repartition the whole domain again. Thus the load balance across the processors array holds in the duration of computation. The parallel efficiency can be improved effectively. The benchmark solution of a cylinder submerged in hypersonic flow has been simulated numerically. Besides, hypersonic flow past around a complex wing-body configuration has also been simulated. The results have displayed that, for both of cases, the computational time can be reduced by about 50%
Scheduling algorithms for saving energy and balancing load
Energy Technology Data Exchange (ETDEWEB)
Antoniadis, Antonios
2012-08-03
In this thesis we study problems of scheduling tasks in computing environments. We consider both the modern objective function of minimizing energy consumption, and the classical objective of balancing load across machines. We first investigate offline deadline-based scheduling in the setting of a single variable-speed processor that is equipped with a sleep state. The objective is that of minimizing the total energy consumption. Apart from settling the complexity of the problem by showing its NP-hardness, we provide a lower bound of 2 for general convex power functions, and a particular natural class of schedules called s{sub crit}-schedules. We also present an algorithmic framework for designing good approximation algorithms. For general convex power functions our framework improves the best known approximation-factor from 2 to 4/3. This factor can be reduced even further to 137/117 for a specific well-motivated class of power functions. Furthermore, we give tight bounds to show that our framework returns optimal s{sub crit}-schedules for the two aforementioned power-function classes. We then focus on the multiprocessor setting where each processor has the ability to vary its speed. Job migration is allowed, and we again consider classical deadline-based scheduling with the objective of energy minimization. We first study the offline problem and show that optimal schedules can be computed efficiently in polynomial time for any convex and non-decreasing power function. Our algorithm relies on repeated maximum flow computations. Regarding the online problem and power functions P(s) = s{sup {alpha}}, where s is the processor speed and {alpha} > 1 a constant, we extend the two well-known single-processor algorithms Optimal Available and Average Rate. We prove that Optimal Available is {alpha}{sup {alpha}}-competitive as in the single-processor case. For Average Rate we show a competitive factor of (2{alpha}){sup {alpha}}/2 + 1, i.e., compared to the single
Dynamic load balancing algorithm for molecular dynamics based on Voronoi cells domain decompositions
Energy Technology Data Exchange (ETDEWEB)
Fattebert, J.-L. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Richards, D.F. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Glosli, J.N. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2012-12-01
We present a new algorithm for automatic parallel load balancing in classical molecular dynamics. It assumes a spatial domain decomposition of particles into Voronoi cells. It is a gradient method which attempts to minimize a cost function by displacing Voronoi sites associated with each processor/sub-domain along steepest descent directions. Excellent load balance has been obtained for quasi-2D and 3D practical applications, with up to 440·10^{6} particles on 65,536 MPI tasks.
Mobility-Aware and Load Balancing Based Clustering Algorithm for Energy Conservation in MANET
Institute of Scientific and Technical Information of China (English)
XU Li; ZHENG Bao-yu; GUO Gong-de
2005-01-01
Mobile ad hoc network (MANET) is one of wireless communication network architecture that has received a lot of attention. MANET is characterized by dynamic network topology and limited energy. With mobility-aware and load balancing based clustering algorithm (MLCA), this paper proposes a new topology management strategy to conserve energy. Performance simulation results show that the proposed MLCA strategy can balances the traffic load inside the whole network, so as to prolong the network lifetime, meanly, at the same time, achieve higher throughput ratio and network stability.
Programming Algorithms of load balancing with HA-Proxy in HTTP services
Directory of Open Access Journals (Sweden)
José Teodoro Mejía Viteri
2018-02-01
Full Text Available The access to the public and private services through the web gains daily protagonism, and sometimes they must support amounts of requests that a team can not process, so there are solutions that use algorithms that allow to distribute the load of requests of a web application in several equipment; the objective of this work is to perform an analysis of load balancing scheduling algorithms through the HA-Proxy tool, and deliver an instrument that identifies the load distribution algorithm to be used and the technological infrastructure, to largely cover implementation. The information used for this work is based on a bibliographic analysis, eld study and implementation of the different load balancing algorithms in equipment, where the distribution and its performance will be analyzed. The incorporation of this technology to the management of services on the web, improves availability, helps business continuity and through the different forms of distribution of the requests of the algorithms that can be implemented in HA-Proxy to provide those responsible for information technology systems with a view of their advantages and disadvantages.
Load Balancing Issues with Constructing Phylogenetic Trees using Neighbour-Joining Algorithm
International Nuclear Information System (INIS)
Al Mamun, S M
2012-01-01
Phylogenetic tree construction is one of the most important and interesting problems in bioinformatics. Constructing an efficient phylogenetic tree has always been a research issue. It needs to consider both the correctness and the speed of the tree construction. In this paper, we implemented the neighbour-joining algorithm, using Message Passing Interface (MPI) for constructing the phylogenetic tree. Performance is efficacious, comparing to the best sequential algorithm. From this paper, it would be clear to the researchers that how load balance can make a great effect for constructing phylogenetic trees using neighbour-joining algorithm.
Model of load balancing using reliable algorithm with multi-agent system
Afriansyah, M. F.; Somantri, M.; Riyadi, M. A.
2017-04-01
Massive technology development is linear with the growth of internet users which increase network traffic activity. It also increases load of the system. The usage of reliable algorithm and mobile agent in distributed load balancing is a viable solution to handle the load issue on a large-scale system. Mobile agent works to collect resource information and can migrate according to given task. We propose reliable load balancing algorithm using least time first byte (LFB) combined with information from the mobile agent. In system overview, the methodology consisted of defining identification system, specification requirements, network topology and design system infrastructure. The simulation method for simulated system was using 1800 request for 10 s from the user to the server and taking the data for analysis. Software simulation was based on Apache Jmeter by observing response time and reliability of each server and then compared it with existing method. Results of performed simulation show that the LFB method with mobile agent can perform load balancing with efficient systems to all backend server without bottleneck, low risk of server overload, and reliable.
Sampling-Based Motion Planning Algorithms for Replanning and Spatial Load Balancing
Energy Technology Data Exchange (ETDEWEB)
Boardman, Beth Leigh [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-10-12
The common theme of this dissertation is sampling-based motion planning with the two key contributions being in the area of replanning and spatial load balancing for robotic systems. Here, we begin by recalling two sampling-based motion planners: the asymptotically optimal rapidly-exploring random tree (RRT*), and the asymptotically optimal probabilistic roadmap (PRM*). We also provide a brief background on collision cones and the Distributed Reactive Collision Avoidance (DRCA) algorithm. The next four chapters detail novel contributions for motion replanning in environments with unexpected static obstacles, for multi-agent collision avoidance, and spatial load balancing. First, we show improved performance of the RRT* when using the proposed Grandparent-Connection (GP) or Focused-Refinement (FR) algorithms. Next, the Goal Tree algorithm for replanning with unexpected static obstacles is detailed and proven to be asymptotically optimal. A multi-agent collision avoidance problem in obstacle environments is approached via the RRT*, leading to the novel Sampling-Based Collision Avoidance (SBCA) algorithm. The SBCA algorithm is proven to guarantee collision free trajectories for all of the agents, even when subject to uncertainties in the knowledge of the other agents’ positions and velocities. Given that a solution exists, we prove that livelocks and deadlock will lead to the cost to the goal being decreased. We introduce a new deconfliction maneuver that decreases the cost-to-come at each step. This new maneuver removes the possibility of livelocks and allows a result to be formed that proves convergence to the goal configurations. Finally, we present a limited range Graph-based Spatial Load Balancing (GSLB) algorithm which fairly divides a non-convex space among multiple agents that are subject to differential constraints and have a limited travel distance. The GSLB is proven to converge to a solution when maximizing the area covered by the agents. The analysis
Load Balancing Scientific Applications
Energy Technology Data Exchange (ETDEWEB)
Pearce, Olga Tkachyshyn [Texas A & M Univ., College Station, TX (United States)
2014-12-01
The largest supercomputers have millions of independent processors, and concurrency levels are rapidly increasing. For ideal efficiency, developers of the simulations that run on these machines must ensure that computational work is evenly balanced among processors. Assigning work evenly is challenging because many large modern parallel codes simulate behavior of physical systems that evolve over time, and their workloads change over time. Furthermore, the cost of imbalanced load increases with scale because most large-scale scientific simulations today use a Single Program Multiple Data (SPMD) parallel programming model, and an increasing number of processors will wait for the slowest one at the synchronization points. To address load imbalance, many large-scale parallel applications use dynamic load balance algorithms to redistribute work evenly. The research objective of this dissertation is to develop methods to decide when and how to load balance the application, and to balance it effectively and affordably. We measure and evaluate the computational load of the application, and develop strategies to decide when and how to correct the imbalance. Depending on the simulation, a fast, local load balance algorithm may be suitable, or a more sophisticated and expensive algorithm may be required. We developed a model for comparison of load balance algorithms for a specific state of the simulation that enables the selection of a balancing algorithm that will minimize overall runtime.
A Comparative Study of Load Balancing Algorithms in Cloud Computing Environment
Katyal, Mayanka; Mishra, Atul
2014-01-01
Cloud Computing is a new trend emerging in IT environment with huge requirements of infrastructure and resources. Load Balancing is an important aspect of cloud computing environment. Efficient load balancing scheme ensures efficient resource utilization by provisioning of resources to cloud users on demand basis in pay as you say manner. Load Balancing may even support prioritizing users by applying appropriate scheduling criteria. This paper presents various load balancing schemes in differ...
A New Approach of Parallelism and Load Balance for the Apriori Algorithm
Directory of Open Access Journals (Sweden)
BOLINA, A. C.
2013-06-01
Full Text Available The main goal of data mining is to discover relevant information on digital content. The Apriori algorithm is widely used to this objective, but its sequential version has a low performance when execu- ted over large volumes of data. Among the solutions for this problem is the parallel implementation of the algorithm, and among the parallel implementations presented in the literature that based on Apriori, it highlights the DPA (Distributed Parallel Apriori [10]. This paper presents the DMTA (Distributed Multithread Apriori algorithm, which is based on DPA and exploits the parallelism level of threads in order to increase the performance. Besides, DMTA can be executed over heterogeneous hardware platform, using different number of cores. The results showed that DMTA outperforms DPA, presents load balance among processes and threads, and it is effective in current multicore architectures.
Devi, D Chitra; Uthariaraj, V Rhymend
2016-01-01
Cloud computing uses the concepts of scheduling and load balancing to migrate tasks to underutilized VMs for effectively sharing the resources. The scheduling of the nonpreemptive tasks in the cloud computing environment is an irrecoverable restraint and hence it has to be assigned to the most appropriate VMs at the initial placement itself. Practically, the arrived jobs consist of multiple interdependent tasks and they may execute the independent tasks in multiple VMs or in the same VM's multiple cores. Also, the jobs arrive during the run time of the server in varying random intervals under various load conditions. The participating heterogeneous resources are managed by allocating the tasks to appropriate resources by static or dynamic scheduling to make the cloud computing more efficient and thus it improves the user satisfaction. Objective of this work is to introduce and evaluate the proposed scheduling and load balancing algorithm by considering the capabilities of each virtual machine (VM), the task length of each requested job, and the interdependency of multiple tasks. Performance of the proposed algorithm is studied by comparing with the existing methods.
Directory of Open Access Journals (Sweden)
D. Chitra Devi
2016-01-01
Full Text Available Cloud computing uses the concepts of scheduling and load balancing to migrate tasks to underutilized VMs for effectively sharing the resources. The scheduling of the nonpreemptive tasks in the cloud computing environment is an irrecoverable restraint and hence it has to be assigned to the most appropriate VMs at the initial placement itself. Practically, the arrived jobs consist of multiple interdependent tasks and they may execute the independent tasks in multiple VMs or in the same VM’s multiple cores. Also, the jobs arrive during the run time of the server in varying random intervals under various load conditions. The participating heterogeneous resources are managed by allocating the tasks to appropriate resources by static or dynamic scheduling to make the cloud computing more efficient and thus it improves the user satisfaction. Objective of this work is to introduce and evaluate the proposed scheduling and load balancing algorithm by considering the capabilities of each virtual machine (VM, the task length of each requested job, and the interdependency of multiple tasks. Performance of the proposed algorithm is studied by comparing with the existing methods.
Using Load Balancing to Scalably Parallelize Sampling-Based Motion Planning Algorithms
Fidel, Adam; Jacobs, Sam Ade; Sharma, Shishir; Amato, Nancy M.; Rauchwerger, Lawrence
2014-01-01
Motion planning, which is the problem of computing feasible paths in an environment for a movable object, has applications in many domains ranging from robotics, to intelligent CAD, to protein folding. The best methods for solving this PSPACE-hard problem are so-called sampling-based planners. Recent work introduced uniform spatial subdivision techniques for parallelizing sampling-based motion planning algorithms that scaled well. However, such methods are prone to load imbalance, as planning time depends on region characteristics and, for most problems, the heterogeneity of the sub problems increases as the number of processors increases. In this work, we introduce two techniques to address load imbalance in the parallelization of sampling-based motion planning algorithms: an adaptive work stealing approach and bulk-synchronous redistribution. We show that applying these techniques to representatives of the two major classes of parallel sampling-based motion planning algorithms, probabilistic roadmaps and rapidly-exploring random trees, results in a more scalable and load-balanced computation on more than 3,000 cores. © 2014 IEEE.
Using Load Balancing to Scalably Parallelize Sampling-Based Motion Planning Algorithms
Fidel, Adam
2014-05-01
Motion planning, which is the problem of computing feasible paths in an environment for a movable object, has applications in many domains ranging from robotics, to intelligent CAD, to protein folding. The best methods for solving this PSPACE-hard problem are so-called sampling-based planners. Recent work introduced uniform spatial subdivision techniques for parallelizing sampling-based motion planning algorithms that scaled well. However, such methods are prone to load imbalance, as planning time depends on region characteristics and, for most problems, the heterogeneity of the sub problems increases as the number of processors increases. In this work, we introduce two techniques to address load imbalance in the parallelization of sampling-based motion planning algorithms: an adaptive work stealing approach and bulk-synchronous redistribution. We show that applying these techniques to representatives of the two major classes of parallel sampling-based motion planning algorithms, probabilistic roadmaps and rapidly-exploring random trees, results in a more scalable and load-balanced computation on more than 3,000 cores. © 2014 IEEE.
Automatic mesh refinement and parallel load balancing for Fokker-Planck-DSMC algorithm
Küchlin, Stephan; Jenny, Patrick
2018-06-01
Recently, a parallel Fokker-Planck-DSMC algorithm for rarefied gas flow simulation in complex domains at all Knudsen numbers was developed by the authors. Fokker-Planck-DSMC (FP-DSMC) is an augmentation of the classical DSMC algorithm, which mitigates the near-continuum deficiencies in terms of computational cost of pure DSMC. At each time step, based on a local Knudsen number criterion, the discrete DSMC collision operator is dynamically switched to the Fokker-Planck operator, which is based on the integration of continuous stochastic processes in time, and has fixed computational cost per particle, rather than per collision. In this contribution, we present an extension of the previous implementation with automatic local mesh refinement and parallel load-balancing. In particular, we show how the properties of discrete approximations to space-filling curves enable an efficient implementation. Exemplary numerical studies highlight the capabilities of the new code.
International Nuclear Information System (INIS)
Simon, M; Kozielski, S; Sakulin, H
2011-01-01
The proposed method is designed for a data acquisition system acquiring data from n independent sources. The data sources are supposed to produce fragments that together constitute some logical wholeness. These fragments are produced with the same frequency and in the same sequence. The discussed algorithm aims to balance the data dynamically between m logically autonomous processing units (consisting of computing nodes) in case of variation in their processing power which could be caused by some faults like failing computing nodes, or broken network connections. As a case study we consider the Data Acquisition System of the Compact Muon Solenoid Experiment at CERN's new Large Hadron Collider. The system acquires data from about 500 sources and combines them into full events. Each data source is expected to deliver event fragments of an average size of 2 kB with 100 kHz frequency. In this paper we present the results of applying proposed load metric and load communication pattern. Moreover, we discuss their impact on the algorithm's overall efficiency and scalability, as well as on fault tolerance of the whole system. We also propose a general concept of an algorithm that allows for choosing the destination processing unit in all source nodes asynchronously and asserts that all fragments of same logical data always go to same unit.
Devi, D. Chitra; Uthariaraj, V. Rhymend
2016-01-01
Cloud computing uses the concepts of scheduling and load balancing to migrate tasks to underutilized VMs for effectively sharing the resources. The scheduling of the nonpreemptive tasks in the cloud computing environment is an irrecoverable restraint and hence it has to be assigned to the most appropriate VMs at the initial placement itself. Practically, the arrived jobs consist of multiple interdependent tasks and they may execute the independent tasks in multiple VMs or in the same VM’s mul...
Stateful load balancing for parallel stream processing
DEFF Research Database (Denmark)
Guo, Qingsong; Zhou, Yongluan
2018-01-01
-objective optimization problem, namely Minimum-Cost-Load-Balance (MCLB). We address MCLB with two approximate algorithms by a certain relaxation of the objectives: (1) a greedy algorithm ELB performs load balancing eagerly but relaxes the objective of load imbalance to a range; and (2) a periodic algorithm CLB aims...
Zhou, Xiuze; Lin, Fan; Yang, Lvqing; Nie, Jing; Tan, Qian; Zeng, Wenhua; Zhang, Nian
2016-01-01
With the continuous expansion of the cloud computing platform scale and rapid growth of users and applications, how to efficiently use system resources to improve the overall performance of cloud computing has become a crucial issue. To address this issue, this paper proposes a method that uses an analytic hierarchy process group decision (AHPGD) to evaluate the load state of server nodes. Training was carried out by using a hybrid hierarchical genetic algorithm (HHGA) for optimizing a radial basis function neural network (RBFNN). The AHPGD makes the aggregative indicator of virtual machines in cloud, and become input parameters of predicted RBFNN. Also, this paper proposes a new dynamic load balancing scheduling algorithm combined with a weighted round-robin algorithm, which uses the predictive periodical load value of nodes based on AHPPGD and RBFNN optimized by HHGA, then calculates the corresponding weight values of nodes and makes constant updates. Meanwhile, it keeps the advantages and avoids the shortcomings of static weighted round-robin algorithm.
Delgosha, Payam; Anantharam, Venkat
2018-03-01
Consider a simple locally finite hypergraph on a countable vertex set, where each edge represents one unit of load which should be distributed among the vertices defining the edge. An allocation of load is called balanced if load cannot be moved from a vertex to another that is carrying less load. We analyze the properties of balanced allocations of load. We extend the concept of balancedness from finite hypergraphs to their local weak limits in the sense of Benjamini and Schramm (Electron J Probab 6(23):13, 2001) and Aldous and Steele (in: Probability on discrete structures. Springer, Berlin, pp 1-72, 2004). To do this, we define a notion of unimodularity for hypergraphs which could be considered an extension of unimodularity in graphs. We give a variational formula for the balanced load distribution and, in particular, we characterize it in the special case of unimodular hypergraph Galton-Watson processes. Moreover, we prove the convergence of the maximum load under some conditions. Our work is an extension to hypergraphs of Anantharam and Salez (Ann Appl Probab 26(1):305-327, 2016), which considered load balancing in graphs, and is aimed at more comprehensively resolving conjectures of Hajek (IEEE Trans Inf Theory 36(6):1398-1414, 1990).
Quantum load balancing in ad hoc networks
Hasanpour, M.; Shariat, S.; Barnaghi, P.; Hoseinitabatabaei, S. A.; Vahid, S.; Tafazolli, R.
2017-06-01
This paper presents a novel approach in targeting load balancing in ad hoc networks utilizing the properties of quantum game theory. This approach benefits from the instantaneous and information-less capability of entangled particles to synchronize the load balancing strategies in ad hoc networks. The quantum load balancing (QLB) algorithm proposed by this work is implemented on top of OLSR as the baseline routing protocol; its performance is analyzed against the baseline OLSR, and considerable gain is reported regarding some of the main QoS metrics such as delay and jitter. Furthermore, it is shown that QLB algorithm supports a solid stability gain in terms of throughput which stands a proof of concept for the load balancing properties of the proposed theory.
DEFF Research Database (Denmark)
Zhao, Xiaojun; Zhang, Chunjiang; Chai, Xiuhui
2018-01-01
In three-phase four-wire systems, unbalanced loads can cause grid currents to be unbalanced, and this may cause the neutral point potential on the grid side to shift. The neutral point potential shift will worsen the control precision as well as the performance of the threephase four-wire unified...... fluctuations, and elaborates the interaction between unbalanced grid currents and DC bus voltage fluctuations; two control strategies of UPQC under three-phase stationary coordinate based on the MCA are given, and finally, the feasibility and effectiveness of the proposed control strategy are verified...... power quality conditioner (UPQC), and it also leads to unbalanced three-phase output voltage, even causing damage to electric equipment. To deal with unbalanced loads, this paper proposes a matching-ratio compensation algorithm (MCA) for the fundamental active component of load currents...
Xu, Zhanqi; Huang, Jiangjiang; Zhou, Zhiqiang; Ding, Zhe; Ma, Tao; Wang, Junping
2013-10-01
To maximize the resource utilization of optical networks, the dynamic traffic grooming, which could efficiently multiplex many low-speed services arriving dynamically onto high-capacity optical channels, has been studied extensively and used widely. However, the link weights in the existing research works can be improved since they do not adapt to the network status and load well. By exploiting the information on the holding times of the preexisting and new lightpaths, and the requested bandwidth of a user service, this paper proposes a grooming algorithm using Adaptively Weighted Links for Holding-Time-Aware (HTA) (abbreviated as AWL-HTA) traffic, especially in the setup process of new lightpath(s). Therefore, the proposed algorithm can not only establish a lightpath that uses network resource efficiently, but also achieve load balancing. In this paper, the key issues on the link weight assignment and procedure within the AWL-HTA are addressed in detail. Comprehensive simulation and experimental results show that the proposed algorithm has a much lower blocking ratio and latency than other existing algorithms.
Short-term Power Load Forecasting Based on Balanced KNN
Lv, Xianlong; Cheng, Xingong; YanShuang; Tang, Yan-mei
2018-03-01
To improve the accuracy of load forecasting, a short-term load forecasting model based on balanced KNN algorithm is proposed; According to the load characteristics, the historical data of massive power load are divided into scenes by the K-means algorithm; In view of unbalanced load scenes, the balanced KNN algorithm is proposed to classify the scene accurately; The local weighted linear regression algorithm is used to fitting and predict the load; Adopting the Apache Hadoop programming framework of cloud computing, the proposed algorithm model is parallelized and improved to enhance its ability of dealing with massive and high-dimension data. The analysis of the household electricity consumption data for a residential district is done by 23-nodes cloud computing cluster, and experimental results show that the load forecasting accuracy and execution time by the proposed model are the better than those of traditional forecasting algorithm.
Directory of Open Access Journals (Sweden)
Khalid Qaraqe
2008-10-01
Full Text Available This paper proposes a novel vertical handoff algorithm between WLAN and CDMA networks to enable the integration of these networks. The proposed vertical handoff algorithm assumes a handoff decision process (handoff triggering and network selection. The handoff trigger is decided based on the received signal strength (RSS. To reduce the likelihood of unnecessary false handoffs, the distance criterion is also considered. As a network selection mechanism, based on the wireless channel assignment algorithm, this paper proposes a context-based network selection algorithm and the corresponding communication algorithms between WLAN and CDMA networks. This paper focuses on a handoff triggering criterion which uses both the RSS and distance information, and a network selection method which uses context information such as the dropping probability, blocking probability, GoS (grade of service, and number of handoff attempts. As a decision making criterion, the velocity threshold is determined to optimize the system performance. The optimal velocity threshold is adjusted to assign the available channels to the mobile stations. The optimal velocity threshold is adjusted to assign the available channels to the mobile stations using four handoff strategies. The four handoff strategies are evaluated and compared with each other in terms of GOS. Finally, the proposed scheme is validated by computer simulations.
Directory of Open Access Journals (Sweden)
Kim Jang-Sub
2008-01-01
Full Text Available This paper proposes a novel vertical handoff algorithm between WLAN and CDMA networks to enable the integration of these networks. The proposed vertical handoff algorithm assumes a handoff decision process (handoff triggering and network selection. The handoff trigger is decided based on the received signal strength (RSS. To reduce the likelihood of unnecessary false handoffs, the distance criterion is also considered. As a network selection mechanism, based on the wireless channel assignment algorithm, this paper proposes a context-based network selection algorithm and the corresponding communication algorithms between WLAN and CDMA networks. This paper focuses on a handoff triggering criterion which uses both the RSS and distance information, and a network selection method which uses context information such as the dropping probability, blocking probability, GoS (grade of service, and number of handoff attempts. As a decision making criterion, the velocity threshold is determined to optimize the system performance. The optimal velocity threshold is adjusted to assign the available channels to the mobile stations. The optimal velocity threshold is adjusted to assign the available channels to the mobile stations using four handoff strategies. The four handoff strategies are evaluated and compared with each other in terms of GOS. Finally, the proposed scheme is validated by computer simulations.
RPL LOAD BALANCING IN INTERNET OF THINGS
Directory of Open Access Journals (Sweden)
Mohammad Reza Parsaei
2017-12-01
Full Text Available ABSTRACT: The wide address space provided by Internet Protocol version 6 (IPv6 lets any thing to be identified uniquely. consistency of the modified version of IPv6 protocol stack with smart objects, facilitated the Internet interconnection of the networks of smart objects and introduced Internet of things. A smart object is a small micro-electronic device that consists of a communication device, a small microprocessor and a sensor or an actuator. A network made of such devices is called low-power and lossy network. RPL routing protocol that is consistent to IPv6, is designed to be used in these kinds of networks. Load balancing is not considered in the RPL design process. Whenever RPL is used in large scale low-power and lossy networks some nodes will suffer from congestion and this problem severely degrades network performance. In this paper, we consider solutions provided to tackle RPL load balancing problems. Load balancing algorithms and protoclos are evaluated through simulation. We evaluate IETF RPL implementation and LB-RPL method with Contiki OS Java (COOJA simulator. They are assessed comprehensively through metrics such as Packet delivery Ratio, Average End to End delay, and Gateway Throughput. LB-RPL improves RPL in terms of Packet delivery Ratio and throughput but increases Average End to End delay. Simulations results show that RPL load balancing needs extensive works to be performed yet.
Partitioning of unstructured meshes for load balancing
International Nuclear Information System (INIS)
Martin, O.C.; Otto, S.W.
1994-01-01
Many large-scale engineering and scientific calculations involve repeated updating of variables on an unstructured mesh. To do these types of computations on distributed memory parallel computers, it is necessary to partition the mesh among the processors so that the load balance is maximized and inter-processor communication time is minimized. This can be approximated by the problem, of partitioning a graph so as to obtain a minimum cut, a well-studied combinatorial optimization problem. Graph partitioning algorithms are discussed that give good but not necessarily optimum solutions. These algorithms include local search methods recursive spectral bisection, and more general purpose methods such as simulated annealing. It is shown that a general procedure enables to combine simulated annealing with Kernighan-Lin. The resulting algorithm is both very fast and extremely effective. (authors) 23 refs., 3 figs., 1 tab
Load Balancing of Parallel Monte Carlo Transport Calculations
International Nuclear Information System (INIS)
Procassini, R J; O'Brien, M J; Taylor, J M
2005-01-01
The performance of parallel Monte Carlo transport calculations which use both spatial and particle parallelism is increased by dynamically assigning processors to the most worked domains. Since he particle work load varies over the course of the simulation, this algorithm determines each cycle if dynamic load balancing would speed up the calculation. If load balancing is required, a small number of particle communications are initiated in order to achieve load balance. This method has decreased the parallel run time by more than a factor of three for certain criticality calculations
Dynamic Load Balancing of Parallel Monte Carlo Transport Calculations
International Nuclear Information System (INIS)
O'Brien, M; Taylor, J; Procassini, R
2004-01-01
The performance of parallel Monte Carlo transport calculations which use both spatial and particle parallelism is increased by dynamically assigning processors to the most worked domains. Since the particle work load varies over the course of the simulation, this algorithm determines each cycle if dynamic load balancing would speed up the calculation. If load balancing is required, a small number of particle communications are initiated in order to achieve load balance. This method has decreased the parallel run time by more than a factor of three for certain criticality calculations
A Dynamic Model for Load Balancing in Cloud Infrastructure
Directory of Open Access Journals (Sweden)
Jitendra Bhagwandas Bhatia
2015-08-01
Full Text Available This paper analysis various challenges faced in optimizing computing resource utilization via load balancing and presents a platform-independent model for load balancing which targets high availability of resources, low SLA (Service Level agreement violations and saves power. To achieve this, incoming requests are monitored for sudden burst, a prediction model is employed to maintain high availability and a power-aware algorithm is applied for choosing a suitable physical node for a virtual host. The proposed dynamic load balancing model provides a way to conflicting goals of saving power and maintaining high resource availability.For anyone building a private, public or hybrid IaaS cloud infrastructure, load balancing of virtual hosts on a limited number of physical nodes, becomes a crucial aspect. This paper analysis various challenges faced in optimizing computing resource utilization via load balancing and presents a platform independent model for load balancing which targets high availability of resources, low SLA (Service Level agreement violations and saves power. To achieve this, incoming requests are monitored for sudden burst, prediction model is employed to maintain high availability and power aware algorithm is applied for choosing a suitable physical node for virtual host. The proposed dynamic load balancing model provides a way to conflicting goals of saving power and maintaining high resource availability.
Load Balancing Routing with Bounded Stretch
Directory of Open Access Journals (Sweden)
Chen Siyuan
2010-01-01
Full Text Available Routing in wireless networks has been heavily studied in the last decade. Many routing protocols are based on classic shortest path algorithms. However, shortest path-based routing protocols suffer from uneven load distribution in the network, such as crowed center effect where the center nodes have more load than the nodes in the periphery. Aiming to balance the load, we propose a novel routing method, called Circular Sailing Routing (CSR, which can distribute the traffic more evenly in the network. The proposed method first maps the network onto a sphere via a simple stereographic projection, and then the route decision is made by a newly defined "circular distance" on the sphere instead of the Euclidean distance in the plane. We theoretically prove that for a network, the distance traveled by the packets using CSR is no more than a small constant factor of the minimum (the distance of the shortest path. We also extend CSR to a localized version, Localized CSR, by modifying greedy routing without any additional communication overhead. In addition, we investigate how to design CSR routing for 3D networks. For all proposed methods, we conduct extensive simulations to study their performances and compare them with global shortest path routing or greedy routing in 2D and 3D wireless networks.
Load balancing in integrated optical wireless networks
DEFF Research Database (Denmark)
Yan, Ying; Dittmann, Lars; Wong, S-W.
2010-01-01
In this paper, we tackle the load balancing problem in Integrated Optical Wireless Networks, where cell breathing technique is used to solve congestion by changing the coverage area of a fully loaded cell tower. Our objective is to design a load balancing mechanism which works closely...... with the integrated control scheme so as to maximize overall network throughput in the integrated network architecture. To the best of our knowledge no load balancing mechanisms, especially based on the Multi-Point Control Protocol (MPCP) defined in the IEEE 802.3ah, have been proposed so far. The major research...... issues are outlined and a cost function based optimization model is developed for power management. In particularly, two alternative feedback schemes are proposed to report wireless network status. Simulation results show that our proposed load balancing mechanism improves network performances....
Research on a Method of Geographical Information Service Load Balancing
Li, Heyuan; Li, Yongxing; Xue, Zhiyong; Feng, Tao
2018-05-01
With the development of geographical information service technologies, how to achieve the intelligent scheduling and high concurrent access of geographical information service resources based on load balancing is a focal point of current study. This paper presents an algorithm of dynamic load balancing. In the algorithm, types of geographical information service are matched with the corresponding server group, then the RED algorithm is combined with the method of double threshold effectively to judge the load state of serve node, finally the service is scheduled based on weighted probabilistic in a certain period. At the last, an experiment system is built based on cluster server, which proves the effectiveness of the method presented in this paper.
DNS load balancing in the CERN cloud
Reguero Naredo, Ignacio; Lobato Pardavila, Lorena
2017-10-01
Load Balancing is one of the technologies enabling deployment of large-scale applications on cloud resources. A DNS Load Balancer Daemon (LBD) has been developed at CERN as a cost-effective way to balance applications accepting DNS timing dynamics and not requiring persistence. It currently serves over 450 load-balanced aliases with two small VMs acting as master and slave. The aliases are mapped to DNS subdomains. These subdomains are managed with DDNS according to a load metric, which is collected from the alias member nodes with SNMP. During the last years, several improvements were brought to the software, for instance: support for IPv6, parallelization of the status requests, implementing the client in Python to allow for multiple aliases with differentiated states on the same machine or support for application state. The configuration of the Load Balancer is currently managed by a Puppet type. It discovers the alias member nodes and gets the alias definitions from the Ermis REST service. The Aiermis self-service GUI for the management of the LB aliases has been produced and is based on the Ermis service above that implements a form of Load Balancing as a Service (LBaaS). The Ermis REST API has authorisation based in Foreman hostgroups. The CERN DNS LBD is Open Software with Apache 2 license.
Software defined networks reactive flow programming and load balance switching
Καλλιανιώτης, Νικόλαος; Kallianiotis, Nikolaos
2017-01-01
This project serves as a Master Thesis as the requirements of the master’s programme Master of Digital Communications and Networks. It proposes load balancing algorithms applied to Software-Defined Networks to achieve the best possible resource utilisation of each of the links present in a network. The open-sources Opendaylight project and Floodlight project are used as SDN controllers, and the network is emulated using Mininet software
A Meta-Heuristic Load Balancer for Cloud Computing Systems
Sliwko, L.; Getov, Vladimir
2015-01-01
This paper introduces a strategy to allocate services on a cloud system without overloading the nodes and maintaining the system stability with minimum cost. We specify an abstract model of cloud resources utilization, including multiple types of resources as well as considerations for the service migration costs. A prototype meta-heuristic load balancer is demonstrated and experimental results are presented and discussed. We also propose a novel genetic algorithm, where population is seeded ...
Dynamic Load Balancing for PIC code using Eulerian/Lagrangian partitioning
Sauget, Marc; Latu, Guillaume
2017-01-01
This document presents an analysis of different load balance strategies for a Plasma physics code that models high energy particle beams with PIC method. A comparison of different load balancing algorithms is given: static or dynamic ones. Lagrangian and Eulerian partitioning techniques have been investigated.
Directory of Open Access Journals (Sweden)
Tsirakis Christos
2017-01-01
Full Text Available The expected huge increase of mobile devices and user data demand by 2020 will stress the current mobile network in an unprecedented way. The future mobile networks must meet several strong requirements regarding the data rate, latency, quality of service and experience, mobility, spectrum and energy efficiency. Therefore, efforts for more efficient mobile network solutions have been recently initiated. To this direction, load balancing has attracted much attention as a promising solution for higher resource utilization, improved system performance and decreased operational cost. It is an effective method for balancing the traffic and alleviating the congestion among heterogeneous networks in the upcoming 5G networks. In this paper, we focus on an offloading scenario for load balancing among LTE and Wi-Fi networks. Additionally, network graphs methodology and its abstracted parameters are investigated in order to better manage wireless resource allocation among multiple connections. The COHERENT architectural framework, which consists of two main control components, makes use of such abstracted network graphs for controlling or managing various tasks such as traffic steering, load balancing, spectrum sharing and RAN sharing. As a result, the COHERENT project eventually develops a unified programmable control framework used to efficiently coordinate the underlying heterogeneous mobile networks as a whole.
Bit Loading Algorithms for Cooperative OFDM Systems
Directory of Open Access Journals (Sweden)
Gui Bo
2008-01-01
Full Text Available Abstract We investigate the resource allocation problem for an OFDM cooperative network with a single source-destination pair and multiple relays. Assuming knowledge of the instantaneous channel gains for all links in the entire network, we propose several bit and power allocation schemes aiming at minimizing the total transmission power under a target rate constraint. First, an optimal and efficient bit loading algorithm is proposed when the relay node uses the same subchannel to relay the information transmitted by the source node. To further improve the performance gain, subchannel permutation, in which the subchannels are reallocated at relay nodes, is considered. An optimal subchannel permutation algorithm is first proposed and then an efficient suboptimal algorithm is considered to achieve a better complexity-performance tradeoff. A distributed bit loading algorithm is also proposed for ad hoc networks. Simulation results show that significant performance gains can be achieved by the proposed bit loading algorithms, especially when subchannel permutation is employed.
Bit Loading Algorithms for Cooperative OFDM Systems
Directory of Open Access Journals (Sweden)
Bo Gui
2007-12-01
Full Text Available We investigate the resource allocation problem for an OFDM cooperative network with a single source-destination pair and multiple relays. Assuming knowledge of the instantaneous channel gains for all links in the entire network, we propose several bit and power allocation schemes aiming at minimizing the total transmission power under a target rate constraint. First, an optimal and efficient bit loading algorithm is proposed when the relay node uses the same subchannel to relay the information transmitted by the source node. To further improve the performance gain, subchannel permutation, in which the subchannels are reallocated at relay nodes, is considered. An optimal subchannel permutation algorithm is first proposed and then an efficient suboptimal algorithm is considered to achieve a better complexity-performance tradeoff. A distributed bit loading algorithm is also proposed for ad hoc networks. Simulation results show that significant performance gains can be achieved by the proposed bit loading algorithms, especially when subchannel permutation is employed.
I/O load balancing for big data HPC applications
Energy Technology Data Exchange (ETDEWEB)
Paul, Arnab K. [Virginia Polytechnic Institute and State University; Goyal, Arpit [Virginia Polytechnic Institute and State University; Wang, Feiyi [ORNL; Oral, H Sarp [ORNL; Butt, Ali R. [Virginia Tech, Blacksburg, VA; Brim, Michael J. [ORNL; Srinivasa, Sangeetha B. [Virginia Polytechnic Institute and State University
2018-01-01
High Performance Computing (HPC) big data problems require efficient distributed storage systems. However, at scale, such storage systems often experience load imbalance and resource contention due to two factors: the bursty nature of scientific application I/O; and the complex I/O path that is without centralized arbitration and control. For example, the extant Lustre parallel file system-that supports many HPC centers-comprises numerous components connected via custom network topologies, and serves varying demands of a large number of users and applications. Consequently, some storage servers can be more loaded than others, which creates bottlenecks and reduces overall application I/O performance. Existing solutions typically focus on per application load balancing, and thus are not as effective given their lack of a global view of the system. In this paper, we propose a data-driven approach to load balance the I/O servers at scale, targeted at Lustre deployments. To this end, we design a global mapper on Lustre Metadata Server, which gathers runtime statistics from key storage components on the I/O path, and applies Markov chain modeling and a minimum-cost maximum-flow algorithm to decide where data should be placed. Evaluation using a realistic system simulator and a real setup shows that our approach yields better load balancing, which in turn can improve end-to-end performance.
Simulation model of load balancing in distributed computing systems
Botygin, I. A.; Popov, V. N.; Frolov, S. G.
2017-02-01
The availability of high-performance computing, high speed data transfer over the network and widespread of software for the design and pre-production in mechanical engineering have led to the fact that at the present time the large industrial enterprises and small engineering companies implement complex computer systems for efficient solutions of production and management tasks. Such computer systems are generally built on the basis of distributed heterogeneous computer systems. The analytical problems solved by such systems are the key models of research, but the system-wide problems of efficient distribution (balancing) of the computational load and accommodation input, intermediate and output databases are no less important. The main tasks of this balancing system are load and condition monitoring of compute nodes, and the selection of a node for transition of the user’s request in accordance with a predetermined algorithm. The load balancing is one of the most used methods of increasing productivity of distributed computing systems through the optimal allocation of tasks between the computer system nodes. Therefore, the development of methods and algorithms for computing optimal scheduling in a distributed system, dynamically changing its infrastructure, is an important task.
Green IGP Link Weights for Energy-efficiency and Load-balancing in IP Backbone Networks
Francois, Frederic; Wang, Ning; Moessner, Klaus; Georgoulas, Stylianos; Xu, Ke
2013-01-01
The energy consumption of backbone networks has become a primary concern for network operators and regulators due to the pervasive deployment of wired backbone networks to meet the requirements of bandwidth-hungry applications. While traditional optimization of IGP link weights has been used in IP based load-balancing operations, in this paper we introduce a novel link weight setting algorithm, the Green Load-balancing Algorithm (GLA), which is able to jointly optimize both energy efficiency ...
Energy-balanced algorithm for RFID estimation
Zhao, Jumin; Wang, Fangyuan; Li, Dengao; Yan, Lijuan
2016-10-01
RFID has been widely used in various commercial applications, ranging from inventory control, supply chain management to object tracking. It is necessary for us to estimate the number of RFID tags deployed in a large area periodically and automatically. Most of the prior works use passive tags to estimate and focus on designing time-efficient algorithms that can estimate tens of thousands of tags in seconds. But for a RFID reader to access tags in a large area, active tags are likely to be used due to their longer operational ranges. But these tags use their own battery as energy supplier. Hence, conserving energy for active tags becomes critical. Some prior works have studied how to reduce energy expenditure of a RFID reader when it reads tags IDs. In this paper, we study how to reduce the amount of energy consumed by active tags during the process of estimating the number of tags in a system and make the energy every tag consumed balanced approximately. We design energy-balanced estimation algorithm that can achieve our goal we mentioned above.
Genetic algorithms in loading pattern optimization
International Nuclear Information System (INIS)
Yilmazbayhan, A.; Tombakoglu, M.; Bekar, K. B.; Erdemli, A. Oe
2001-01-01
Genetic Algorithm (GA) based systems are used for the loading pattern optimization. The use of Genetic Algorithm operators such as regional crossover, crossover and mutation, and selection of initial population size for PWRs are discussed. Antithetic variates are used to generate the initial population. The performance of GA with antithetic variates is compared to traditional GA. The results of multi-cycle optimization are discussed for objective function taking into account cycle burn-up and discharge burn-up
Node Load Balance Multi-flow Opportunistic Routing in Wireless Mesh Networks
Directory of Open Access Journals (Sweden)
Wang Tao
2014-04-01
Full Text Available Opportunistic routing (OR has been proposed to improve the performance of wireless networks by exploiting the multi-user diversity and broadcast nature of the wireless medium. It involves multiple candidate forwarders to relay packets every hop. The existing OR doesn’t take account of the traffic load and load balance, therefore some nodes may be overloaded while the others may not, leading to network performance decline. In this paper, we focus on opportunities routing selection with node load balance which is described as a convex optimization problem. To solve the problem, by combining primal-dual and sub-gradient methods, a fully distributed Node load balance Multi-flow Opportunistic Routing algorithm (NMOR is proposed. With node load balance constraint, NMOR allocates the flow rate iteratively and the rate allocation decides the candidate forwarder selection of opportunities routing. The simulation results show that NMOR algorithm improves 100 %, 62 % of the aggregative throughput than ETX and EAX, respectively.
A comparative experiment in distributed load balancing
Randles, Martin
2009-12-01
The anticipated uptake of Cloud computing, built on the well-established research fields of web services, networks, utility computing, distributed computing and virtualisation, will bring many advantages in cost, flexibility and availability for service users. These benefits are expected to further drive the demand for cloud services, increasing both the cloud customer base and the scale of cloud installations. This has implications for many technical issues in such Service Oriented Architectures and Internet of Services (IoS) type applications; fault tolerance, high availability and scalability for examples. Central to these issues is the establishment of effective load balancing techniques. It is clear that the scale and complexity of these systems makes centralized individual assignment of jobs to specific servers infeasible; leading to the need for an effective distributed solution. This paper investigates three possible distributed solutions, which have been proposed for load balancing: An approach inspired by the foraging behaviour of the Honeybee, Biased Random Sampling and Active Clustering. © 2009 IEEE.
Neural Network Algorithm for Particle Loading
International Nuclear Information System (INIS)
Lewandowski, J.L.V.
2003-01-01
An artificial neural network algorithm for continuous minimization is developed and applied to the case of numerical particle loading. It is shown that higher-order moments of the probability distribution function can be efficiently renormalized using this technique. A general neural network for the renormalization of an arbitrary number of moments is given
Loading pattern optimization using ant colony algorithm
International Nuclear Information System (INIS)
Hoareau, Fabrice
2008-01-01
Electricite de France (EDF) operates 58 nuclear power plants (NPP), of the Pressurized Water Reactor type. The loading pattern optimization of these NPP is currently done by EDF expert engineers. Within this framework, EDF R and D has developed automatic optimization tools that assist the experts. LOOP is an industrial tool, developed by EDF R and D and based on a simulated annealing algorithm. In order to improve the results of such automatic tools, new optimization methods have to be tested. Ant Colony Optimization (ACO) algorithms are recent methods that have given very good results on combinatorial optimization problems. In order to evaluate the performance of such methods on loading pattern optimization, direct comparisons between LOOP and a mock-up based on the Max-Min Ant System algorithm (a particular variant of ACO algorithms) were made on realistic test-cases. It is shown that the results obtained by the ACO mock-up are very similar to those of LOOP. Future research will consist in improving these encouraging results by using parallelization and by hybridizing the ACO algorithm with local search procedures. (author)
Two-Step Load Balancing Scheme for Fairness Improvement in ...
African Journals Online (AJOL)
ABSTRACT: The problem of load imbalance in HetNets among wireless access technologies is addressed in this article. ... balancing could either mean balancing the transmit power or the radio ..... Weight for Multimedia Transmission.
SYMMETRICAL (AND GENERIC) ALGORITHMS FOR HEIGHT BALANCED TREES
BRON, C
1990-01-01
Most algorithms for height balanced trees (or AVL-trees, after Adelson-Velskii and Landis [1]) suffer from a lack of exploitation of the symmetry of balance restoring operations when insertions and deletions in such tree structures are being made. Either we find algorithms in duplicate (i.e.,
Study of load balancing technology for EAST data management
Energy Technology Data Exchange (ETDEWEB)
Li, Shi, E-mail: lishi@ipp.ac.cn [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei, Anhui (China); Wang, Feng [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei, Anhui (China); Xiao, Bingjia [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei, Anhui (China); School of Nuclear Science and Technology, University of Science and Technology of China, Hefei, Anhui (China); Yang, Fei [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei, Anhui (China); Department of Computer Science, Anhui Medical University, Hefei, Anhui (China); Sun, Xiaoyang; Wang, Yong [Institute of Plasma Physics, Chinese Academy of Sciences, Hefei, Anhui (China)
2014-05-15
Highlights: • The load balancing concept is introduced into the MDSplus data service. • The new data service system based on the LVS framework and heartbeat technologies are described. • The scheduling algorithm “WLC” is used, and a software system is developed for optimizing the weight of node server. - Abstract: With the continuous renewal and increasing number of diagnostics, the EAST tokamak routinely generates ∼3 GB of raw data per pulse of the experiment, which is transferred to a centralized data management system. In order to strengthen international cooperation, all the acquired data has been converted and stored in the MDSplus servers. During the data system operation, there are some problems when a lot of client machines connect to a single MDSplus data server. Because the server process keeps the connection until the client closes its connection, a lot of server processes use a lot of network ports and consume a large amount of memory, so that the speed of access to data is very slow, but the CPU resource is not fully utilized. To improve data management system performance, many MDSplus servers will be installed on the blade server and form a server cluster to realize load balancing and high availability by using LVS and heartbeat technology. This paper will describe the details of the design and the test results.
Directory of Open Access Journals (Sweden)
K. Mohaideen Pitchai
2017-07-01
Full Text Available Wireless Sensor Network (WSN consists of a large number of small sensors with restricted energy. Prolonged network lifespan, scalability, node mobility and load balancing are important needs for several WSN applications. Clustering the sensor nodes is an efficient technique to reach these goals. WSN have the characteristics of topology dynamics because of factors like energy conservation and node movement that leads to Dynamic Load Balanced Clustering Problem (DLBCP. In this paper, Elitism based Random Immigrant Genetic Approach (ERIGA is proposed to solve DLBCP which adapts to topology dynamics. ERIGA uses the dynamic Genetic Algorithm (GA components for solving the DLBCP. The performance of load balanced clustering process is enhanced with the help of this dynamic GA. As a result, the ERIGA achieves to elect suitable cluster heads which balances the network load and increases the lifespan of the network.
Partial Key Grouping: Load-Balanced Partitioning of Distributed Streams
Nasir, Muhammad Anis Uddin; Morales, Gianmarco De Francisci; Garcia-Soriano, David; Kourtellis, Nicolas; Serafini, Marco
2015-01-01
We study the problem of load balancing in distributed stream processing engines, which is exacerbated in the presence of skew. We introduce PARTIAL KEY GROUPING (PKG), a new stream partitioning scheme that adapts the classical “power of two choices” to a distributed streaming setting by leveraging two novel techniques: key splitting and local load estimation. In so doing, it achieves better load balancing than key grouping while being more scalable than shuffle grouping. We test PKG on severa...
Two Stage Secure Dynamic Load Balancing Architecture for SIP Server Clusters
Directory of Open Access Journals (Sweden)
G. Vennila
2014-08-01
Full Text Available Session Initiation Protocol (SIP is a signaling protocol emerged with an aim to enhance the IP network capabilities in terms of complex service provision. SIP server scalability with load balancing has a greater concern due to the dramatic increase in SIP service demand. Load balancing of session method (request/response and security measures optimizes the SIP server to regulate of network traffic in Voice over Internet Protocol (VoIP. Establishing a honeywall prior to the load balancer significantly reduces SIP traffic and drops inbound malicious load. In this paper, we propose Active Least Call in SIP Server (ALC_Server algorithm fulfills objectives like congestion avoidance, improved response times, throughput, resource utilization, reducing server faults, scalability and protection of SIP call from DoS attacks. From the test bed, the proposed two-tier architecture demonstrates that the ALC_Server method dynamically controls the overload and provides robust security, uniform load distribution for SIP servers.
Hu, Weiming; Fan, Yabo; Xing, Junliang; Sun, Liang; Cai, Zhaoquan; Maybank, Stephen
2018-09-01
We construct a new efficient near duplicate image detection method using a hierarchical hash code learning neural network and load-balanced locality-sensitive hashing (LSH) indexing. We propose a deep constrained siamese hash coding neural network combined with deep feature learning. Our neural network is able to extract effective features for near duplicate image detection. The extracted features are used to construct a LSH-based index. We propose a load-balanced LSH method to produce load-balanced buckets in the hashing process. The load-balanced LSH significantly reduces the query time. Based on the proposed load-balanced LSH, we design an effective and feasible algorithm for near duplicate image detection. Extensive experiments on three benchmark data sets demonstrate the effectiveness of our deep siamese hash encoding network and load-balanced LSH.
Static and dynamic load-balancing strategies for parallel reservoir simulation
International Nuclear Information System (INIS)
Anguille, L.; Killough, J.E.; Li, T.M.C.; Toepfer, J.L.
1995-01-01
Accurate simulation of the complex phenomena that occur in flow in porous media can tax even the most powerful serial computers. Emergence of new parallel computer architectures as a future efficient tool in reservoir simulation may overcome this difficulty. Unfortunately, major problems remain to be solved before using parallel computers commercially: production serial programs must be rewritten to be efficient in parallel environments and load balancing methods must be explored to evenly distribute the workload on each processor during the simulation. This study implements both a static load-balancing algorithm and a receiver-initiated dynamic load-sharing algorithm to achieve high parallel efficiencies on both the IBM SP2 and Intel IPSC/860 parallel computers. Significant speedup improvement was recorded for both methods. Further optimization of these algorithms yielded a technique with efficiencies as high as 90% and 70% on 8 and 32 nodes, respectively. The increased performance was the result of the minimization of message-passing overhead
A high performance load balance strategy for real-time multicore systems.
Cho, Keng-Mao; Tsai, Chun-Wei; Chiu, Yi-Shiuan; Yang, Chu-Sing
2014-01-01
Finding ways to distribute workloads to each processor core and efficiently reduce power consumption is of vital importance, especially for real-time systems. In this paper, a novel scheduling algorithm is proposed for real-time multicore systems to balance the computation loads and save power. The developed algorithm simultaneously considers multiple criteria, a novel factor, and task deadline, and is called power and deadline-aware multicore scheduling (PDAMS). Experiment results show that the proposed algorithm can greatly reduce energy consumption by up to 54.2% and the deadline times missed, as compared to the other scheduling algorithms outlined in this paper.
A High Performance Load Balance Strategy for Real-Time Multicore Systems
Directory of Open Access Journals (Sweden)
Keng-Mao Cho
2014-01-01
Full Text Available Finding ways to distribute workloads to each processor core and efficiently reduce power consumption is of vital importance, especially for real-time systems. In this paper, a novel scheduling algorithm is proposed for real-time multicore systems to balance the computation loads and save power. The developed algorithm simultaneously considers multiple criteria, a novel factor, and task deadline, and is called power and deadline-aware multicore scheduling (PDAMS. Experiment results show that the proposed algorithm can greatly reduce energy consumption by up to 54.2% and the deadline times missed, as compared to the other scheduling algorithms outlined in this paper.
Implementation of GAMMON - An efficient load balancing strategy for a local computer system
Baumgartner, Katherine M.; Kling, Ralph M.; Wah, Benjamin W.
1989-01-01
GAMMON (Global Allocation from Maximum to Minimum in cONstant time), an efficient load-balancing algorithm, is described. GAMMON uses the available broadcast capability of multiaccess networks to implement an efficient search technique for finding hosts with maximal and minimal loads. The search technique has an average overhead which is independent of the number of participating stations. The transition from the theoretical concept to a practical, reliable, and efficient implementation is described.
Design of a Load-Balancing Architecture For Parallel Firewalls
National Research Council Canada - National Science Library
Joyner, William
1999-01-01
.... This thesis proposes a load-balancing firewall architecture to meet the Navy's needs. It first conducts an architectural analysis of the problem and then presents a high-level system design as a solution...
Efektifitas Load Balancing Dalam Mengurangi Kemacetan Lalu Lintas
Directory of Open Access Journals (Sweden)
Erwin Harahap
2017-12-01
Full Text Available Abstrak. Kemacetan jalan raya merupakan permasalahan umum di setiap kota yang memerlukan penanganan serius. Pemecahan permasalahan kemacetan jalan raya tidak hanya dapat diselesaikan dengan hanya meningkatkan kualitas dan kuantitas infrastruktur, namun juga manajemen lalu lintas. Pada artikel diusulkan suatu metode untuk mengurangi kemacetan lalu lintas, yaitu dengan menyeimbangkan beban ke berbagai ruas jalan yang disebut dengan load balancing. Melalui metode ini diharapkan beban lalu lintas terbagi secara merata ke berbagai jalur alternatif sedemikian sehingga antrian panjang kendaraan dapat dihindari. Evaluasi efektifitas dari metode load balancing ini dilakukan melalui simulasi dengan mengimplementasikan salah satu bidang ilmu Matematika, yaitu teori Antrian. Simulasi dibuat dengan menggunakan toolbox SimEvents yang dijalankan pada software MATLAB. Kata Kunci: load balancing, kemacetan, lalu lintas, sim-events, matlab Abstract. (the effectiveness of load balancing in reducing the road traffic congestion Road congestion is a common problem in any city that needs serious handling. The solution of the road congestion problems can not only be solved by simply improving the quality and quantity of infrastructure, but also the traffic management. In this article, we proposed a method to reduce the traffic congestion by balancing the vehicle loads to a various road segments, called as load balancing. Through this method, it is expected that the traffic load is evenly distributed to various alternative routes, such that, long queues and traffic jam can be avoided. Evaluation of the load balancing’s effectiveness is performed through a simulation by implementing the Queueing Theory. Simulations are created using the SimEvents toolbox that runs on MATLAB software. Keywords: load balancing, road congestion, traffic, simevents, matlab.
MVDR Algorithm Based on Estimated Diagonal Loading for Beamforming
Directory of Open Access Journals (Sweden)
Yuteng Xiao
2017-01-01
Full Text Available Beamforming algorithm is widely used in many signal processing fields. At present, the typical beamforming algorithm is MVDR (Minimum Variance Distortionless Response. However, the performance of MVDR algorithm relies on the accurate covariance matrix. The MVDR algorithm declines dramatically with the inaccurate covariance matrix. To solve the problem, studying the beamforming array signal model and beamforming MVDR algorithm, we improve MVDR algorithm based on estimated diagonal loading for beamforming. MVDR optimization model based on diagonal loading compensation is established and the interval of the diagonal loading compensation value is deduced on the basis of the matrix theory. The optimal diagonal loading value in the interval is also determined through the experimental method. The experimental results show that the algorithm compared with existing algorithms is practical and effective.
Physical load handling and listening comprehension effects on balance control.
Qu, Xingda
2010-12-01
The purpose of this study was to determine the physical load handling and listening comprehension effects on balance control. A total of 16 young and 16 elderly participants were recruited in this study. The physical load handling task required holding a 5-kg load in each hand with arms at sides. The listening comprehension task involved attentive listening to a short conversation. Three short questions were asked regarding the conversation right after the testing trial to test the participants' attentiveness during the experiment. Balance control was assessed by centre of pressure-based measures, which were calculated from the force platform data when the participants were quietly standing upright on a force platform. Results from this study showed that both physical load handling and listening comprehension adversely affected balance control. Physical load handling had a more deleterious effect on balance control under the listening comprehension condition vs. no-listening comprehension condition. Based on the findings from this study, interventions for the improvement of balance could be focused on avoiding exposures to physically demanding tasks and cognitively demanding tasks simultaneously. STATEMENT OF RELEVANCE: Findings from this study can aid in better understanding how humans maintain balance, especially when physical and cognitive loads are applied. Such information is useful for developing interventions to prevent fall incidents and injuries in occupational settings and daily activities.
General Influence Coefficient Algorithm in Balancing of Rotating Machinery
Directory of Open Access Journals (Sweden)
Xiaoping Yu
2004-01-01
Full Text Available The General Influence Coefficient Algorithm (GICA, developed in this article, is a new calculation method for Influence Coefficients (ICs with a general formula. Compared to the traditional calculation method, GICA can solve the ICs' calculation task when the group of trial weights are installed on the rotor each time, the trial weights are retained on the rotor systems, or there is redundant trial balancing data, when even part of the ICs is known. GICA is also a powerful tool for refining the ICs from redundant balancing data or historical balancing data and serves as a general algorithm. With the general matrix formula, GICA is ready to be applied in a computer-aided balancing system as the key part of calculation software. Examples in industry are also presented to demonstrate the aplication of this new algorithm.
A Novel Assembly Line Balancing Method Based on PSO Algorithm
Directory of Open Access Journals (Sweden)
Xiaomei Hu
2014-01-01
Full Text Available Assembly line is widely used in manufacturing system. Assembly line balancing problem is a crucial question during design and management of assembly lines since it directly affects the productivity of the whole manufacturing system. The model of assembly line balancing problem is put forward and a general optimization method is proposed. The key data on assembly line balancing problem is confirmed, and the precedence relations diagram is described. A double objective optimization model based on takt time and smoothness index is built, and balance optimization scheme based on PSO algorithm is proposed. Through the simulation experiments of examples, the feasibility and validity of the assembly line balancing method based on PSO algorithm is proved.
Line Balancing Using Largest Candidate Rule Algorithm In A Garment Industry: A Case Study
Directory of Open Access Journals (Sweden)
V. P.Jaganathan
2014-12-01
Full Text Available The emergence of fast changes in fashion has given rise to the need to shorten production cycle times in the garment industry. As effective usage of resources has a significant effect on the productivity and efficiency of production operations, garment manufacturers are urged to utilize their resources effectively in order to meet dynamic customer demand. This paper focuses specifically on line balancing and layout modification. The aim of assembly line balance in sewing lines is to assign tasks to the workstations, so that the machines of the workstation can perform the assigned tasks with a balanced loading. Largest Candidate Rule Algorithm (LCR has been deployed in this paper.
A robust embedded vision system feasible white balance algorithm
Wang, Yuan; Yu, Feihong
2018-01-01
White balance is a very important part of the color image processing pipeline. In order to meet the need of efficiency and accuracy in embedded machine vision processing system, an efficient and robust white balance algorithm combining several classical ones is proposed. The proposed algorithm mainly has three parts. Firstly, in order to guarantee higher efficiency, an initial parameter calculated from the statistics of R, G and B components from raw data is used to initialize the following iterative method. After that, the bilinear interpolation algorithm is utilized to implement demosaicing procedure. Finally, an adaptive step adjustable scheme is introduced to ensure the controllability and robustness of the algorithm. In order to verify the proposed algorithm's performance on embedded vision system, a smart camera based on IMX6 DualLite, IMX291 and XC6130 is designed. Extensive experiments on a large amount of images under different color temperatures and exposure conditions illustrate that the proposed white balance algorithm avoids color deviation problem effectively, achieves a good balance between efficiency and quality, and is suitable for embedded machine vision processing system.
Fuzzy pool balance: An algorithm to achieve a two dimensional balance in distribute storage systems
International Nuclear Information System (INIS)
Wu, Wenjing; Chen, Gang
2014-01-01
The limitation of scheduling modules and the gradual addition of disk pools in distributed storage systems often result in imbalances among their disk pools in terms of both disk usage and file count. This can cause various problems to the storage system such as single point of failure, low system throughput and imbalanced resource utilization and system loads. An algorithm named Fuzzy Pool Balance (FPB) is proposed here to solve this problem. The input of FPB is the current file distribution among disk pools and the output is a file migration plan indicating what files are to be migrated to which pools. FPB uses an array to classify the files by their sizes. The file classification array is dynamically calculated with a defined threshold named T max that defines the allowed pool disk usage deviations. File classification is the basis of file migration. FPB also defines the Immigration Pool (IP) and Emigration Pool (EP) according to the pool disk usage and File Quantity Ratio (FQR) that indicates the percentage of each category of files in each disk pool, so files with higher FQR in an EP will be migrated to IP(s) with a lower FQR of this file category. To verify this algorithm, we implemented FPB on an ATLAS Tier2 dCache production system. The results show that FPB can achieve a very good balance in both free space and file counts, and adjusting the threshold value T max and the correction factor to the average FQR can achieve a tradeoff between free space and file count.
Directory of Open Access Journals (Sweden)
Johan Parent
2004-01-01
Full Text Available We report on the improvements that can be achieved by applying machine learning techniques, in particular reinforcement learning, for the dynamic load balancing of parallel applications. The applications being considered in this paper are coarse grain data intensive applications. Such applications put high pressure on the interconnect of the hardware. Synchronization and load balancing in complex, heterogeneous networks need fast, flexible, adaptive load balancing algorithms. Viewing a parallel application as a one-state coordination game in the framework of multi-agent reinforcement learning, and by using a recently introduced multi-agent exploration technique, we are able to improve upon the classic job farming approach. The improvements are achieved with limited computation and communication overhead.
Improvement on LiFePO4 Cell Balancing Algorithm
Vencislav C. Valchev; Plamen V. Yankov; Dimo D. Stefanov
2018-01-01
The paper presents improvement on operation time of cell balancing algorithm compared to conventional multiple cell LiFePO4 charge methodology. A flowchart is synthesised to explain the main steps of the software design, which afterwards is implemented in a microcontroller. Experimental results are provided to clarify the transition between charge and balance process. Graphical data for a voltage equalization of eight cells is presented to verify the proposed improvement.
Improvement on LiFePO4 Cell Balancing Algorithm
Directory of Open Access Journals (Sweden)
Vencislav C. Valchev
2018-02-01
Full Text Available The paper presents improvement on operation time of cell balancing algorithm compared to conventional multiple cell LiFePO4 charge methodology. A flowchart is synthesised to explain the main steps of the software design, which afterwards is implemented in a microcontroller. Experimental results are provided to clarify the transition between charge and balance process. Graphical data for a voltage equalization of eight cells is presented to verify the proposed improvement.
Directory of Open Access Journals (Sweden)
Alimuddin Alimuddin
2016-01-01
Full Text Available The application of academic information system (siakad a web-based college is essential to improve the academic services. Siakad the application has many obstacles, especially in dealing with a high amount of access that caused the overload. Moreover in case of hardware or software failure caused siakad inaccessible. The solution of this problem is the use of many existing servers where the load is distributed in the respective server. Need a method of distributing the load evenly in the respective server load balancing is the method by round robin algorithm so high siakad scalability. As for dealing with the failure of a server need fault tolerance for the availability siakad be high. This research is to develop methods of load balancing and fault tolerance using software linux virtual server and some additional programs such as ipvsadm and heartbeat that has the ability to increase scalability and availability siakad. The results showed that with load balancing to minimize the response time to 5,7%, increase throughput by 37% or 1,6 times and maximize resource utilization or utilization of 1,6 times increased, and avoid overload. While high availability is obtained from the server's ability to perform failover or move another server in the event of failure. Thus implementing load balancing and fault tolerance can improve the service performance of siakad and avoid mistakes.
A Location Selection Policy of Live Virtual Machine Migration for Power Saving and Load Balancing
Directory of Open Access Journals (Sweden)
Jia Zhao
2013-01-01
Full Text Available Green cloud data center has become a research hotspot of virtualized cloud computing architecture. And load balancing has also been one of the most important goals in cloud data centers. Since live virtual machine (VM migration technology is widely used and studied in cloud computing, we have focused on location selection (migration policy of live VM migration for power saving and load balancing. We propose a novel approach MOGA-LS, which is a heuristic and self-adaptive multiobjective optimization algorithm based on the improved genetic algorithm (GA. This paper has presented the specific design and implementation of MOGA-LS such as the design of the genetic operators, fitness values, and elitism. We have introduced the Pareto dominance theory and the simulated annealing (SA idea into MOGA-LS and have presented the specific process to get the final solution, and thus, the whole approach achieves a long-term efficient optimization for power saving and load balancing. The experimental results demonstrate that MOGA-LS evidently reduces the total incremental power consumption and better protects the performance of VM migration and achieves the balancing of system load compared with the existing research. It makes the result of live VM migration more high-effective and meaningful.
A location selection policy of live virtual machine migration for power saving and load balancing.
Zhao, Jia; Ding, Yan; Xu, Gaochao; Hu, Liang; Dong, Yushuang; Fu, Xiaodong
2013-01-01
Green cloud data center has become a research hotspot of virtualized cloud computing architecture. And load balancing has also been one of the most important goals in cloud data centers. Since live virtual machine (VM) migration technology is widely used and studied in cloud computing, we have focused on location selection (migration policy) of live VM migration for power saving and load balancing. We propose a novel approach MOGA-LS, which is a heuristic and self-adaptive multiobjective optimization algorithm based on the improved genetic algorithm (GA). This paper has presented the specific design and implementation of MOGA-LS such as the design of the genetic operators, fitness values, and elitism. We have introduced the Pareto dominance theory and the simulated annealing (SA) idea into MOGA-LS and have presented the specific process to get the final solution, and thus, the whole approach achieves a long-term efficient optimization for power saving and load balancing. The experimental results demonstrate that MOGA-LS evidently reduces the total incremental power consumption and better protects the performance of VM migration and achieves the balancing of system load compared with the existing research. It makes the result of live VM migration more high-effective and meaningful.
On delay adjustment for dynamic load balancing in distributed virtual environments.
Deng, Yunhua; Lau, Rynson W H
2012-04-01
Distributed virtual environments (DVEs) are becoming very popular in recent years, due to the rapid growing of applications, such as massive multiplayer online games (MMOGs). As the number of concurrent users increases, scalability becomes one of the major challenges in designing an interactive DVE system. One solution to address this scalability problem is to adopt a multi-server architecture. While some methods focus on the quality of partitioning the load among the servers, others focus on the efficiency of the partitioning process itself. However, all these methods neglect the effect of network delay among the servers on the accuracy of the load balancing solutions. As we show in this paper, the change in the load of the servers due to network delay would affect the performance of the load balancing algorithm. In this work, we conduct a formal analysis of this problem and discuss two efficient delay adjustment schemes to address the problem. Our experimental results show that our proposed schemes can significantly improve the performance of the load balancing algorithm with neglectable computation overhead.
Power Balance AODV Routing Algorithm of WSN in Precision Agriculture Environment Monitoring
Directory of Open Access Journals (Sweden)
Xiaoqin Qin
2013-11-01
Full Text Available As one of important technologies of IOT (Internet of Things, WSN (Wireless Sensor Networks has been widely used in precision agriculture environment monitoring. WSN is a kind of energy-constrained network, but power balance is not taken into account in traditional routing protocols. A novel routing algorithm, named Power Balance Ad hoc On-Demand Distance Vector (PB-AODV, is proposed on cross-layer design. In the route discovery process of PB-AODV, routing path is established by the Received Signal Strength Indication (RSSI value. The optimal transmitting power, which is computed according to RSSI value, power threshold and node’s surplus energy, is encapsulated into Route Reply Packet. Hence, the sender node can adjust its transmission power to save energy according to the Route Reply Packet. Simulation results show that the proposed algorithm is effective for load balancing, and increases the WSN’s lifetime 14.3% consequently.
Load Balanced Mapping of Distributed Objects to Minimize Network Communication
Stoyenko, Alexander D.; Bosch, J.; Bosch, Jan; Aksit, Mehmet; Marlowe, Thomas J.
1996-01-01
This paper introduces a new load balancing and communica- tion minimizing heuristic used in the Inverse Remote Procedure Call (IRPC) system. While the paper briefly describes the IRPC system, the focus is on the new IRPC assignment heuristic. The IRPC compiler maps a distributed program to a graph
Reimplementing the LBD DNS Load Balancer with concurrency in GO
CERN. Geneva
2016-01-01
Using the current configuration with 430 aliases, today’s implementation of the LBD DNS Load Balancer does one cycle through all aliases in around 240 seconds. We have a scalability limit of 300 seconds - that is the update period of most aliases. This talk will present a PoC showing how the time could be reduced to just 12 seconds.
Bin-packing problems with load balancing and stability constraints
DEFF Research Database (Denmark)
Trivella, Alessio; Pisinger, David
apper in a wide range of disciplines, including transportation and logistics, computer science, engineering, economics and manufacturing. The problem is well-known to be N P-hard and difficult to solve in practice, especially when dealing with the multi-dimensional cases. Closely connected to the BPP...... realistic constraints related to e.g. load balancing, cargo stability and weight limits, in the multi-dimensional BPP. The BPP poses additional challenges compared to the CLP due to the supplementary objective of minimizing the number of bins. In particular, in section 2 we discuss how to integrate bin......-packing and load balancing of items. The problem has only been considered in the literature in simplified versions, e.g. balancing a single bin or introducing a feasible region for the barycenter. In section 3 we generalize the problem to handle cargo stability and weight constraints....
A strategy for load balancing in distributed storage systems
CERN. Geneva
2012-01-01
Distributed storage systems are critical to the operation of the WLCG. These systems are not limited to fulfilling the long term storage requirements. They also serve data for computational analysis and other computational jobs. Distributed storage systems provide the ability to aggregate the storage and IO capacity of disks and tapes, but at the end of the day IO rate is still bound by the capabilities of the hardware, in particular the hard drives. Throughput of hard drives has increased dramatically over the decades, however for computational analysis IOPS is typically the limiting factor. To maximize return of investment, balancing IO load over available hardware is crucial. The task is made complicated by the common use of heterogeneous hardware and software environments that results from combining new and old hardware into a single storage system. This paper describes recent advances made in load balancing in the dCache distributed storage system. We describe a set of common requirements for load balan...
Directory of Open Access Journals (Sweden)
Hyun-Woo Kim
2016-05-01
Full Text Available Recent advancements in Information Technology (IT have sparked the creation of numerous and diverse types of devices and services. Manual data collection measurement methods have been automated through the use of various wireless or wired sensors. Single sensor devices are included in smart devices such as smartphones. Data transmission is critical for big data collected from sensor nodes, such as Mobile Sensor Nodes (MSNs, where sensors move dynamically according to sensor mobility, or Fixed Sensor Nodes (FSNs, where sensor locations are decided by the users. False data transfer processing of big data results in topology lifespan reduction and data transfer delays. Hence, a variety of simulators and diverse load-balancing algorithms have been developed as protocol verification tools for topology lifespan maximization and effective data transfer processing. However, those previously developed simulators have limited functions, such as an event function for a specific sensor or a battery consumption rate test for sensor deployment. Moreover, since the previous load-balancing algorithms consider only the general traffic distribution and the number of connected nodes without considering the current topology condition, the sustainable load-balancing technique that takes into account the battery consumption rate of the dispersed sensor nodes is required. Therefore, this paper proposes the Sustainable Load-balancing Scheme (SLS, which maximizes the overall topology lifespan through effective and sustainable load-balancing of data transfer among the sensors. SLS is capable of maintaining an effective topology as it considers both the battery consumption rate of the sensors and the data transfer delay.
The Automated Assessment of Postural Stability: Balance Detection Algorithm.
Napoli, Alessandro; Glass, Stephen M; Tucker, Carole; Obeid, Iyad
2017-12-01
Impaired balance is a common indicator of mild traumatic brain injury, concussion and musculoskeletal injury. Given the clinical relevance of such injuries, especially in military settings, it is paramount to develop more accurate and reliable on-field evaluation tools. This work presents the design and implementation of the automated assessment of postural stability (AAPS) system, for on-field evaluations following concussion. The AAPS is a computer system, based on inexpensive off-the-shelf components and custom software, that aims to automatically and reliably evaluate balance deficits, by replicating a known on-field clinical test, namely, the Balance Error Scoring System (BESS). The AAPS main innovation is its balance error detection algorithm that has been designed to acquire data from a Microsoft Kinect ® sensor and convert them into clinically-relevant BESS scores, using the same detection criteria defined by the original BESS test. In order to assess the AAPS balance evaluation capability, a total of 15 healthy subjects (7 male, 8 female) were required to perform the BESS test, while simultaneously being tracked by a Kinect 2.0 sensor and a professional-grade motion capture system (Qualisys AB, Gothenburg, Sweden). High definition videos with BESS trials were scored off-line by three experienced observers for reference scores. AAPS performance was assessed by comparing the AAPS automated scores to those derived by three experienced observers. Our results show that the AAPS error detection algorithm presented here can accurately and precisely detect balance deficits with performance levels that are comparable to those of experienced medical personnel. Specifically, agreement levels between the AAPS algorithm and the human average BESS scores ranging between 87.9% (single-leg on foam) and 99.8% (double-leg on firm ground) were detected. Moreover, statistically significant differences in balance scores were not detected by an ANOVA test with alpha equal to 0
Implementing peak load reduction algorithms for household electrical appliances
International Nuclear Information System (INIS)
Dlamini, Ndumiso G.; Cromieres, Fabien
2012-01-01
Considering household appliance automation for reduction of household peak power demand, this study explored aspects of the interaction between household automation technology and human behaviour. Given a programmable household appliance switching system, and user-reported appliance use times, we simulated the load reduction effectiveness of three types of algorithms, which were applied at both the single household level and across all 30 households. All three algorithms effected significant load reductions, while the least-to-highest potential user inconvenience ranking was: coordinating the timing of frequent intermittent loads (algorithm 2); moving period-of-day time-flexible loads to off-peak times (algorithm 1); and applying short-term time delays to avoid high peaks (algorithm 3) (least accommodating). Peak reduction was facilitated by load interruptibility, time of use flexibility and the willingness of users to forgo impulsive appliance use. We conclude that a general factor determining the ability to shift the load due to a particular appliance is the time-buffering between the service delivered and the power demand of an appliance. Time-buffering can be ‘technologically inherent’, due to human habits, or realised by managing user expectations. There are implications for the design of appliances and home automation systems. - Highlights: ► We explored the interaction between appliance automation and human behaviour. ► There is potential for considerable load shifting of household appliances. ► Load shifting for load reduction is eased with increased time buffering. ► Design, human habits and user expectations all influence time buffering. ► Certain automation and appliance design features can facilitate load shifting.
Dynamic load-balancing-extended gradient mechanism: Graphic representation
Energy Technology Data Exchange (ETDEWEB)
Muniz, Francisco J., E-mail: muniz@cdtn.br [Centro de Desenvolvimento da Tecnologia Nuclear (CDTN/CNEN-MG), Belo Horizonte, MG (Brazil)
2017-07-01
Load-balancing methods are quite well described in the open literature (hundreds of articles can be found about this subject). In particularly, about the Dynamic Load-balancing mechanism Extended Gradient (EG), several articles of the author are available. Even though, there are some overlap, each one of them is focused on a particular aspect of the mechanism, in a complementary way. In this article, a graphic representation of the Extended Gradient mechanism is done: this representation way had not yet been explored. However, for an in-depth knowledge of the Extended Gradient mechanism, at least, some other articles should to be read. In the CDTN, Clusters are used, mainly, in deterministic methods (CFD) and non-deterministic methods (Monte Carlo). (author)
Dynamic load-balancing-extended gradient mechanism: Graphic representation
International Nuclear Information System (INIS)
Muniz, Francisco J.
2017-01-01
Load-balancing methods are quite well described in the open literature (hundreds of articles can be found about this subject). In particularly, about the Dynamic Load-balancing mechanism Extended Gradient (EG), several articles of the author are available. Even though, there are some overlap, each one of them is focused on a particular aspect of the mechanism, in a complementary way. In this article, a graphic representation of the Extended Gradient mechanism is done: this representation way had not yet been explored. However, for an in-depth knowledge of the Extended Gradient mechanism, at least, some other articles should to be read. In the CDTN, Clusters are used, mainly, in deterministic methods (CFD) and non-deterministic methods (Monte Carlo). (author)
PeerFlow: Secure Load Balancing in Tor
Directory of Open Access Journals (Sweden)
Johnson Aaron
2017-04-01
Full Text Available We present PeerFlow, a system to securely load balance client traffic in Tor. Security in Tor requires that no adversary handle too much traffic. However, Tor relays are run by volunteers who cannot be trusted to report the relay bandwidths, which Tor clients use for load balancing. We show that existing methods to determine the bandwidths of Tor relays allow an adversary with little bandwidth to attack large amounts of client traffic. These methods include Tor’s current bandwidth-scanning system, TorFlow, and the peer-measurement system EigenSpeed. We present an improved design called PeerFlow that uses a peer-measurement process both to limit an adversary’s ability to increase his measured bandwidth and to improve accuracy. We show our system to be secure, fast, and efficient. We implement PeerFlow in Tor and demonstrate its speed and accuracy in large-scale network simulations.
Analisis Kinerja Penerapan Container untuk Load Balancing Web Server
Directory of Open Access Journals (Sweden)
Muhammad Agung Nugroho
2016-12-01
Full Text Available Container merupakan teknologi virtualisasi terbaru. Container memudahkan system administrator dalam mengelola aplikasi pada server. Docker container dapat digunakan untuk membangun, mempersiapkan, dan menjalankan aplikasi. Dapat membuat aplikasi dari bahasa pemrograman yang berbeda pada lapisan apapun. Aplikasi dapat di bungkus dalam container, dan aplikasi dapat berjalan pada lingkungan apapun dimana saja. Dalam perkembangannya container ini dapat digunakan untuk load balancing, dengan memanfaatkan HA Proxy. Load Balancing dapat digunakan untuk menyelesaikan permasalahan beban kinerja web server yang terlalu berat (overload terhadap permintaan. Load Balancing merupakan salah satu metode untuk meningkatkan skalabilitas web server sekaligus mengurangi beban kerja web server. Ujicoba dilakukan dengan memberikan beban request pada single container dan multi container, dan membandingkan kinerjanya. Analisis kinerja dapat dilakukan dengan menggunakan parameter performance pada processor, memori dan proses layanan. Penerapan ujicoba dilakukan pada raspberry pi. Hasil yang diperoleh multi container dapat digunakan untuk mengembangkan metode load balancing, hasil ujicoba menunjukkan performance raspberry pi dapat optimum karena pembagian beban processor.
Load power device and system for real-time execution of hierarchical load identification algorithms
Yang, Yi; Madane, Mayura Arun; Zambare, Prachi Suresh
2017-11-14
A load power device includes a power input; at least one power output for at least one load; and a plurality of sensors structured to sense voltage and current at the at least one power output. A processor is structured to provide real-time execution of: (a) a plurality of load identification algorithms, and (b) event detection and operating mode detection for the at least one load.
Load Balancing As A Service In Openstack-Liberty
Directory of Open Access Journals (Sweden)
Rashmi T V
2015-08-01
Full Text Available Cloud computing is a technology which provides computing resource on demand over the internet as a service. To meet this many opensource cloud operating system are provided for the tenants in order to get useful services from the cloud. There are many opensource cloud OS like AWS Open Shift HP OpenStack etc. Out of all these OpenStack comes with free of cost and it has got a huge community. It can be installed and deploy in private institution or company with free of cost. This paper provides a model and techniques for the dynamic load balancing in OpenStack for managing the trafficloads among the Virtual Machines. The main purpose is to increase the utilization of computing resources and minimize the traffic. Load Balancing as a Service is one of the main service in OpenStack Networking. OpenStack is an opensource platform which provides Infrastructure as a Service. It allows userstenants tocreate their own private clouds and to deploy Virtual Machines which manages different workloads. In this paper we provide an architecture of openstack LBaaS for dynamic load balancing in open stack cloud deployment.
An improved harmony search algorithm for power economic load dispatch
Energy Technology Data Exchange (ETDEWEB)
Santos Coelho, Leandro dos [Pontifical Catholic University of Parana, PUCPR, Industrial and Systems Engineering Graduate Program, PPGEPS, Imaculada Conceicao, 1155, 80215-901 Curitiba, PR (Brazil)], E-mail: leandro.coelho@pucpr.br; Mariani, Viviana Cocco [Pontifical Catholic University of Parana, PUCPR, Department of Mechanical Engineering, PPGEM, Imaculada Conceicao, 1155, 80215-901 Curitiba, PR (Brazil)], E-mail: viviana.mariani@pucpr.br
2009-10-15
A meta-heuristic algorithm called harmony search (HS), mimicking the improvisation process of music players, has been recently developed. The HS algorithm has been successful in several optimization problems. The HS algorithm does not require derivative information and uses stochastic random search instead of a gradient search. In addition, the HS algorithm is simple in concept, few in parameters, and easy in implementation. This paper presents an improved harmony search (IHS) algorithm based on exponential distribution for solving economic dispatch problems. A 13-unit test system with incremental fuel cost function taking into account the valve-point loading effects is used to illustrate the effectiveness of the proposed IHS method. Numerical results show that the IHS method has good convergence property. Furthermore, the generation costs of the IHS method are lower than those of the classical HS and other optimization algorithms reported in recent literature.
An improved harmony search algorithm for power economic load dispatch
Energy Technology Data Exchange (ETDEWEB)
Coelho, Leandro dos Santos [Pontifical Catholic Univ. of Parana, PUCPR, Industrial and Systems Engineering Graduate Program, PPGEPS, Imaculada Conceicao, 1155, 80215-901 Curitiba, PR (Brazil); Mariani, Viviana Cocco [Pontifical Catholic Univ. of Parana, PUCPR, Dept. of Mechanical Engineering, PPGEM, Imaculada Conceicao, 1155, 80215-901 Curitiba, PR (Brazil)
2009-10-15
A meta-heuristic algorithm called harmony search (HS), mimicking the improvisation process of music players, has been recently developed. The HS algorithm has been successful in several optimization problems. The HS algorithm does not require derivative information and uses stochastic random search instead of a gradient search. In addition, the HS algorithm is simple in concept, few in parameters, and easy in implementation. This paper presents an improved harmony search (IHS) algorithm based on exponential distribution for solving economic dispatch problems. A 13-unit test system with incremental fuel cost function taking into account the valve-point loading effects is used to illustrate the effectiveness of the proposed IHS method. Numerical results show that the IHS method has good convergence property. Furthermore, the generation costs of the IHS method are lower than those of the classical HS and other optimization algorithms reported in recent literature. (author)
Electricity Load Forecasting Using Support Vector Regression with Memetic Algorithms
Directory of Open Access Journals (Sweden)
Zhongyi Hu
2013-01-01
Full Text Available Electricity load forecasting is an important issue that is widely explored and examined in power systems operation literature and commercial transactions in electricity markets literature as well. Among the existing forecasting models, support vector regression (SVR has gained much attention. Considering the performance of SVR highly depends on its parameters; this study proposed a firefly algorithm (FA based memetic algorithm (FA-MA to appropriately determine the parameters of SVR forecasting model. In the proposed FA-MA algorithm, the FA algorithm is applied to explore the solution space, and the pattern search is used to conduct individual learning and thus enhance the exploitation of FA. Experimental results confirm that the proposed FA-MA based SVR model can not only yield more accurate forecasting results than the other four evolutionary algorithms based SVR models and three well-known forecasting models but also outperform the hybrid algorithms in the related existing literature.
An improved harmony search algorithm for power economic load dispatch
International Nuclear Information System (INIS)
Santos Coelho, Leandro dos; Mariani, Viviana Cocco
2009-01-01
A meta-heuristic algorithm called harmony search (HS), mimicking the improvisation process of music players, has been recently developed. The HS algorithm has been successful in several optimization problems. The HS algorithm does not require derivative information and uses stochastic random search instead of a gradient search. In addition, the HS algorithm is simple in concept, few in parameters, and easy in implementation. This paper presents an improved harmony search (IHS) algorithm based on exponential distribution for solving economic dispatch problems. A 13-unit test system with incremental fuel cost function taking into account the valve-point loading effects is used to illustrate the effectiveness of the proposed IHS method. Numerical results show that the IHS method has good convergence property. Furthermore, the generation costs of the IHS method are lower than those of the classical HS and other optimization algorithms reported in recent literature.
A parallel 3D particle-in-cell code with dynamic load balancing
International Nuclear Information System (INIS)
Wolfheimer, Felix; Gjonaj, Erion; Weiland, Thomas
2006-01-01
A parallel 3D electrostatic Particle-In-Cell (PIC) code including an algorithm for modelling Space Charge Limited (SCL) emission [E. Gjonaj, T. Weiland, 3D-modeling of space-charge-limited electron emission. A charge conserving algorithm, Proceedings of the 11th Biennial IEEE Conference on Electromagnetic Field Computation, 2004] is presented. A domain decomposition technique based on orthogonal recursive bisection is used to parallelize the computation on a distributed memory environment of clustered workstations. For problems with a highly nonuniform and time dependent distribution of particles, e.g., bunch dynamics, a dynamic load balancing between the processes is needed to preserve the parallel performance. The algorithm for the detection of a load imbalance and the redistribution of the tasks among the processes is based on a weight function criterion, where the weight of a cell measures the computational load associated with it. The algorithm is studied with two examples. In the first example, multiple electron bunches as occurring in the S-DALINAC [A. Richter, Operational experience at the S-DALINAC, Proceedings of the Fifth European Particle Accelerator Conference, 1996] accelerator are simulated in the absence of space charge fields. In the second example, the SCL emission and electron trajectories in an electron gun are simulated
A parallel 3D particle-in-cell code with dynamic load balancing
Energy Technology Data Exchange (ETDEWEB)
Wolfheimer, Felix [Technische Universitaet Darmstadt, Institut fuer Theorie Elektromagnetischer Felder, Schlossgartenstr.8, 64283 Darmstadt (Germany)]. E-mail: wolfheimer@temf.de; Gjonaj, Erion [Technische Universitaet Darmstadt, Institut fuer Theorie Elektromagnetischer Felder, Schlossgartenstr.8, 64283 Darmstadt (Germany); Weiland, Thomas [Technische Universitaet Darmstadt, Institut fuer Theorie Elektromagnetischer Felder, Schlossgartenstr.8, 64283 Darmstadt (Germany)
2006-03-01
A parallel 3D electrostatic Particle-In-Cell (PIC) code including an algorithm for modelling Space Charge Limited (SCL) emission [E. Gjonaj, T. Weiland, 3D-modeling of space-charge-limited electron emission. A charge conserving algorithm, Proceedings of the 11th Biennial IEEE Conference on Electromagnetic Field Computation, 2004] is presented. A domain decomposition technique based on orthogonal recursive bisection is used to parallelize the computation on a distributed memory environment of clustered workstations. For problems with a highly nonuniform and time dependent distribution of particles, e.g., bunch dynamics, a dynamic load balancing between the processes is needed to preserve the parallel performance. The algorithm for the detection of a load imbalance and the redistribution of the tasks among the processes is based on a weight function criterion, where the weight of a cell measures the computational load associated with it. The algorithm is studied with two examples. In the first example, multiple electron bunches as occurring in the S-DALINAC [A. Richter, Operational experience at the S-DALINAC, Proceedings of the Fifth European Particle Accelerator Conference, 1996] accelerator are simulated in the absence of space charge fields. In the second example, the SCL emission and electron trajectories in an electron gun are simulated.
Richardson, J.; Labbe, M.; Belala, Y.; Leduc, Vincent
1994-01-01
The requirement for improving aircraft utilization and responsiveness in airlift operations has been recognized for quite some time by the Canadian Forces. To date, the utilization of scarce airlift resources has been planned mainly through the employment of manpower-intensive manual methods in combination with the expertise of highly qualified personnel. In this paper, we address the problem of facilitating the load planning process for military aircraft cargo planes through the development of a computer-based system. We introduce TALBAS (Transport Aircraft Loading and BAlancing System), a knowledge-based system designed to assist personnel involved in preparing valid load plans for the C130 Hercules aircraft. The main features of this system which are accessible through a convivial graphical user interface, consists of the automatic generation of valid cargo arrangements given a list of items to be transported, the user-definition of load plans and the automatic validation of such load plans.
Joint Load Balancing and Power Allocation for Hybrid VLC/RF Networks
Obeed, Mohanad; Salhab, Anas M.; Zummo, Salam A.; Alouini, Mohamed-Slim
2018-01-01
In this paper, we propose and study a new joint load balancing (LB) and power allocation (PA) scheme for a hybrid visible light communication (VLC) and radio frequency (RF) system consisting of one RF\\access point (AP) and multiple VLC\\APs. An iterative algorithm is proposed to distribute the users on the APs and distribute the powers of these APs on their users. In PA subproblem, an optimization problem is formulated to allocate the power of each AP to the connected users for the total achievable data rates maximization. It is proved that the PA optimization problem is concave but not easy to tackle. Therefore, we provide a new algorithm to obtain the optimal dual variables after formulating them in terms of each other. Then, the users that are connected to the overloaded APs and receive less data rates start seeking for other APs that offer higher data rates. Users with lower data rates continue re-connecting from AP to other to balance the load only if this travel increases the summation of the achievable data rates and enhances the system fairness. The numerical results demonstrate that the proposed algorithms improve the system capacity and system fairness with fast convergence.
Directory of Open Access Journals (Sweden)
M. Lawanyashri
Full Text Available Cloud computing has gained precise attention from the research community and management of IT, due to its scalable and dynamic capabilities. It is evolving as a vibrant technology to modernize and restructure healthcare organization to provide best services to the consumers. The rising demand for healthcare services and applications in cloud computing leads to the imbalance in resource usage and drastically increases the power consumption resulting in high operating cost. To achieve fast execution time and optimum utilization of the virtual machines, we propose a multi-objective hybrid fruitfly optimization technique based on simulated annealing to improve the convergence rate and optimization accuracy. The proposed approach is used to achieve the optimal resource utilization and reduces the energy consumption and cost in cloud computing environment. The result attained in our proposed technique provides an improved solution. The experimental results show that the proposed algorithm efficiently outperforms compared to the existing load balancing algorithms. Keywords: Cloud computing, Electronic Health Records (EHR, Load balancing, Fruitfly Optimization Algorithm (FOA, Simulated Annealing (SA, Energy consumption
Joint Load Balancing and Power Allocation for Hybrid VLC/RF Networks
Obeed, Mohanad
2018-01-15
In this paper, we propose and study a new joint load balancing (LB) and power allocation (PA) scheme for a hybrid visible light communication (VLC) and radio frequency (RF) system consisting of one RF\\\\access point (AP) and multiple VLC\\\\APs. An iterative algorithm is proposed to distribute the users on the APs and distribute the powers of these APs on their users. In PA subproblem, an optimization problem is formulated to allocate the power of each AP to the connected users for the total achievable data rates maximization. It is proved that the PA optimization problem is concave but not easy to tackle. Therefore, we provide a new algorithm to obtain the optimal dual variables after formulating them in terms of each other. Then, the users that are connected to the overloaded APs and receive less data rates start seeking for other APs that offer higher data rates. Users with lower data rates continue re-connecting from AP to other to balance the load only if this travel increases the summation of the achievable data rates and enhances the system fairness. The numerical results demonstrate that the proposed algorithms improve the system capacity and system fairness with fast convergence.
An Efficient SDN Load Balancing Scheme Based on Variance Analysis for Massive Mobile Users
Directory of Open Access Journals (Sweden)
Hong Zhong
2015-01-01
Full Text Available In a traditional network, server load balancing is used to satisfy the demand for high data volumes. The technique requires large capital investment while offering poor scalability and flexibility, which difficultly supports highly dynamic workload demands from massive mobile users. To solve these problems, this paper analyses the principle of software-defined networking (SDN and presents a new probabilistic method of load balancing based on variance analysis. The method can be used to dynamically manage traffic flows for supporting massive mobile users in SDN networks. The paper proposes a solution using the OpenFlow virtual switching technology instead of the traditional hardware switching technology. A SDN controller monitors data traffic of each port by means of variance analysis and provides a probability-based selection algorithm to redirect traffic dynamically with the OpenFlow technology. Compared with the existing load balancing methods which were designed to support traditional networks, this solution has lower cost, higher reliability, and greater scalability which satisfy the needs of mobile users.
Load Balancing Scheme on the Basis of Huffman Coding for P2P Information Retrieval
Kurasawa, Hisashi; Takasu, Atsuhiro; Adachi, Jun
Although a distributed index on a distributed hash table (DHT) enables efficient document query processing in Peer-to-Peer information retrieval (P2P IR), the index costs a lot to construct and it tends to be an unfair management because of the unbalanced term frequency distribution. We devised a new distributed index, named Huffman-DHT, for P2P IR. The new index uses an algorithm similar to Huffman coding with a modification to the DHT structure based on the term distribution. In a Huffman-DHT, a frequent term is assigned to a short ID and allocated a large space in the node ID space in DHT. Throuth ID management, the Huffman-DHT balances the index registration accesses among peers and reduces load concentrations. Huffman-DHT is the first approach to adapt concepts of coding theory and term frequency distribution to load balancing. We evaluated this approach in experiments using a document collection and assessed its load balancing capabilities in P2P IR. The experimental results indicated that it is most effective when the P2P system consists of about 30, 000 nodes and contains many documents. Moreover, we proved that we can construct a Huffman-DHT easily by estimating the probability distribution of the term occurrence from a small number of sample documents.
A network flow model for load balancing in circuit-switched multicomputers
Bokhari, Shahid H.
1990-01-01
In multicomputers that utilize circuit switching or wormhole routing, communication overhead depends largely on link contention - the variation due to distance between nodes is negligible. This has a major impact on the load balancing problem. In this case, there are some nodes with excess load (sources) and others with deficit load (sinks) and it is required to find a matching of sources to sinks that avoids contention. The problem is made complex by the hardwired routing on currently available machines: the user can control only which nodes communicate but not how the messages are routed. Network flow models of message flow in the mesh and the hypercube were developed to solve this problem. The crucial property of these models is the correspondence between minimum cost flows and correctly routed messages. To solve a given load balancing problem, a minimum cost flow algorithm is applied to the network. This permits one to determine efficiently a maximum contention free matching of sources to sinks which, in turn, tells one how much of the given imbalance can be eliminated without contention.
Multi-agent grid system Agent-GRID with dynamic load balancing of cluster nodes
Satymbekov, M. N.; Pak, I. T.; Naizabayeva, L.; Nurzhanov, Ch. A.
2017-12-01
In this study the work presents the system designed for automated load balancing of the contributor by analysing the load of compute nodes and the subsequent migration of virtual machines from loaded nodes to less loaded ones. This system increases the performance of cluster nodes and helps in the timely processing of data. A grid system balances the work of cluster nodes the relevance of the system is the award of multi-agent balancing for the solution of such problems.
Differential harmony search algorithm to optimize PWRs loading pattern
Energy Technology Data Exchange (ETDEWEB)
Poursalehi, N., E-mail: npsalehi@yahoo.com [Engineering Department, Shahid Beheshti University, G.C, P.O.Box: 1983963113, Tehran (Iran, Islamic Republic of); Zolfaghari, A.; Minuchehr, A. [Engineering Department, Shahid Beheshti University, G.C, P.O.Box: 1983963113, Tehran (Iran, Islamic Republic of)
2013-04-15
Highlights: ► Exploit of DHS algorithm in LP optimization reveals its flexibility, robustness and reliability. ► Upshot of our experiments with DHS shows that the search approach to optimal LP is quickly. ► On the average, the final band width of DHS fitness values is narrow relative to HS and GHS. -- Abstract: The objective of this work is to develop a core loading optimization technique using differential harmony search algorithm in the context of obtaining an optimal configuration of fuel assemblies in pressurized water reactors. To implement and evaluate the proposed technique, differential harmony search nodal expansion package for 2-D geometry, DHSNEP-2D, is developed. The package includes two modules; in the first modules differential harmony search (DHS) is implemented and nodal expansion code which solves two dimensional-multi group neutron diffusion equations using fourth degree flux expansion with one node per a fuel assembly is in the second module. For evaluation of DHS algorithm, classical harmony search (HS) and global-best harmony search (GHS) algorithms are also included in DHSNEP-2D in order to compare the outcome of techniques together. For this purpose, two PWR test cases have been investigated to demonstrate the DHS algorithm capability in obtaining near optimal loading pattern. Results show that the convergence rate of DHS and execution times are quite promising and also is reliable for the fuel management operation. Moreover, numerical results show the good performance of DHS relative to other competitive algorithms such as genetic algorithm (GA), classical harmony search (HS) and global-best harmony search (GHS) algorithms.
Differential harmony search algorithm to optimize PWRs loading pattern
International Nuclear Information System (INIS)
Poursalehi, N.; Zolfaghari, A.; Minuchehr, A.
2013-01-01
Highlights: ► Exploit of DHS algorithm in LP optimization reveals its flexibility, robustness and reliability. ► Upshot of our experiments with DHS shows that the search approach to optimal LP is quickly. ► On the average, the final band width of DHS fitness values is narrow relative to HS and GHS. -- Abstract: The objective of this work is to develop a core loading optimization technique using differential harmony search algorithm in the context of obtaining an optimal configuration of fuel assemblies in pressurized water reactors. To implement and evaluate the proposed technique, differential harmony search nodal expansion package for 2-D geometry, DHSNEP-2D, is developed. The package includes two modules; in the first modules differential harmony search (DHS) is implemented and nodal expansion code which solves two dimensional-multi group neutron diffusion equations using fourth degree flux expansion with one node per a fuel assembly is in the second module. For evaluation of DHS algorithm, classical harmony search (HS) and global-best harmony search (GHS) algorithms are also included in DHSNEP-2D in order to compare the outcome of techniques together. For this purpose, two PWR test cases have been investigated to demonstrate the DHS algorithm capability in obtaining near optimal loading pattern. Results show that the convergence rate of DHS and execution times are quite promising and also is reliable for the fuel management operation. Moreover, numerical results show the good performance of DHS relative to other competitive algorithms such as genetic algorithm (GA), classical harmony search (HS) and global-best harmony search (GHS) algorithms
Dynamic load balancing in a concurrent plasma PIC code on the JPL/Caltech Mark III hypercube
International Nuclear Information System (INIS)
Liewer, P.C.; Leaver, E.W.; Decyk, V.K.; Dawson, J.M.
1990-01-01
Dynamic load balancing has been implemented in a concurrent one-dimensional electromagnetic plasma particle-in-cell (PIC) simulation code using a method which adds very little overhead to the parallel code. In PIC codes, the orbits of many interacting plasma electrons and ions are followed as an initial value problem as the particles move in electromagnetic fields calculated self-consistently from the particle motions. The code was implemented using the GCPIC algorithm in which the particles are divided among processors by partitioning the spatial domain of the simulation. The problem is load-balanced by partitioning the spatial domain so that each partition has approximately the same number of particles. During the simulation, the partitions are dynamically recreated as the spatial distribution of the particles changes in order to maintain processor load balance
A Baseline Load Schedule for the Manual Calibration of a Force Balance
Ulbrich, N.; Gisler, R.
2013-01-01
A baseline load schedule for the manual calibration of a force balance is defined that takes current capabilities at the NASA Ames Balance Calibration Laboratory into account. The chosen load schedule consists of 18 load series with a total of 194 data points. It was designed to satisfy six requirements: (i) positive and negative loadings should be applied for each load component; (ii) at least three loadings should be applied between 0 % and 100 % load capacity; (iii) normal and side force loadings should be applied at the forward gage location, aft gage location, and the balance moment center; (iv) the balance should be used in "up" and "down" orientation to get positive and negative axial force loadings; (v) the constant normal and side force approaches should be used to get the rolling moment loadings; (vi) rolling moment loadings should be obtained for 0, 90, 180, and 270 degrees balance orientation. In addition, three different approaches are discussed in the paper that may be used to independently estimate the natural zeros, i.e., the gage outputs of the absolute load datum of the balance. These three approaches provide gage output differences that can be used to estimate the weight of both the metric and non-metric part of the balance. Data from the calibration of a six-component force balance will be used in the final manuscript of the paper to illustrate characteristics of the proposed baseline load schedule.
Silva, Bhagya Nathali; Khan, Murad; Han, Kijun
2018-01-01
The emergence of smart devices and smart appliances has highly favored the realization of the smart home concept. Modern smart home systems handle a wide range of user requirements. Energy management and energy conservation are in the spotlight when deploying sophisticated smart homes. However, the performance of energy management systems is highly influenced by user behaviors and adopted energy management approaches. Appliance scheduling is widely accepted as an effective mechanism to manage domestic energy consumption. Hence, we propose a smart home energy management system that reduces unnecessary energy consumption by integrating an automated switching off system with load balancing and appliance scheduling algorithm. The load balancing scheme acts according to defined constraints such that the cumulative energy consumption of the household is managed below the defined maximum threshold. The scheduling of appliances adheres to the least slack time (LST) algorithm while considering user comfort during scheduling. The performance of the proposed scheme has been evaluated against an existing energy management scheme through computer simulation. The simulation results have revealed a significant improvement gained through the proposed LST-based energy management scheme in terms of cost of energy, along with reduced domestic energy consumption facilitated by an automated switching off mechanism. PMID:29495346
Directory of Open Access Journals (Sweden)
Bhagya Nathali Silva
2018-02-01
Full Text Available The emergence of smart devices and smart appliances has highly favored the realization of the smart home concept. Modern smart home systems handle a wide range of user requirements. Energy management and energy conservation are in the spotlight when deploying sophisticated smart homes. However, the performance of energy management systems is highly influenced by user behaviors and adopted energy management approaches. Appliance scheduling is widely accepted as an effective mechanism to manage domestic energy consumption. Hence, we propose a smart home energy management system that reduces unnecessary energy consumption by integrating an automated switching off system with load balancing and appliance scheduling algorithm. The load balancing scheme acts according to defined constraints such that the cumulative energy consumption of the household is managed below the defined maximum threshold. The scheduling of appliances adheres to the least slack time (LST algorithm while considering user comfort during scheduling. The performance of the proposed scheme has been evaluated against an existing energy management scheme through computer simulation. The simulation results have revealed a significant improvement gained through the proposed LST-based energy management scheme in terms of cost of energy, along with reduced domestic energy consumption facilitated by an automated switching off mechanism.
Silva, Bhagya Nathali; Khan, Murad; Han, Kijun
2018-02-25
The emergence of smart devices and smart appliances has highly favored the realization of the smart home concept. Modern smart home systems handle a wide range of user requirements. Energy management and energy conservation are in the spotlight when deploying sophisticated smart homes. However, the performance of energy management systems is highly influenced by user behaviors and adopted energy management approaches. Appliance scheduling is widely accepted as an effective mechanism to manage domestic energy consumption. Hence, we propose a smart home energy management system that reduces unnecessary energy consumption by integrating an automated switching off system with load balancing and appliance scheduling algorithm. The load balancing scheme acts according to defined constraints such that the cumulative energy consumption of the household is managed below the defined maximum threshold. The scheduling of appliances adheres to the least slack time (LST) algorithm while considering user comfort during scheduling. The performance of the proposed scheme has been evaluated against an existing energy management scheme through computer simulation. The simulation results have revealed a significant improvement gained through the proposed LST-based energy management scheme in terms of cost of energy, along with reduced domestic energy consumption facilitated by an automated switching off mechanism.
MCNP load balancing and fault tolerance with PVM
International Nuclear Information System (INIS)
McKinney, G.W.
1995-01-01
Version 4A of the Monte Carlo neutron, photon, and electron transport code MCNP, developed by LANL (Los Alamos National Laboratory), supports distributed-memory multiprocessing through the software package PVM (Parallel Virtual Machine, version 3.1.4). Using PVM for interprocessor communication, MCNP can simultaneously execute a single problem on a cluster of UNIX-based workstations. This capability provided system efficiencies that exceeded 80% on dedicated workstation clusters, however, on heterogeneous or multiuser systems, the performance was limited by the slowest processor (i.e., equal work was assigned to each processor). The next public release of MCNP will provide multiprocessing enhancements that include load balancing and fault tolerance which are shown to dramatically increase multiuser system efficiency and reliability
Road traffic management based on self-load-balancing approach
Directory of Open Access Journals (Sweden)
Adnane Ahmed
2016-01-01
Full Text Available Traffic congestion is one of the most challenging problems for nowadays cities. Several contributions mainly based on V2V (Vehicle-to-Vehicle communication have been published, but most of them have never been applied due to their communication related problems and costs. In this article, a novel cost-effective approach is introduced inspired by social life of insects where direct (V2V communication does not exist anymore. Vehicles are equipped with devices that perform simple tasks, but their interactions with the environment through RSUs (Road Side Units allow the creation of an intelligence which notifies drivers about congested road segments to avoid them. We call this emerging behavior self-load balancing. Description of the fundamentals of this approach and its performance are detailed in this work.
Joint Optimization of Power Allocation and Load Balancing for Hybrid VLC/RF Networks
Obeed, Mohanad
2018-04-18
In this paper, we propose and study a new joint load balancing (LB) and power allocation (PA) scheme for a hybrid visible light communication (VLC) and radio frequency (RF) system consisting of one RF access point (AP) and multiple VLC APs. An iterative algorithm is proposed to distribute users on APs and distribute the powers of the APs on their users. In the PA subproblem, an optimization problem is formulated to allocate the power of each AP to the connected users for total achievable data rate maximization. In this subproblem, we propose a new efficient algorithm that finds optimal dual variables after formulating them in terms of each other. This new algorithm provides faster convergence and better performance than the traditional subgradient method. In addition, it does not depend on the step size or the initial values of the variables, which we look for, as the subgradient does. Then, we start with the user of the minimum data rate seeking another AP that offers a higher data rate for that user. Users with lower data rates continue reconnecting from one AP to another to balance the load only if this travel increases the summation of the achievable data rates and enhances the system fairness. Two approaches are proposed to have the joint PA and LB performed: a main approach that considers the exact interference information for all users, and a suboptimal approach that aims to decrease the complexity of the first approach by considering only the approximate interference information of users. The numerical results demonstrate that the proposed algorithms improve the system capacity and system fairness with fast convergence.
Joint Optimization of Power Allocation and Load Balancing for Hybrid VLC/RF Networks
Obeed, Mohanad; Salhab, Anas; Zummo, Salam A.; Alouini, Mohamed-Slim
2018-01-01
In this paper, we propose and study a new joint load balancing (LB) and power allocation (PA) scheme for a hybrid visible light communication (VLC) and radio frequency (RF) system consisting of one RF access point (AP) and multiple VLC APs. An iterative algorithm is proposed to distribute users on APs and distribute the powers of the APs on their users. In the PA subproblem, an optimization problem is formulated to allocate the power of each AP to the connected users for total achievable data rate maximization. In this subproblem, we propose a new efficient algorithm that finds optimal dual variables after formulating them in terms of each other. This new algorithm provides faster convergence and better performance than the traditional subgradient method. In addition, it does not depend on the step size or the initial values of the variables, which we look for, as the subgradient does. Then, we start with the user of the minimum data rate seeking another AP that offers a higher data rate for that user. Users with lower data rates continue reconnecting from one AP to another to balance the load only if this travel increases the summation of the achievable data rates and enhances the system fairness. Two approaches are proposed to have the joint PA and LB performed: a main approach that considers the exact interference information for all users, and a suboptimal approach that aims to decrease the complexity of the first approach by considering only the approximate interference information of users. The numerical results demonstrate that the proposed algorithms improve the system capacity and system fairness with fast convergence.
Mizan: A system for dynamic load balancing in large-scale graph processing
Khayyat, Zuhair
2013-01-01
Pregel [23] was recently introduced as a scalable graph mining system that can provide significant performance improvements over traditional MapReduce implementations. Existing implementations focus primarily on graph partitioning as a preprocessing step to balance computation across compute nodes. In this paper, we examine the runtime characteristics of a Pregel system. We show that graph partitioning alone is insufficient for minimizing end-to-end computation. Especially where data is very large or the runtime behavior of the algorithm is unknown, an adaptive approach is needed. To this end, we introduce Mizan, a Pregel system that achieves efficient load balancing to better adapt to changes in computing needs. Unlike known implementations of Pregel, Mizan does not assume any a priori knowledge of the structure of the graph or behavior of the algorithm. Instead, it monitors the runtime characteristics of the system. Mizan then performs efficient fine-grained vertex migration to balance computation and communication. We have fully implemented Mizan; using extensive evaluation we show that - especially for highly-dynamic workloads - Mizan provides up to 84% improvement over techniques leveraging static graph pre-partitioning. © 2013 ACM.
Research reactor loading pattern optimization using estimation of distribution algorithms
Energy Technology Data Exchange (ETDEWEB)
Jiang, S. [Dept. of Earth Science and Engineering, Applied Modeling and Computation Group AMCG, Imperial College, London, SW7 2AZ (United Kingdom); Ziver, K. [Dept. of Earth Science and Engineering, Applied Modeling and Computation Group AMCG, Imperial College, London, SW7 2AZ (United Kingdom); AMCG Group, RM Consultants, Abingdon (United Kingdom); Carter, J. N.; Pain, C. C.; Eaton, M. D.; Goddard, A. J. H. [Dept. of Earth Science and Engineering, Applied Modeling and Computation Group AMCG, Imperial College, London, SW7 2AZ (United Kingdom); Franklin, S. J.; Phillips, H. J. [Imperial College, Reactor Centre, Silwood Park, Buckhurst Road, Ascot, Berkshire, SL5 7TE (United Kingdom)
2006-07-01
A new evolutionary search based approach for solving the nuclear reactor loading pattern optimization problems is presented based on the Estimation of Distribution Algorithms. The optimization technique developed is then applied to the maximization of the effective multiplication factor (K{sub eff}) of the Imperial College CONSORT research reactor (the last remaining civilian research reactor in the United Kingdom). A new elitism-guided searching strategy has been developed and applied to improve the local convergence together with some problem-dependent information based on the 'stand-alone K{sub eff} with fuel coupling calculations. A comparison study between the EDAs and a Genetic Algorithm with Heuristic Tie Breaking Crossover operator has shown that the new algorithm is efficient and robust. (authors)
Research reactor loading pattern optimization using estimation of distribution algorithms
International Nuclear Information System (INIS)
Jiang, S.; Ziver, K.; Carter, J. N.; Pain, C. C.; Eaton, M. D.; Goddard, A. J. H.; Franklin, S. J.; Phillips, H. J.
2006-01-01
A new evolutionary search based approach for solving the nuclear reactor loading pattern optimization problems is presented based on the Estimation of Distribution Algorithms. The optimization technique developed is then applied to the maximization of the effective multiplication factor (K eff ) of the Imperial College CONSORT research reactor (the last remaining civilian research reactor in the United Kingdom). A new elitism-guided searching strategy has been developed and applied to improve the local convergence together with some problem-dependent information based on the 'stand-alone K eff with fuel coupling calculations. A comparison study between the EDAs and a Genetic Algorithm with Heuristic Tie Breaking Crossover operator has shown that the new algorithm is efficient and robust. (authors)
Carmichael, H.
1953-01-01
A torsional-type analytical balance designed to arrive at its equilibrium point more quickly than previous balances is described. In order to prevent external heat sources creating air currents inside the balance casing that would reiard the attainment of equilibrium conditions, a relatively thick casing shaped as an inverted U is placed over the load support arms and the balance beam. This casing is of a metal of good thernnal conductivity characteristics, such as copper or aluminum, in order that heat applied to one portion of the balance is quickly conducted to all other sensitive areas, thus effectively preventing the fornnation of air currents caused by unequal heating of the balance.
PWR loading pattern optimization using Harmony Search algorithm
International Nuclear Information System (INIS)
Poursalehi, N.; Zolfaghari, A.; Minuchehr, A.
2013-01-01
Highlights: ► Numerical results reveal that the HS method is reliable. ► The great advantage of HS is significant gain in computational cost. ► On the average, the final band width of search fitness values is narrow. ► Our experiments show that the search approaches the optimal value fast. - Abstract: In this paper a core reloading technique using Harmony Search, HS, is presented in the context of finding an optimal configuration of fuel assemblies, FA, in pressurized water reactors. To implement and evaluate the proposed technique a Harmony Search along Nodal Expansion Code for 2-D geometry, HSNEC2D, is developed to obtain nearly optimal arrangement of fuel assemblies in PWR cores. This code consists of two sections including Harmony Search algorithm and Nodal Expansion modules using fourth degree flux expansion which solves two dimensional-multi group diffusion equations with one node per fuel assembly. Two optimization test problems are investigated to demonstrate the HS algorithm capability in converging to near optimal loading pattern in the fuel management field and other subjects. Results, convergence rate and reliability of the method are quite promising and show the HS algorithm performs very well and is comparable to other competitive algorithms such as Genetic Algorithm and Particle Swarm Intelligence. Furthermore, implementation of nodal expansion technique along HS causes considerable reduction of computational time to process and analysis optimization in the core fuel management problems
Directory of Open Access Journals (Sweden)
Muthukkumar R.
2017-04-01
Full Text Available Cognitive Radio (CR is a promising and potential technique to enable secondary users (SUs or unlicenced users to exploit the unused spectrum resources effectively possessed by primary users (PUs or licenced users. The proven clustering approach is used to organize nodes in the network into the logical groups to attain energy efficiency, network scalability, and stability for improving the sensing accuracy in CR through cooperative spectrum sensing (CSS. In this paper, a distributed dynamic load balanced clustering (DDLBC algorithm is proposed. In this algorithm, each member in the cluster is to calculate the cooperative gain, residual energy, distance, and sensing cost from the neighboring clusters to perform the optimal decision. Each member in a cluster participates in selecting a cluster head (CH through cooperative gain, and residual energy that minimises network energy consumption and enhances the channel sensing. First, we form the number of clusters using the Markov decision process (MDP model to reduce the energy consumption in a network. In this algorithm, CR users effectively utilize the PUs reporting time slots of unavailability. The simulation results reveal that the clusters convergence, energy efficiency, and accuracy of channel sensing increased considerably by using the proposed algorithm.
Directory of Open Access Journals (Sweden)
Muthukkumar R.
2016-07-01
Full Text Available Cognitive Radio (CR is a promising and potential technique to enable secondary users (SUs or unlicenced users to exploit the unused spectrum resources effectively possessed by primary users (PUs or licenced users. The proven clustering approach is used to organize nodes in the network into the logical groups to attain energy efficiency, network scalability, and stability for improving the sensing accuracy in CR through cooperative spectrum sensing (CSS. In this paper, a distributed dynamic load balanced clustering (DDLBC algorithm is proposed. In this algorithm, each member in the cluster is to calculate the cooperative gain, residual energy, distance, and sensing cost from the neighboring clusters to perform the optimal decision. Each member in a cluster participates in selecting a cluster head (CH through cooperative gain, and residual energy that minimises network energy consumption and enhances the channel sensing. First, we form the number of clusters using the Markov decision process (MDP model to reduce the energy consumption in a network. In this algorithm, CR users effectively utilize the PUs reporting time slots of unavailability. The simulation results reveal that the clusters convergence, energy efficiency, and accuracy of channel sensing increased considerably by using the proposed algorithm.
Rapisarda, P.; Trentelman, H.L.; Minh, H.B.
We illustrate an algorithm that starting from the image representation of a strictly bounded-real system computes a minimal balanced state variable, from which a minimal balanced state realization is readily obtained. The algorithm stems from an iterative procedure to compute a storage function,
Application of the distributed genetic algorithm for loading pattern optimization problems
International Nuclear Information System (INIS)
Hashimoto, Hiroshi; Yamamoto, Akio
2000-01-01
The distributed genetic algorithm (DGA) is applied for loading pattern optimization problems of the pressurized water reactors (PWR). Due to stiff nature of the loading pattern optimizations (e.g. multi-modality and non-linearity), stochastic methods like the simulated annealing or the genetic algorithm (GA) are widely applied for these problems. A basic concept of DGA is based on that of GA. However, DGA equally distributes candidates of solutions (i.e. loading patterns) to several independent 'islands' and evolves them in each island. Migrations of some candidates are performed among islands with a certain period. Since candidates of solutions independently evolve in each island with accepting different genes of migrants from other islands, premature convergence in the traditional GA can be prevented. Because many candidate loading patterns should be evaluated in one generation of GA or DGA, the parallelization in these calculations works efficiently. Parallel efficiency was measured using our optimization code and good load balance was attained even in a heterogeneous cluster environment due to dynamic distribution of the calculation load. The optimization code is based on the client/server architecture with the TCP/IP native socket and a client (optimization module) and calculation server modules communicate the objects of loading patterns each other. Throughout the sensitivity study on optimization parameters of DGA, a suitable set of the parameters for a test problem was identified. Finally, optimization capability of DGA and the traditional GA was compared in the test problem and DGA provided better optimization results than the traditional GA. (author)
Perancangan dan Pengujian Load Balancing dan Failover Menggunakan NginX
Directory of Open Access Journals (Sweden)
Rahmad Dani
2017-06-01
Full Text Available Situs web dengan traffic yang tinggi dapat menyebabkan beban kerja yang berat di sisi server, yang pada gilirannya akan mengakibatkan turunnya kinerja server, bahkan kegagalan sistem secara keseluruhan. Salah satu solusi untuk mengatasi masalah tersebut adalah dengan menerapkan teknik load balancing dan failover. Load balancing merupakan teknologi untuk melakukan pembagian beban kepada beberapa server, memastikan tidak terjadi kelebihan beban pada salah satu server. Sementara itu, failover merupakan kemampuan suatu sistem untuk berpindah ke sistem cadangan jika sistem utama mengalami kegagalan. Dalam penelitian ini load balancing dengan teknik failover akan diimplementasikan pada sistem operasi Ubuntu. Software inti yang digunakan dalam penelitian ini adalah Nginx dan KeepAlived. Nginx akan berfungsi sebagai load balancer, sedangkan KeepAlived untuk mengimplementasikan teknik failover. Beberapa skenario telah disiapkan untuk menguji sistem load balancing yang telah dirancang. Pengujian dilakukan dengan menggunakan perangkat lunak JMeter. Berdasarkan pengujian yang telah dilakukan, sistem yang dirancang berhasil membagikan beban permintaan dan dapat terus bekerja walaupun terjadi kegagalan pada server load balancer ataupun kegagalan pada server backend. Selain itu, dalam beberapa pengujian, penggunaan load balancing terbukti mampu menurunkan waktu respon dan meningkatkan thoughput pada sistem sehingga mampu meningkatkan performa keseluruhan sistem. Mengacu pada hasil penelitian ini, sistem load balancing dan failover menggunakan Nginx dapat dijadikan salah satu solusi pada sistem web server dengan situs web yang memiliki traffic tinggi.
Heyland, Mark; Trepczynski, Adam; Duda, Georg N; Zehn, Manfred; Schaser, Klaus-Dieter; Märdian, Sven
2015-12-01
Selection of boundary constraints may influence amount and distribution of loads. The purpose of this study is to analyze the potential of inertia relief and follower load to maintain the effects of musculoskeletal loads even under large deflections in patient specific finite element models of intact or fractured bone compared to empiric boundary constraints which have been shown to lead to physiological displacements and surface strains. The goal is to elucidate the use of boundary conditions in strain analyses of bones. Finite element models of the intact femur and a model of clinically relevant fracture stabilization by locking plate fixation were analyzed with normal walking loading conditions for different boundary conditions, specifically re-balanced loading, inertia relief and follower load. Peak principal cortex surface strains for different boundary conditions are consistent (maximum deviation 13.7%) except for inertia relief without force balancing (maximum deviation 108.4%). Influence of follower load on displacements increases with higher deflection in fracture model (from 3% to 7% for force balanced model). For load balanced models, follower load had only minor influence, though the effect increases strongly with higher deflection. Conventional constraints of fixed nodes in space should be carefully reconsidered because their type and position are challenging to justify and for their potential to introduce relevant non-physiological reaction forces. Inertia relief provides an alternative method which yields physiological strain results. Copyright © 2015 IPEM. Published by Elsevier Ltd. All rights reserved.
Tseng, Chinyang Henry
2016-05-31
In wireless networks, low-power Zigbee is an excellent network solution for wireless medical monitoring systems. Medical monitoring generally involves transmission of a large amount of data and easily causes bottleneck problems. Although Zigbee's AODV mesh routing provides extensible multi-hop data transmission to extend network coverage, it originally does not, and needs to support some form of load balancing mechanism to avoid bottlenecks. To guarantee a more reliable multi-hop data transmission for life-critical medical applications, we have developed a multipath solution, called Load-Balanced Multipath Routing (LBMR) to replace Zigbee's routing mechanism. LBMR consists of three main parts: Layer Routing Construction (LRC), a Load Estimation Algorithm (LEA), and a Route Maintenance (RM) mechanism. LRC assigns nodes into different layers based on the node's distance to the medical data gateway. Nodes can have multiple next-hops delivering medical data toward the gateway. All neighboring layer-nodes exchange flow information containing current load, which is the used by the LEA to estimate future load of next-hops to the gateway. With LBMR, nodes can choose the neighbors with the least load as the next-hops and thus can achieve load balancing and avoid bottlenecks. Furthermore, RM can detect route failures in real-time and perform route redirection to ensure routing robustness. Since LRC and LEA prevent bottlenecks while RM ensures routing fault tolerance, LBMR provides a highly reliable routing service for medical monitoring. To evaluate these accomplishments, we compare LBMR with Zigbee's AODV and another multipath protocol, AOMDV. The simulation results demonstrate LBMR achieves better load balancing, less unreachable nodes, and better packet delivery ratio than either AODV or AOMDV.
Ebtehaj, Isa; Bonakdari, Hossein
2014-01-01
The existence of sediments in wastewater greatly affects the performance of the sewer and wastewater transmission systems. Increased sedimentation in wastewater collection systems causes problems such as reduced transmission capacity and early combined sewer overflow. The article reviews the performance of the genetic algorithm (GA) and imperialist competitive algorithm (ICA) in minimizing the target function (mean square error of observed and predicted Froude number). To study the impact of bed load transport parameters, using four non-dimensional groups, six different models have been presented. Moreover, the roulette wheel selection method is used to select the parents. The ICA with root mean square error (RMSE) = 0.007, mean absolute percentage error (MAPE) = 3.5% show better results than GA (RMSE = 0.007, MAPE = 5.6%) for the selected model. All six models return better results than the GA. Also, the results of these two algorithms were compared with multi-layer perceptron and existing equations.
Lukitasari, Desy; Oklilas, Ahmad Fali
2010-01-01
Virtual server adalah server yang mempunyai skalabilitas dan ketersedian yang tinggi yang dibangun diatas sebuah cluster dari beberapa real server. Real server dan load balancer akan saling terkoneksi baik dalam jaringan lokal kecepatan tinggi atau yang terpisah secara geografis. Load balancer dapat mengirim permintaan-permintaan ke server yang berbeda dan membuat paralel service dari sebuah cluster pada sebuah alamat IP tunggal dan meminta pengiriman dapat menggunakan teknologi IP load...
Coupling Algorithms for Calculating Sensitivities of Population Balances
International Nuclear Information System (INIS)
Man, P. L. W.; Kraft, M.; Norris, J. R.
2008-01-01
We introduce a new class of stochastic algorithms for calculating parametric derivatives of the solution of the space-homogeneous Smoluchowski's coagulation equation. Currently, it is very difficult to produce low variance estimates of these derivatives in reasonable amounts of computational time through the use of stochastic methods. These new algorithms consider a central difference estimator of the parametric derivative which is calculated by evaluating the coagulation equation at two different parameter values simultaneously, and causing variance reduction by maximising the covariance between these. The two different coupling strategies ('Single' and 'Double') have been compared to the case when there is no coupling ('Independent'). Both coupling algorithms converge and the Double coupling is the most 'efficient' algorithm. For the numerical example chosen we obtain a factor of about 100 in efficiency in the best case (small system evolution time and small parameter perturbation).
Characteristic statistic algorithm (CSA) for in-core loading pattern optimization
International Nuclear Information System (INIS)
Liu Zhihong; Hu Yongming; Shi Gong
2007-01-01
To solve the problem of PWR in-core loading pattern optimization, a more suitable global optimization algorithm, i.e., Characteristic statistic algorithm (CSA), is used. The searching process of this algorithm and how to apply it to this problem are presented. Loading pattern optimization code SCYCLE is developed. Two different problems on real PWR models are calculated and the results are compared with other algorithms. It is shown that SCYCLE has high efficiency and good global performance on this problem. (authors)
A Simple Method for Static Load Balancing of Parallel FDTD Codes
DEFF Research Database (Denmark)
Franek, Ondrej
2016-01-01
A static method for balancing computational loads in parallel implementations of the finite-difference timedomain method is presented. The procedure is fairly straightforward and computationally inexpensive, thus providing an attractive alternative to optimization techniques. The method is descri...
Evaluating algorithms for the Generation of Referring Expressions using a balanced corpus
Gatt, A.; van der Sluis, Ielka; van Deemter, Kees
2007-01-01
Despite being the focus of intensive research, evaluation of algorithms that generate referring expressions is still in its infancy. We describe a corpusbased evaluation methodology, applied to a number of classic algorithms in this area. The methodology focuses on balance and semantic transparency
Design of a Load-Balancing Architecture For Parallel Firewalls
National Research Council Canada - National Science Library
Joyner, William
1999-01-01
Because firewalls can become a potential choke point as network speeds and loads increase, the Navy needs a cost-effective means of increasing data rate through firewalls by placing several machines...
A Balancing Algorithm in Wireless Sensor Network Based on the Assistance of Approaching Nodes
Directory of Open Access Journals (Sweden)
Chengpei Tang
2013-03-01
Full Text Available Sensor node in wireless sensor network is a micro-embedded system with limited memory, energy and communication capabilities. Some nodes will run out of energy and exit the network earlier than other nodes because of the uneven energy consumption. This will lead to partial or complete paralysis of the whole wireless sensor network. A balancing algorithm based on the assistance of approaching nodes is proposed. Via the set theory, notes are divided into neighbor nodes set and approaching nodes set. Approaching nodes will help weaker nodes forward part of massages to balance energy consumption. Simulation result has verified the rationality and feasibility of the balancing algorithm.
Indian Academy of Sciences (India)
to as 'divide-and-conquer'. Although there has been a large effort in realizing efficient algorithms, there are not many universally accepted algorithm design paradigms. In this article, we illustrate algorithm design techniques such as balancing, greedy strategy, dynamic programming strategy, and backtracking or traversal of ...
Insensitive versus efficient dynamic load balancing in networks without blocking
Jonckheere, M.
2006-01-01
So-called Whittle networks have recently been shown to give tight approximations for the performance of non-locally balanced networks with blocking, including practical routing policies such as joining the shortest queue. In the present paper, we turn the attention to networks without blocking. To
Power-aware load balancing of large scale MPI applications
Etinski, Maja; Corbalán González, Julita; Labarta Mancho, Jesús José; Valero Cortés, Mateo; Veidenbaum, Alex
2009-01-01
Power consumption is a very important issue for HPC community, both at the level of one application or at the level of whole workload. Load imbalance of a MPI application can be exploited to save CPU energy without penalizing the execution time. An application is load imbalanced when some nodes are assigned more computation than others. The nodes with less computation can be run at lower frequency since otherwise they have to wait for the nodes with more computation blocked in MPI calls. A te...
Cell Load Balancing Schemes for Uncoordinated Heterogeneous Deployment
DEFF Research Database (Denmark)
Mihaylov, Mihail; Mihovska, Albena D.; Poulkov, Vladimir
2013-01-01
This paper proposes an energy consumption improvement algorithm based on a coefficient determining the reliability of offloading users to a new base station (BS) regarding the additional power needed for them to be compensated during an offload from pico BS (PBS) to macro BS (MBS) in uncoordinate...
International Nuclear Information System (INIS)
Li Qianqian; Jiang Xiaofeng; Zhang Shaohong
2009-01-01
In this study, the age technique, the concepts of relativeness degree and worth function are exploited to improve the performance of genetic algorithm (GA) for PWR loading pattern search. Among them, the age technique endows the algorithm be capable of learning from previous search 'experience' and guides it to do a better search in the vicinity ora local optimal; the introduction of the relativeness degree checks the relativeness of two loading patterns before performing crossover between them, which can significantly reduce the possibility of prematurity of the algorithm; while the application of the worth function makes the algorithm be capable of generating new loading patterns based on the statistics of common features of evaluated good loading patterns. Numerical verification against a loading pattern search benchmark problem ora two-loop reactor demonstrates that the adoption of these techniques is able to significantly enhance the efficiency of the genetic algorithm while improves the quality of the final solution as well. (authors)
Software defined network architecture based research on load balancing strategy
You, Xiaoqian; Wu, Yang
2018-05-01
As a new type network architecture, software defined network has the key idea of separating the control place of the network from the transmission plane, to manage and control the network in a concentrated way; in addition, the network interface is opened on the control layer and the data layer, so as to achieve programmable control of the network. Considering that only the single shortest route is taken into the calculation of traditional network data flow transmission, and congestion and resource consumption caused by excessive load of link circuits are ignored, a link circuit load based flow media business QoS gurantee system is proposed in this article to divide the flow in the network into ordinary data flow and QoS flow. In this way, it supervises the link circuit load with the controller so as to calculate reasonable route rapidly and issue the flow table to the exchanger, to finish rapid data transmission. In addition, it establishes a simulation platform to acquire optimized result through simulation experiment.
Algorithm for Non-proportional Loading in Sequentially Linear Analysis
Yu, C.; Hoogenboom, P.C.J.; Rots, J.G.; Saouma, V.; Bolander, J.; Landis, E.
2016-01-01
Sequentially linear analysis (SLA) is an alternative to the Newton-Raphson method for analyzing the nonlinear behavior of reinforced concrete and masonry structures. In this paper SLA is extended to load cases that are applied one after the other, for example first dead load and then wind load. It
Directory of Open Access Journals (Sweden)
Elham Faraji
2016-03-01
Full Text Available In this research, the capability of a charged system search algorithm (CSS in handling water management optimization problems is investigated. First, two complex mathematical problems are solved by CSS and the results are compared with those obtained from other metaheuristic algorithms. In the last step, the optimization model developed by the CSS algorithm is applied to the waste load allocation in rivers based on the total maximum daily load (TMDL concept. The results are presented in Tables and Figures for easy comparison. The study indicates the superiority of the CSS algorithm in terms of its speed and performance over the other metaheuristic algorithms while its precision in water management optimization problems is verified.
Dynamic game balancing implementation using adaptive algorithm in mobile-based Safari Indonesia game
Yuniarti, Anny; Nata Wardanie, Novita; Kuswardayan, Imam
2018-03-01
In developing a game there is one method that should be applied to maintain the interest of players, namely dynamic game balancing. Dynamic game balancing is a process to match a player’s playing style with the behaviour, attributes, and game environment. This study applies dynamic game balancing using adaptive algorithm in scrolling shooter game type called Safari Indonesia which developed using Unity. The game of this type is portrayed by a fighter aircraft character trying to defend itself from insistent enemy attacks. This classic game is chosen to implement adaptive algorithms because it has quite complex attributes to be developed using dynamic game balancing. Tests conducted by distributing questionnaires to a number of players indicate that this method managed to reduce frustration and increase the pleasure factor in playing.
Replication and load balancing strategy of STAR's relational database management system (RDBM)
Energy Technology Data Exchange (ETDEWEB)
DePhillips, M; Lauret, J; Kopytine, M [Brookhaven National Laboratory, Upton NY 11973 (United States); Kent State University, Kent Ohio 44242 (United States)], E-mail: jlauret@bnl.gov
2008-07-15
Database demand resulting from offline analysis and production of data at the STAR experiment at Brookhaven National Laboratory's Relativistic Heavy-Ion Collider has steadily increased over the last six years of data taking activities. With each year, STAR more than doubles the number of events recorded with an anticipation of reaching a billion event capabilities as early as next year. The challenges faced from producing and analyzing this magnitude of events in parallel have raised issues with regard to the distribution of calibrations and geometry data, via databases, to STAR's growing global collaboration. Rapid distribution, availability, ensured synchronization and load balancing have become paramount considerations. Both conventional technology and novel approaches are used in parallel to realize these goals. This paper discusses how STAR uses load balancing to optimize database usage. It discusses distribution methods via MySQL master slave replication; the synchronization issues that arise from this type of distribution and solutions, mostly homegrown, put forth to overcome these issues. A novel approach toward load balancing between slave nodes that assists in maintaining a high availability rate for a veracious community is discussed in detail. This load balancing addresses both, pools of nodes internal to a given location, as well as balancing the load for remote users between different available locations. Challenges, trade-offs, rationale for decisions and paths forward will be discussed in all cases, presenting a solid production environment with a vision for scalable growth.
Replication and load balancing strategy of STAR's relational database management system (RDBM)
International Nuclear Information System (INIS)
DePhillips, M; Lauret, J; Kopytine, M
2008-01-01
Database demand resulting from offline analysis and production of data at the STAR experiment at Brookhaven National Laboratory's Relativistic Heavy-Ion Collider has steadily increased over the last six years of data taking activities. With each year, STAR more than doubles the number of events recorded with an anticipation of reaching a billion event capabilities as early as next year. The challenges faced from producing and analyzing this magnitude of events in parallel have raised issues with regard to the distribution of calibrations and geometry data, via databases, to STAR's growing global collaboration. Rapid distribution, availability, ensured synchronization and load balancing have become paramount considerations. Both conventional technology and novel approaches are used in parallel to realize these goals. This paper discusses how STAR uses load balancing to optimize database usage. It discusses distribution methods via MySQL master slave replication; the synchronization issues that arise from this type of distribution and solutions, mostly homegrown, put forth to overcome these issues. A novel approach toward load balancing between slave nodes that assists in maintaining a high availability rate for a veracious community is discussed in detail. This load balancing addresses both, pools of nodes internal to a given location, as well as balancing the load for remote users between different available locations. Challenges, trade-offs, rationale for decisions and paths forward will be discussed in all cases, presenting a solid production environment with a vision for scalable growth
Load-balancing techniques for a parallel electromagnetic particle-in-cell code
Energy Technology Data Exchange (ETDEWEB)
PLIMPTON,STEVEN J.; SEIDEL,DAVID B.; PASIK,MICHAEL F.; COATS,REBECCA S.
2000-01-01
QUICKSILVER is a 3-d electromagnetic particle-in-cell simulation code developed and used at Sandia to model relativistic charged particle transport. It models the time-response of electromagnetic fields and low-density-plasmas in a self-consistent manner: the fields push the plasma particles and the plasma current modifies the fields. Through an LDRD project a new parallel version of QUICKSILVER was created to enable large-scale plasma simulations to be run on massively-parallel distributed-memory supercomputers with thousands of processors, such as the Intel Tflops and DEC CPlant machines at Sandia. The new parallel code implements nearly all the features of the original serial QUICKSILVER and can be run on any platform which supports the message-passing interface (MPI) standard as well as on single-processor workstations. This report describes basic strategies useful for parallelizing and load-balancing particle-in-cell codes, outlines the parallel algorithms used in this implementation, and provides a summary of the modifications made to QUICKSILVER. It also highlights a series of benchmark simulations which have been run with the new code that illustrate its performance and parallel efficiency. These calculations have up to a billion grid cells and particles and were run on thousands of processors. This report also serves as a user manual for people wishing to run parallel QUICKSILVER.
Accelerating Multiple Compound Comparison Using LINGO-Based Load-Balancing Strategies on Multi-GPUs.
Lin, Chun-Yuan; Wang, Chung-Hung; Hung, Che-Lun; Lin, Yu-Shiang
2015-01-01
Compound comparison is an important task for the computational chemistry. By the comparison results, potential inhibitors can be found and then used for the pharmacy experiments. The time complexity of a pairwise compound comparison is O(n (2)), where n is the maximal length of compounds. In general, the length of compounds is tens to hundreds, and the computation time is small. However, more and more compounds have been synthesized and extracted now, even more than tens of millions. Therefore, it still will be time-consuming when comparing with a large amount of compounds (seen as a multiple compound comparison problem, abbreviated to MCC). The intrinsic time complexity of MCC problem is O(k (2) n (2)) with k compounds of maximal length n. In this paper, we propose a GPU-based algorithm for MCC problem, called CUDA-MCC, on single- and multi-GPUs. Four LINGO-based load-balancing strategies are considered in CUDA-MCC in order to accelerate the computation speed among thread blocks on GPUs. CUDA-MCC was implemented by C+OpenMP+CUDA. CUDA-MCC achieved 45 times and 391 times faster than its CPU version on a single NVIDIA Tesla K20m GPU card and a dual-NVIDIA Tesla K20m GPU card, respectively, under the experimental results.
Accelerating Multiple Compound Comparison Using LINGO-Based Load-Balancing Strategies on Multi-GPUs
Directory of Open Access Journals (Sweden)
Chun-Yuan Lin
2015-01-01
Full Text Available Compound comparison is an important task for the computational chemistry. By the comparison results, potential inhibitors can be found and then used for the pharmacy experiments. The time complexity of a pairwise compound comparison is O(n2, where n is the maximal length of compounds. In general, the length of compounds is tens to hundreds, and the computation time is small. However, more and more compounds have been synthesized and extracted now, even more than tens of millions. Therefore, it still will be time-consuming when comparing with a large amount of compounds (seen as a multiple compound comparison problem, abbreviated to MCC. The intrinsic time complexity of MCC problem is O(k2n2 with k compounds of maximal length n. In this paper, we propose a GPU-based algorithm for MCC problem, called CUDA-MCC, on single- and multi-GPUs. Four LINGO-based load-balancing strategies are considered in CUDA-MCC in order to accelerate the computation speed among thread blocks on GPUs. CUDA-MCC was implemented by C+OpenMP+CUDA. CUDA-MCC achieved 45 times and 391 times faster than its CPU version on a single NVIDIA Tesla K20m GPU card and a dual-NVIDIA Tesla K20m GPU card, respectively, under the experimental results.
STAR load balancing and tiered-storage infrastructure strategy for ultimate db access
International Nuclear Information System (INIS)
Arkhipkin, D; Lauret, J; Betts, W; Didenko, L; Van Buren, G
2011-01-01
In recent years, the STAR experiment's database demands have grown in accord not only with simple facility growth, but also with a growing physics program. In addition to the accumulated metadata from a decade of operations, refinements to detector calibrations force user analysis to access database information post data production. Users may access any year's data at any point in time, causing a near random access of the metadata queried, contrary to time-organized production cycles. Moreover, complex online event selection algorithms created a query scarcity ( s parsity ) scenario for offline production further impacting performance. Fundamental changes in our hardware approach were hence necessary to improve query speed. Initial strategic improvements were focused on developing fault-tolerant, load-balanced access to a multi-slave infrastructure. Beyond that, we explored, tested and quantified the benefits of introducing a Tiered storage architecture composed of conventional drives, solid-state disks, and memory-resident databases as well as leveraging the use of smaller database services fitting in memory. The results of our extensive testing in real life usage are presented.
Load-balancing techniques for a parallel electromagnetic particle-in-cell code
International Nuclear Information System (INIS)
Plimpton, Steven J.; Seidel, David B.; Pasik, Michael F.; Coats, Rebecca S.
2000-01-01
QUICKSILVER is a 3-d electromagnetic particle-in-cell simulation code developed and used at Sandia to model relativistic charged particle transport. It models the time-response of electromagnetic fields and low-density-plasmas in a self-consistent manner: the fields push the plasma particles and the plasma current modifies the fields. Through an LDRD project a new parallel version of QUICKSILVER was created to enable large-scale plasma simulations to be run on massively-parallel distributed-memory supercomputers with thousands of processors, such as the Intel Tflops and DEC CPlant machines at Sandia. The new parallel code implements nearly all the features of the original serial QUICKSILVER and can be run on any platform which supports the message-passing interface (MPI) standard as well as on single-processor workstations. This report describes basic strategies useful for parallelizing and load-balancing particle-in-cell codes, outlines the parallel algorithms used in this implementation, and provides a summary of the modifications made to QUICKSILVER. It also highlights a series of benchmark simulations which have been run with the new code that illustrate its performance and parallel efficiency. These calculations have up to a billion grid cells and particles and were run on thousands of processors. This report also serves as a user manual for people wishing to run parallel QUICKSILVER
Kalman-fuzzy algorithm in short term load forecasting
International Nuclear Information System (INIS)
Shah Baki, S.R.; Saibon, H.; Lo, K.L.
1996-01-01
A combination of Kalman-Fuzzy-Neural is developed to forecast the next 24 hours load. The input data fed to neural network are presented with training data set composed of historical load data, weather, day of the week, month of the year and holidays. The load data is fed through Kalman-Fuzzy filter before being applied to Neural Network for training. With this techniques Neural Network converges faster and the mean percentage error of predicted load is reduced as compared to the classical ANN technique
Choudhary, Alok Nidhi; Leung, Mun K.; Huang, Thomas S.; Patel, Janak H.
1989-01-01
Computer vision systems employ a sequence of vision algorithms in which the output of an algorithm is the input of the next algorithm in the sequence. Algorithms that constitute such systems exhibit vastly different computational characteristics, and therefore, require different data decomposition techniques and efficient load balancing techniques for parallel implementation. However, since the input data for a task is produced as the output data of the previous task, this information can be exploited to perform knowledge based data decomposition and load balancing. Presented here are algorithms for a motion estimation system. The motion estimation is based on the point correspondence between the involved images which are a sequence of stereo image pairs. Researchers propose algorithms to obtain point correspondences by matching feature points among stereo image pairs at any two consecutive time instants. Furthermore, the proposed algorithms employ non-iterative procedures, which results in saving considerable amounts of computation time. The system consists of the following steps: (1) extraction of features; (2) stereo match of images in one time instant; (3) time match of images from consecutive time instants; (4) stereo match to compute final unambiguous points; and (5) computation of motion parameters.
ANALISIS PENGARUH KONFIGURASI EIGRP EQUAL DAN UNEQUAL COST LOAD BALANCING TERHADAP KINERJA ROUTER
Directory of Open Access Journals (Sweden)
Dian Bagus Saptonugroho
2015-04-01
Full Text Available Routing protocol is tasked with finding the best route to send the packet. Assessed using the metric. If there is more than one route with the same metric value, Routing Information Path (RIP, Open Shortest Path First (OSPF, and Enhanched Interior Gateway Routing Protocol (EIGRP support equal cost load balancing to send packets to the destination. If there is more than one route with a different metric values, EIGRP can do unequal cost load balancing. Research needs to be conducted to determine the effect of the configuration of EIGRP equal and unequal cost load balancing on the performance of the router which can be used as a proof-of-concept testing that is part of the project design document on a network. Research networks using EIGRP as the routing protocol. After the equal and unequal load balancing is enabled by configuring the variance, CEF, per-destination load balancing, per-packet load balancing, or traffic sharing and analyzing its effect on the neighbor table, topology table, routing table, the data transmission, survivability, convergence, throughput, and utilization. This study used an emulator GNS3 as Cisco 2691 Router with Cisco IOS version 12:24 (25 c and advanced enterprise-adventerprisek9 image c2691-mz.124-25c.bin, and OPNET Modeler 14.5 for simulation. The results of the study can be used as a proof-of-concept testing in the design document for later use as contemplated in the manufacture of plan implementation and verification plan.
Burger, Eric M.; Moura, Scott J.
2015-01-01
A fundamental requirement of the electric power system is to maintain a continuous and instantaneous balance between generation and load. The intermittency and uncertainty introduced by renewable energy generation requires the expansion of ancillary power system services to maintain such a balance. In this paper, we examine the potential of thermostatically controlled loads (TCLs), such as refrigerators and electric water heaters, to provide generation following services in real-time energy m...
A Beacon Transmission Power Control Algorithm Based on Wireless Channel Load Forecasting in VANETs.
Mo, Yuanfu; Yu, Dexin; Song, Jun; Zheng, Kun; Guo, Yajuan
2015-01-01
In a vehicular ad hoc network (VANET), the periodic exchange of single-hop status information broadcasts (beacon frames) produces channel loading, which causes channel congestion and induces information conflict problems. To guarantee fairness in beacon transmissions from each node and maximum network connectivity, adjustment of the beacon transmission power is an effective method for reducing and preventing channel congestion. In this study, the primary factors that influence wireless channel loading are selected to construct the KF-BCLF, which is a channel load forecasting algorithm based on a recursive Kalman filter and employs multiple regression equation. By pre-adjusting the transmission power based on the forecasted channel load, the channel load was kept within a predefined range; therefore, channel congestion was prevented. Based on this method, the CLF-BTPC, which is a transmission power control algorithm, is proposed. To verify KF-BCLF algorithm, a traffic survey method that involved the collection of floating car data along a major traffic road in Changchun City is employed. By comparing this forecast with the measured channel loads, the proposed KF-BCLF algorithm was proven to be effective. In addition, the CLF-BTPC algorithm is verified by simulating a section of eight-lane highway and a signal-controlled urban intersection. The results of the two verification process indicate that this distributed CLF-BTPC algorithm can effectively control channel load, prevent channel congestion, and enhance the stability and robustness of wireless beacon transmission in a vehicular network.
A Beacon Transmission Power Control Algorithm Based on Wireless Channel Load Forecasting in VANETs.
Directory of Open Access Journals (Sweden)
Yuanfu Mo
Full Text Available In a vehicular ad hoc network (VANET, the periodic exchange of single-hop status information broadcasts (beacon frames produces channel loading, which causes channel congestion and induces information conflict problems. To guarantee fairness in beacon transmissions from each node and maximum network connectivity, adjustment of the beacon transmission power is an effective method for reducing and preventing channel congestion. In this study, the primary factors that influence wireless channel loading are selected to construct the KF-BCLF, which is a channel load forecasting algorithm based on a recursive Kalman filter and employs multiple regression equation. By pre-adjusting the transmission power based on the forecasted channel load, the channel load was kept within a predefined range; therefore, channel congestion was prevented. Based on this method, the CLF-BTPC, which is a transmission power control algorithm, is proposed. To verify KF-BCLF algorithm, a traffic survey method that involved the collection of floating car data along a major traffic road in Changchun City is employed. By comparing this forecast with the measured channel loads, the proposed KF-BCLF algorithm was proven to be effective. In addition, the CLF-BTPC algorithm is verified by simulating a section of eight-lane highway and a signal-controlled urban intersection. The results of the two verification process indicate that this distributed CLF-BTPC algorithm can effectively control channel load, prevent channel congestion, and enhance the stability and robustness of wireless beacon transmission in a vehicular network.
Vestibular control of standing balance is enhanced with increased cognitive load.
McGeehan, Michael A; Woollacott, Marjorie H; Dalton, Brian H
2017-04-01
When cognitive load is elevated during a motor task, cortical inhibition and reaction time are increased; yet, standing balance control is often unchanged. This disconnect is likely explained by compensatory mechanisms within the balance system such as increased sensitivity of the vestibulomotor pathway. This study aimed to determine the effects of increased cognitive load on the vestibular control of standing balance. Participants stood blindfolded on a force plate with their head facing left and arms relaxed at their sides for two trials while exposed to continuous electrical vestibular stimulation (EVS). Participants either stood quietly or executed a cognitive task (double-digit arithmetic). Surface electromyography (EMG) and anterior-posterior ground-body forces (APF) were measured in order to evaluate vestibular-evoked balance responses in the frequency (coherence and gain) and time (cumulant density) domains. Total distance traveled for anterior-posterior center of pressure (COP) was assessed as a metric of balance variability. Despite similar distances traveled for COP, EVS-medial gastrocnemius (MG) EMG and EVS-APF coherence and EVS-TA EMG and EVS-MG EMG gain were elevated for multiple frequencies when standing with increased cognitive load. For the time domain, medium-latency peak amplitudes increased by 13-54% for EVS-APF and EVS-EMG relationships with the cognitive task compared to without. Peak short-latency amplitudes were unchanged. These results indicate that reliance on vestibular control of balance is enhanced when cognitive load is elevated. This augmented neural strategy may act to supplement divided cortical processing resources within the balance system and compensate for the acute neuromuscular modifications associated with increased cognitive demand.
Multi-Layer Mobility Load Balancing in a Heterogeneous LTE Network
DEFF Research Database (Denmark)
Fotiadis, Panagiotis; Polignano, Michele; Laselva, Daniela
2012-01-01
This paper analyzes the behavior of a distributed Mobility Load Balancing (MLB) scheme in a multi-layer 3GPP (3rd Generation Partnership Project) Long Term Evolution (LTE) deployment with different User Equipment (UE) densities in certain network areas covered with pico cells. Target of the study...
Implementasi Cluster Server pada Raspberry Pi dengan Menggunakan Metode Load Balancing
Directory of Open Access Journals (Sweden)
Ridho Habi Putra
2016-06-01
Full Text Available Server merupakan bagian penting dalam sebuah layanan didalam jaringan komputer. Peran server dapat menentukan kualitas baik buruknya dari layanan tersebut. Kegagalan dari sebuah server bisa disebabkan oleh beberapa faktor diantaranya kerusakan perangkat keras, sistem jaringan serta aliran listrik. Salah satu solusi untuk mengatasi kegagalan server dalam suatu jaringan komputer adalah dengan melakukan clustering server. Tujuan dari penelitian ini adalah untuk mengukur kemampuan Raspberry Pi (Raspi digunakan sebagai web server. Raspberry Pi yang digunakan menggunakan Raspberry Pi 2 Model B dengan menggunakan processor ARM Cortex-A7 berjalan pada frekuensi 900MHz dengan memiliki RAM 1GB. Sistem operasi yang digunakan pada Raspberry Pi adalah Linux Debian Wheezy. Konsep penelitian ini menggunakan empat buah perangkat Raspberry Pi dimana dua Raspi digunakan sebagai web server dan dua Raspi lainnya digunakan sebagai penyeimbang beban (Load Balancer serta database server. Metode yang digunakan dalam pembangunan cluster server ini menggunakan metode load balancing, dimana beban server bekerja secara merata di masing-masing node. Pengujian yang diterapkan dengan melakukan perbandingan kinerja dari Raspbery Pi yang menangani lalu lintas data secara tunggal tanpa menggunakan load balancer serta pengujian Raspberry Pi dengan menggunakan load balancer sebagai beban penyeimbang antara anggota cluster server.
Lifting an unexpectedly heavy object : the effects on low-back loading and balance loss
van der Burg, J C; van Dieën, J H; Toussaint, H M
OBJECTIVE: This study evaluates the effects of lifting an unexpectedly heavy object on low-back loading and loss of balance. BACKGROUND: It is often suggested that lifting an unexpectedly heavy object may be a major risk factor for low-back pain. This may lead to an increase in muscle activation,
Multi-Class load balancing scheme for QoS and energy ...
African Journals Online (AJOL)
Multi-Class load balancing scheme for QoS and energy conservation in cloud computing. ... If you would like more information about how to print, save, and work with PDFs, Highwire Press provides a helpful Frequently Asked Questions about PDFs. Alternatively, you can download the PDF file directly to your computer, from ...
Portable Parallel Programming for the Dynamic Load Balancing of Unstructured Grid Applications
Biswas, Rupak; Das, Sajal K.; Harvey, Daniel; Oliker, Leonid
1999-01-01
The ability to dynamically adapt an unstructured -rid (or mesh) is a powerful tool for solving computational problems with evolving physical features; however, an efficient parallel implementation is rather difficult, particularly from the view point of portability on various multiprocessor platforms We address this problem by developing PLUM, tin automatic anti architecture-independent framework for adaptive numerical computations in a message-passing environment. Portability is demonstrated by comparing performance on an SP2, an Origin2000, and a T3E, without any code modifications. We also present a general-purpose load balancer that utilizes symmetric broadcast networks (SBN) as the underlying communication pattern, with a goal to providing a global view of system loads across processors. Experiments on, an SP2 and an Origin2000 demonstrate the portability of our approach which achieves superb load balance at the cost of minimal extra overhead.
Application of SVR with chaotic GASA algorithm in cyclic electric load forecasting
International Nuclear Information System (INIS)
Zhang, Wen Yu; Hong, Wei-Chiang; Dong, Yucheng; Tsai, Gary; Sung, Jing-Tian; Fan, Guo-feng
2012-01-01
The electric load forecasting is complicated, and it sometimes reveals cyclic changes due to cyclic economic activities or climate seasonal nature, such as hourly peak in a working day, weekly peak in a business week, and monthly peak in a demand planned year. Hybridization of support vector regression (SVR) with chaotic sequence and evolutionary algorithms has successfully been applied to improve forecasting accuracy, and to effectively avoid trapping in a local optimum. However, it has not been widely explored to employ SVR-based model to deal with cyclic electric load forecasting. This paper will firstly investigate the potentiality of a novel hybrid algorithm, namely chaotic genetic algorithm-simulated annealing algorithm (CGASA), with an SVR model to improve load forecasting accurate performance. In which, the proposed CGASA employs internal randomness of chaotic iterations to overcome premature local optimum. Secondly, the seasonal mechanism will then be applied to well adjust the cyclic load tendency. Finally, a numerical example from an existed reference is employed to compare the forecasting performance of the proposed SSVRCGASA model. The forecasting results show that the SSVRCGASA model yields more accurate forecasting results than ARIMA and TF-ε-SVR-SA models. -- Highlights: ► Hybridizing the seasonal adjustment mechanism into an SVR model. ► Employing chaotic sequence to improve the premature convergence of genetic algorithm and simulated annealing algorithm. ► Successfully providing significant accurate monthly load demand forecasting.
International Nuclear Information System (INIS)
Hong, W.-C.
2009-01-01
Accurate forecasting of electric load has always been the most important issues in the electricity industry, particularly for developing countries. Due to the various influences, electric load forecasting reveals highly nonlinear characteristics. Recently, support vector regression (SVR), with nonlinear mapping capabilities of forecasting, has been successfully employed to solve nonlinear regression and time series problems. However, it is still lack of systematic approaches to determine appropriate parameter combination for a SVR model. This investigation elucidates the feasibility of applying chaotic particle swarm optimization (CPSO) algorithm to choose the suitable parameter combination for a SVR model. The empirical results reveal that the proposed model outperforms the other two models applying other algorithms, genetic algorithm (GA) and simulated annealing algorithm (SA). Finally, it also provides the theoretical exploration of the electric load forecasting support system (ELFSS)
Efficient graph-based dynamic load-balancing for parallel large-scale agent-based traffic simulation
Xu, Y.; Cai, W.; Aydt, H.; Lees, M.; Tolk, A.; Diallo, S.Y.; Ryzhov, I.O.; Yilmaz, L.; Buckley, S.; Miller, J.A.
2014-01-01
One of the issues of parallelizing large-scale agent-based traffic simulations is partitioning and load-balancing. Traffic simulations are dynamic applications where the distribution of workload in the spatial domain constantly changes. Dynamic load-balancing at run-time has shown better efficiency
International Nuclear Information System (INIS)
Gong Zhaohu; Wang Kan; Yao Dong
2011-01-01
Highlights: → We present a new Loading Pattern Optimization method - Interval Bound Algorithm (IBA). → IBA directly uses the reactivity of fuel assemblies and burnable poison. → IBA can optimize fuel assembly orientation in a coupled way. → Numerical experiment shows that IBA outperforms genetic algorithm and engineers. → We devise DDWF technique to deal with multiple objectives and constraints. - Abstract: In order to optimize the core loading pattern in Nuclear Power Plants, the paper presents a new optimization method - Interval Bound Algorithm (IBA). Similar to the typical population based algorithms, e.g. genetic algorithm, IBA maintains a population of solutions and evolves them during the optimization process. IBA acquires the solution by statistical learning and sampling the control variable intervals of the population in each iteration. The control variables are the transforms of the reactivity of fuel assemblies or the worth of burnable poisons, which are the crucial heuristic information for loading pattern optimization problems. IBA can deal with the relationship between the dependent variables by defining the control variables. Based on the IBA algorithm, a parallel Loading Pattern Optimization code, named IBALPO, has been developed. To deal with multiple objectives and constraints, the Dynamic Discontinuous Weight Factors (DDWF) for the fitness function have been used in IBALPO. Finally, the code system has been used to solve a realistic reloading problem and a better pattern has been obtained compared with the ones searched by engineers and genetic algorithm, thus the performance of the code is proved.
A Novel Load Balancing Scheme for Multipath Routing Protocol in MANET
Directory of Open Access Journals (Sweden)
Kokilamani Mounagurusamy
2016-09-01
Full Text Available The recent advancements in information and communication technology create a great demand for multipath routing protocols. In MANET, nodes can be arbitrarily located and can move freely at any given time. The topology of MANET can change rapidly and unpredictably. Because wireless link capacities are usually limited, congestion is possible in MANETs. Hence, balancing the load in a MANET is important since nodes with high load will deplete their batteries quickly, thereby increasing the probability of disconnecting or partitioning the network. To overcome these, the multipath protocol should be aware of load at route discovery phase. The main objective of the proposed article is to balance the load on a node and to extend the lifetime of the node due to the congestion, energy depletion and link failures. This article describes a novel load and congestion aware scheme called Path Efficient Ad-hoc On-demand Multipath Distance Vector (PE-AOMDV protocol to increase the performance of routing process in MANET in terms of congestion, end-to-end delay and load balancing. A new threshold value and a counter variable are introduced to limit the number of communication paths passing over a node in route discovery phase. For every new request the counter variable is incremented by one and the threshold value is compared to see whether the maximum number of connections has been reached or not. The proposed method is network simulator ns-2 and it is found that there is a significant improvement in the proposed scheme. It reduces the energy consumption, average end-to-end delay and normalized routing overhead. Also the proposed scheme increases packet delivery ratio, throughput and minimizes routing overheads.
International Nuclear Information System (INIS)
Marzouk, Youssef M.; Ghoniem, Ahmed F.
2005-01-01
A number of complex physical problems can be approached through N-body simulation, from fluid flow at high Reynolds number to gravitational astrophysics and molecular dynamics. In all these applications, direct summation is prohibitively expensive for large N and thus hierarchical methods are employed for fast summation. This work introduces new algorithms, based on k-means clustering, for partitioning parallel hierarchical N-body interactions. We demonstrate that the number of particle-cluster interactions and the order at which they are performed are directly affected by partition geometry. Weighted k-means partitions minimize the sum of clusters' second moments and create well-localized domains, and thus reduce the computational cost of N-body approximations by enabling the use of lower-order approximations and fewer cells. We also introduce compatible techniques for dynamic load balancing, including adaptive scaling of cluster volumes and adaptive redistribution of cluster centroids. We demonstrate the performance of these algorithms by constructing a parallel treecode for vortex particle simulations, based on the serial variable-order Cartesian code developed by Lindsay and Krasny [Journal of Computational Physics 172 (2) (2001) 879-907]. The method is applied to vortex simulations of a transverse jet. Results show outstanding parallel efficiencies even at high concurrencies, with velocity evaluation errors maintained at or below their serial values; on a realistic distribution of 1.2 million vortex particles, we observe a parallel efficiency of 98% on 1024 processors. Excellent load balance is achieved even in the face of several obstacles, such as an irregular, time-evolving particle distribution containing a range of length scales and the continual introduction of new vortex particles throughout the domain. Moreover, results suggest that k-means yields a more efficient partition of the domain than a global oct-tree
DEFF Research Database (Denmark)
Pedersen, Lars-Flemming; Suhr, Karin Isabel; Dalsgaard, Anne Johanne Tang
2012-01-01
This study investigated the effects of applying four fixed feed loadings to three replicated recirculating aquaculture systems (RAS) on water quality changes, nitrogenous balances and growth performance of rainbow trout (Oncorhynchus mykiss).Feed loadings ranged from 1.6 to 6.3kgfeed/m3 make-up...... water, with a constant make-up water renewal of 4.7% of total water volume per day in all twelve RAS. Fish densities ranged from 14 to 92kg/m3 during the prolonged trial of 10weeks. Selected water quality parameters were measured during two intensive sampling campaigns, evaluating biofilter...
Cellular Genetic Algorithm with Communicating Grids for Assembly Line Balancing Problems
Directory of Open Access Journals (Sweden)
BRUDARU, O.
2010-05-01
Full Text Available This paper presents a new approach with cellular multigrid genetic algorithms for the "I"-shaped and "U"-shaped assembly line balancing problems, including parallel workstations and compatibility constraints. First, a cellular hybrid genetic algorithm that uses a single grid is described. Appropriate operators for mutation, hypermutation, and crossover and two devoration techniques are proposed for creating and maintaining groups based on similarity. This monogrid algorithm is extended for handling many populations placed on different grids. In the multigrid version, the population of each grid is organized in clusters using the positional information of the chromosomes. A similarity preserving communication protocol between the clusters placed on different grids is introduced. The experimental evaluation shows that the multigrid cellular genetic algorithm with communicating grids is better than the hybrid genetic algorithm used for building it, whereas it dominates the monogrid version in all cases. Absolute performance is evaluated using classical benchmarks. The role of certain components of the cellular algorithm is explained and the effect of some parameters is evaluated.
Dynamic Load Balancing Based on Constrained K-D Tree Decomposition for Parallel Particle Tracing
Energy Technology Data Exchange (ETDEWEB)
Zhang, Jiang; Guo, Hanqi; Yuan, Xiaoru; Hong, Fan; Peterka, Tom
2018-01-01
Particle tracing is a fundamental technique in flow field data visualization. In this work, we present a novel dynamic load balancing method for parallel particle tracing. Specifically, we employ a constrained k-d tree decomposition approach to dynamically redistribute tasks among processes. Each process is initially assigned a regularly partitioned block along with duplicated ghost layer under the memory limit. During particle tracing, the k-d tree decomposition is dynamically performed by constraining the cutting planes in the overlap range of duplicated data. This ensures that each process is reassigned particles as even as possible, and on the other hand the new assigned particles for a process always locate in its block. Result shows good load balance and high efficiency of our method.
An Image Encryption Algorithm Based on Balanced Pixel and Chaotic Map
Directory of Open Access Journals (Sweden)
Jian Zhang
2014-01-01
Full Text Available Image encryption technology has been applied in many fields and is becoming the main way of protecting the image information security. There are also many ways of image encryption. However, the existing encryption algorithms, in order to obtain a better effect of encryption, always need encrypting several times. There is not an effective method to decide the number of encryption times, generally determined by the human eyes. The paper proposes an image encryption algorithm based on chaos and simultaneously proposes a balanced pixel algorithm to determine the times of image encryption. Many simulation experiments have been done including encryption effect and security analysis. Experimental results show that the proposed method is feasible and effective.
Controlling the Balance of Exploration and Exploitation in ACO Algorithm
Directory of Open Access Journals (Sweden)
Ayad Mohammed Jabbar
2018-02-01
Full Text Available Ant colony optimization is a meta-heuristic algorithm inspired by the foraging behavior of real ant colony. The algorithm is a population-based solution employed in different optimization problems such as classification, image processing, clustering, and so on. This paper sheds the light on the side of improving the results of traveling salesman problem produced by the algorithm. The key success that produces the valuable results is due to the two important components of exploration and exploitation. Balancing both components is the foundation of controlling search within the ACO. This paper proposes to modify the main probabilistic method to overcome the drawbacks of the exploration problem and produces global optimal results in high dimensional space. Experiments on six variant of ant colony optimization indicate that the proposed work produces high-quality results in terms of shortest route
Enhanced method of fast re-routing with load balancing in software-defined networks
Lemeshko, Oleksandr; Yeremenko, Oleksandra
2017-11-01
A two-level method of fast re-routing with load balancing in a software-defined network (SDN) is proposed. The novelty of the method consists, firstly, in the introduction of a two-level hierarchy of calculating the routing variables responsible for the formation of the primary and backup paths, and secondly, in ensuring a balanced load of the communication links of the network, which meets the requirements of the traffic engineering concept. The method provides implementation of link, node, path, and bandwidth protection schemes for fast re-routing in SDN. The separation in accordance with the interaction prediction principle along two hierarchical levels of the calculation functions of the primary (lower level) and backup (upper level) routes allowed to abandon the initial sufficiently large and nonlinear optimization problem by transiting to the iterative solution of linear optimization problems of half the dimension. The analysis of the proposed method confirmed its efficiency and effectiveness in terms of obtaining optimal solutions for ensuring balanced load of communication links and implementing the required network element protection schemes for fast re-routing in SDN.
Load balancing in highly parallel processing of Monte Carlo code for particle transport
International Nuclear Information System (INIS)
Higuchi, Kenji; Takemiya, Hiroshi; Kawasaki, Takuji
1998-01-01
In parallel processing of Monte Carlo (MC) codes for neutron, photon and electron transport problems, particle histories are assigned to processors making use of independency of the calculation for each particle. Although we can easily parallelize main part of a MC code by this method, it is necessary and practically difficult to optimize the code concerning load balancing in order to attain high speedup ratio in highly parallel processing. In fact, the speedup ratio in the case of 128 processors remains in nearly one hundred times when using the test bed for the performance evaluation. Through the parallel processing of the MCNP code, which is widely used in the nuclear field, it is shown that it is difficult to attain high performance by static load balancing in especially neutron transport problems, and a load balancing method, which dynamically changes the number of assigned particles minimizing the sum of the computational and communication costs, overcomes the difficulty, resulting in nearly fifteen percentage of reduction for execution time. (author)
Directory of Open Access Journals (Sweden)
Ioannis P. Panapakidis
2018-02-01
Full Text Available Due to high implementation rates of smart meter systems, considerable amount of research is placed in machine learning tools for data handling and information retrieval. A key tool in load data processing is clustering. In recent years, a number of researches have proposed different clustering algorithms in the load profiling field. The present paper provides a methodology for addressing the aforementioned problem through Multi-Criteria Decision Analysis (MCDA and namely, using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS. A comparison of the algorithms is employed. Next, a single test case on the selection of an algorithm is examined. User specific weights are applied and based on these weight values, the optimal algorithm is drawn.
Angular-contact ball-bearing internal load estimation algorithm using runtime adaptive relaxation
Medina, H.; Mutu, R.
2017-07-01
An algorithm to estimate internal loads for single-row angular contact ball bearings due to externally applied thrust loads and high-operating speeds is presented. A new runtime adaptive relaxation procedure and blending function is proposed which ensures algorithm stability whilst also reducing the number of iterations needed to reach convergence, leading to an average reduction in computation time in excess of approximately 80%. The model is validated based on a 218 angular contact bearing and shows excellent agreement compared to published results.
Genetic algorithm for the optimization of the loading pattern for reactor core fuel management
International Nuclear Information System (INIS)
Zhou Sheng; Hu Yongming; zheng Wenxiang
2000-01-01
The paper discusses the application of a genetic algorithm to the optimization of the loading pattern for in-core fuel management with the NP characteristics. The algorithm develops a matrix model for the fuel assembly loading pattern. The burnable poisons matrix was assigned randomly considering the distributed nature of the poisons. A method based on the traveling salesman problem was used to solve the problem. A integrated code for in-core fuel management was formed by combining this code with a reactor physics code
Multiobjective Economic Load Dispatch in 3-D Space by Genetic Algorithm
Jain, N. K.; Nangia, Uma; Singh, Iqbal
2017-10-01
This paper presents the application of genetic algorithm to Multiobjective Economic Load Dispatch (MELD) problem considering fuel cost, transmission losses and environmental pollution as objective functions. The MELD problem has been formulated using constraint method. The non-inferior set for IEEE 5, 14 and 30-bus system has been generated by using genetic algorithm and the target point has been obtained by using maximization of minimum relative attainments.
Comparison of optimization of loading patterns on the basis of SA and PMA algorithms
International Nuclear Information System (INIS)
Beliczai, Botond
2007-01-01
Optimization of loading patterns is a very important task from economical point of view in a nuclear power plant. The optimization algorithms used for this purpose can be categorized basically into two categories: deterministic ones and stochastic ones. In the Paks nuclear power plant a deterministic optimization procedure is used to optimize the loading pattern at BOC, so that the core would have maximal reactivity reserve. To the group of stochastic optimization procedures belong mainly simulated annealing (SA) procedures and genetic algorithms (GA). There are new procedures as well, which try to combine the advantages of SAs and GAs. One of them is called population mutation annealing algorithm (PMA). In the Paks NPP we would like to introduce fuel assemblies including burnable poison (Gd) in the near future. In order to be able to find the optimal loading pattern (or near-optimal loading patterns) in that case, we have to optimize our core not only for objective functions defined at BOC, but at EOC as well. For this purpose I used stochastic algorithms (SA and PMA) to investigate loading pattern optimization results for different objective functions at BOC. (author)
Energy Balance Routing Algorithm Based on Virtual MIMO Scheme for Wireless Sensor Networks
Directory of Open Access Journals (Sweden)
Jianpo Li
2014-01-01
Full Text Available Wireless sensor networks are usually energy limited and therefore an energy-efficient routing algorithm is desired for prolonging the network lifetime. In this paper, we propose a new energy balance routing algorithm which has the following three improvements over the conventional LEACH algorithm. Firstly, we propose a new cluster head selection scheme by taking into consideration the remaining energy and the most recent energy consumption of the nodes and the entire network. In this way, the sensor nodes with smaller remaining energy or larger energy consumption will be much less likely to be chosen as cluster heads. Secondly, according to the ratio of remaining energy to distance, cooperative nodes are selected to form virtual MIMO structures. It mitigates the uneven distribution of clusters and the unbalanced energy consumption of the whole network. Thirdly, we construct a comprehensive energy consumption model, which can reflect more realistically the practical energy consumption. Numerical simulations analyze the influences of cooperative node numbers and cluster head node numbers on the network lifetime. It is shown that the energy consumption of the proposed routing algorithm is lower than the conventional LEACH algorithm and for the simulation example the network lifetime is prolonged about 25%.
Adaptive algorithm for predicting increases in central loads of electrical energy systems
Energy Technology Data Exchange (ETDEWEB)
Arbachyauskene, N A; Pushinaytis, K V
1982-01-01
An adaptive algorithm for predicting increases in central loads of the electrical energy system is suggested for the task of evaluating the condition. The algorithm is based on the Kalman filter. In order to calculate the coefficient of intensification, the a priori assigned noise characteristics with low accuracy are used only in the beginning of the calculation. Further, the coefficient of intensification is calculated from the innovation sequence. This approach makes it possible to correct errors in the assignment of the statistical noise characteristics and to follow their changes. The algorithm is experimentally verified.
L2-LBMT: A Layered Load Balance Routing Protocol for underwater multimedia data transmission
Lv, Ze; Tang, Ruichun; Tao, Ye; Sun, Xin; Xu, Xiaowei
2017-12-01
Providing highly efficient underwater transmission of mass multimedia data is challenging due to the particularities of the underwater environment. Although there are many schemes proposed to optimize the underwater acoustic network communication protocols, from physical layer, data link layer, network layer to transport layer, the existing routing protocols for underwater wireless sensor network (UWSN) still cannot well deal with the problems in transmitting multimedia data because of the difficulties involved in high energy consumption, low transmission reliability or high transmission delay. It prevents us from applying underwater multimedia data to real-time monitoring of marine environment in practical application, especially in emergency search, rescue operation and military field. Therefore, the inefficient transmission of marine multimedia data has become a serious problem that needs to be solved urgently. In this paper, A Layered Load Balance Routing Protocol (L2-LBMT) is proposed for underwater multimedia data transmission. In L2-LBMT, we use layered and load-balance Ad Hoc Network to transmit data, and adopt segmented data reliable transfer (SDRT) protocol to improve the data transport reliability. And a 3-node variant of tornado (3-VT) code is also combined with the Ad Hoc Network to transmit little emergency data more quickly. The simulation results show that the proposed protocol can balance energy consumption of each node, effectively prolong the network lifetime and reduce transmission delay of marine multimedia data.
Assessment of load of beam-balanced pumping units by electric motor power indicators
Directory of Open Access Journals (Sweden)
Д. И. Шишлянников
2017-10-01
Full Text Available The results of experimental studies on the loading of beam-balanced pumping units (BP of sucker rod- pumping equipment (SRPE are presented. It is noted that the key factor that has the most significant effect causing the SRPE failure is the balance of the beam pumping unit, which determines the amount of specific energy consumption for the rise of reservoir fluid and the level of dynamic loads on the machine units. The urgency of using software-recording systems for estimating the loading of units of oil field pumping installations is substantiated. The principle of operation and design of the «AKD-SK» software recording system is described. The prospects of using this method for controlling the performance parameters and evaluating the technical state of the sicker rod-pumping units is proved on the basis of an analysis of the magnitude and nature of the changes in the loads of drive motors determined by the registration of the instantaneous values of the consumed power. The main provisions of the methodology for analyzing the watt-meters of drive motors of the sucker rod-pumping units are outlined. The nature of the manifestation of the main defects of submersible pumps and beam-balanced pumping units is described. The results of pilot-industrial tests of the beam-balanced pumping units equipped with advanced permanent magnet motors and intelligent control stations are presented. It is proved that the use of permanent magnet motors allows to reduce the specific energy consumption for the rise of reservoir fluid, which increases the efficiency of the SRPE.However, the presence of transient processes and generator operating modes of the permanent magnet motors results in the occurrence of significant dynamic loads, which, due to the rigid fixing of the rotor of magnet motor on the reducer shaft, negatively affect the life of the gearbox bearings. It has been shown that the lack of its own bearings in the tested motors causes a high probability
Adaptive Swarm Balancing Algorithms for rare-event prediction in imbalanced healthcare data
Wong, Raymond K.; Mohammed, Sabah; Fiaidhi, Jinan; Sung, Yunsick
2017-01-01
Clinical data analysis and forecasting have made substantial contributions to disease control, prevention and detection. However, such data usually suffer from highly imbalanced samples in class distributions. In this paper, we aim to formulate effective methods to rebalance binary imbalanced dataset, where the positive samples take up only the minority. We investigate two different meta-heuristic algorithms, particle swarm optimization and bat algorithm, and apply them to empower the effects of synthetic minority over-sampling technique (SMOTE) for pre-processing the datasets. One approach is to process the full dataset as a whole. The other is to split up the dataset and adaptively process it one segment at a time. The experimental results reported in this paper reveal that the performance improvements obtained by the former methods are not scalable to larger data scales. The latter methods, which we call Adaptive Swarm Balancing Algorithms, lead to significant efficiency and effectiveness improvements on large datasets while the first method is invalid. We also find it more consistent with the practice of the typical large imbalanced medical datasets. We further use the meta-heuristic algorithms to optimize two key parameters of SMOTE. The proposed methods lead to more credible performances of the classifier, and shortening the run time compared to brute-force method. PMID:28753613
Application of self-balanced loading test to socketed pile in weak rock
Cheng, Ye; Gong, Weiming; Dai, Guoliang; Wu, JingKun
2008-11-01
Method of self-balanced loading test differs from the traditional methods of pile test. The key equipment of the test is a cell. The cell specially designed is used to exert load which is placed in pile body. During the test, displacement values of the top plate and the bottom plate of the cell are recorded according to every level of load. So Q-S curves can be obtained. In terms of test results, the bearing capacity of pile can be judged. Equipments of the test are simply and cost of it is low. Under some special conditions, the method will take a great advantage. In Guangxi Province, tertiary mudstone distributes widely which is typical weak rock. It is usually chosen as the bearing stratum of pile foundation. In order to make full use of its high bearing capacity, pile is generally designed as belled pile. Foundations of two high-rise buildings which are close to each other are made up of belled socketed piles in weak rock. To obtain the bearing capacity of the belled socketed pile in weak rock, loading test in situ should be taken since it is not reasonable that experimental compression strength of the mudstone is used for design. The self-balanced loading test was applied to eight piles of two buildings. To get the best test effect, the assembly of cell should be taken different modes in terms of the depth that pile socketed in rock and the dimension of the enlarged toe. The assembly of cells had been taken three modes, and tests were carried on successfully. By the self-balanced loading test, the large bearing capacities of belled socketed piles were obtained. Several key parameters required in design were achieved from the tests. For the data of tests had been analyzed, the bearing performance of pile tip, pile side and whole pile was revealed. It is further realized that the bearing capacity of belled socketed pile in the mudstone will decrease after the mudstone it socketed in has been immerged. Among kinds of mineral ingredient in the mudstone
A Web-Based Tool to Interpolate Nitrogen Loading Using a Genetic Algorithm
Directory of Open Access Journals (Sweden)
Youn Shik Park
2014-09-01
Full Text Available Water quality data may not be collected at a high frequency, nor over the range of streamflow data. For instance, water quality data are often collected monthly, biweekly, or weekly, since collecting and analyzing water quality samples are costly compared to streamflow data. Regression models are often used to interpolate pollutant loads from measurements made intermittently. Web-based Load Interpolation Tool (LOADIN was developed to provide user-friendly interfaces and to allow use of streamflow and water quality data from U.S. Geological Survey (USGS via web access. LOADIN has a regression model assuming that instantaneous load is comprised of the pollutant load based on streamflow and the pollutant load variation within the period. The regression model has eight coefficients determined by a genetic algorithm with measured water quality data. LOADIN was applied to eleven water quality datasets from USGS gage stations located in Illinois, Indiana, Michigan, Minnesota, and Wisconsin states with drainage areas from 44 km2 to 1,847,170 km2. Measured loads were calculated by multiplying nitrogen data by streamflow data associated with measured nitrogen data. The estimated nitrogen loads and measured loads were evaluated using Nash-Sutcliffe Efficiency (NSE and coefficient of determination (R2. NSE ranged from 0.45 to 0.91, and R2 ranged from 0.51 to 0.91 for nitrogen load estimation.
International Nuclear Information System (INIS)
Hong, Wei-Chiang
2011-01-01
Support vector regression (SVR), with hybrid chaotic sequence and evolutionary algorithms to determine suitable values of its three parameters, not only can effectively avoid converging prematurely (i.e., trapping into a local optimum), but also reveals its superior forecasting performance. Electric load sometimes demonstrates a seasonal (cyclic) tendency due to economic activities or climate cyclic nature. The applications of SVR models to deal with seasonal (cyclic) electric load forecasting have not been widely explored. In addition, the concept of recurrent neural networks (RNNs), focused on using past information to capture detailed information, is helpful to be combined into an SVR model. This investigation presents an electric load forecasting model which combines the seasonal recurrent support vector regression model with chaotic artificial bee colony algorithm (namely SRSVRCABC) to improve the forecasting performance. The proposed SRSVRCABC employs the chaotic behavior of honey bees which is with better performance in function optimization to overcome premature local optimum. A numerical example from an existed reference is used to elucidate the forecasting performance of the proposed SRSVRCABC model. The forecasting results indicate that the proposed model yields more accurate forecasting results than ARIMA and TF-ε-SVR-SA models. Therefore, the SRSVRCABC model is a promising alternative for electric load forecasting. -- Highlights: → Hybridizing the seasonal adjustment and the recurrent mechanism into an SVR model. → Employing chaotic sequence to improve the premature convergence of artificial bee colony algorithm. → Successfully providing significant accurate monthly load demand forecasting.
International Nuclear Information System (INIS)
Martin-del-Campo, Cecilia; Francois, Juan Luis; Avendano, Linda; Gonzalez, Mario
2004-01-01
An optimization system based on Genetic Algorithms (GAs), in combination with expert knowledge coded in heuristics rules, was developed for the design of optimized boiling water reactor (BWR) fuel loading patterns. The system was coded in a computer program named Loading Pattern Optimization System based on Genetic Algorithms, in which the optimization code uses GAs to select candidate solutions, and the core simulator code CM-PRESTO to evaluate them. A multi-objective function was built to maximize the cycle energy length while satisfying power and reactivity constraints used as BWR design parameters. Heuristic rules were applied to satisfy standard fuel management recommendations as the Control Cell Core and Low Leakage loading strategies, and octant symmetry. To test the system performance, an optimized cycle was designed and compared against an actual operating cycle of Laguna Verde Nuclear Power Plant, Unit I
Artificial bee colony algorithm for economic load dispatch with wind power energy
Directory of Open Access Journals (Sweden)
Safari Amin
2016-01-01
Full Text Available This paper presents an efficient Artificial Bee Colony (ABC algorithm for solving large scale economic load dispatch (ELD problems in power networks. To realize the ELD, the valve-point loading effect, system load demand, power losses, ramp rate limits and prohibited operation zones are considered here. Simulations were performed on four different power systems with 3, 6, 15 and 40 generating units and the results are compared with two forms of power systems, one power system is with a wind power generator and other power system is without a wind power generator. The results of this study reveal that the proposed approach is able to find appreciable ELD solutions than those of previous algorithms.
Performance evaluation of Genetic Algorithms on loading pattern optimization of PWRs
International Nuclear Information System (INIS)
Tombakoglu, M.; Bekar, K.B.; Erdemli, A.O.
2001-01-01
Genetic Algorithm (GA) based systems are used for search and optimization problems. There are several applications of GAs in literature successfully applied for loading pattern optimization problems. In this study, we have selected loading pattern optimization problem of Pressurised Water Reactor (PWR). The main objective of this work is to evaluate the performance of Genetic Algorithm operators such as regional crossover, crossover and mutation, and selection and construction of initial population and its size for PWR loading pattern optimization problems. The performance of GA with antithetic variates is compared to traditional GA. Antithetic variates are used to generate the initial population and its use with GA operators are also discussed. Finally, the results of multi-cycle optimization problems are discussed for objective function taking into account cycle burn-up and discharge burn-up.(author)
International Nuclear Information System (INIS)
Gherbi, Chirihane; Aliouat, Zibouda; Benmohammed, Mohamed
2016-01-01
Clustering is a well known approach to cope with large nodes density and efficiently conserving energy in Wireless Sensor Networks (WSN). Load balancing is an effective approach for optimizing resources like channel bandwidth, the main objective of this paper is to combine these two valuable approaches in order to significantly improve the main WSN service such as information routing. So, our proposal is a routing protocol in which load traffic is shared among cluster members in order to reduce the dropping probability due to queue overflow at some nodes. To this end, a novel hierarchical approach, called Hierarchical Energy-Balancing Multipath routing protocol for Wireless Sensor Networks (HEBM) is proposed. The HEBM approach aims to fulfill the following purposes: decreasing the overall network energy consumption, balancing the energy dissipation among the sensor nodes and as direct consequence: extending the lifetime of the network. In fact, the cluster-heads are optimally determined and suitably distributed over the area of interest allowing the member nodes reaching them with adequate energy dissipation and appropriate load balancing utilization. In addition, nodes radio are turned off for fixed time duration according to sleeping control rules optimizing so their energy consumption. The performance evaluation of the proposed protocol is carried out through the well-known NS2 simulator and the exhibited results are convincing. Like this, the residual energy of sensor nodes was measured every 20 s throughout the duration of simulation, in order to calculate the total number of alive nodes. Based on the simulation results, we concluded that our proposed HEBM protocol increases the profit of energy, and prolongs the network lifetime duration from 32% to 40% compared to DEEAC reference protocol and from 25% to 28% compared to FEMCHRP protocol. The authors also note that the proposed protocol is 41.7% better than DEEAC with respect to FND (Fist node die), and 25
Directory of Open Access Journals (Sweden)
Ridho Syahrial Ibrahim
2017-03-01
Full Text Available Maraknya isu global warming serta keterbatasan sumber daya alam membuat mulai banyaknya dibangun pembangkit-pembangkit listrik dengan renewable energy, salah satunya adalah pembangkit tenaga angin. Pada jurnal ini, firefly algorithm diterapkan untuk mengoptimasi total biaya pembangkitan 2 buah sistem uji, tanpa dan dengan mempertimbangkan penambahan tenaga angin. Hasil simulasi menunjukkan bahwa dengan penambahan pembangkit tenaga angin ke dalam sistem tenaga listrik, total biaya pembangkitan tidak selalu lebih murah. Selain itu, hasil simulasi juga menunjukkan bahwa firefly algorithm sebagai metode optimasi dapat menyelesaikan permasalahan economic load dispatch (ELD lebih baik dibandingkan metode lain yang sudah dilakukan, yaitu particle swarm optimization (PSO, bat algorithm (BA, biogeography-based optimization (BBO dan plant growth simulation algorithm (PGSA dengan persentase selisih nilai penghematan total biaya berkisar antara 0.32% ($50 hingga 9.27% ($11884.
Multicycle Optimization of Advanced Gas-Cooled Reactor Loading Patterns Using Genetic Algorithms
International Nuclear Information System (INIS)
Ziver, A. Kemal; Carter, Jonathan N.; Pain, Christopher C.; Oliveira, Cassiano R.E. de; Goddard, Antony J. H.; Overton, Richard S.
2003-01-01
A genetic algorithm (GA)-based optimizer (GAOPT) has been developed for in-core fuel management of advanced gas-cooled reactors (AGRs) at HINKLEY B and HARTLEPOOL, which employ on-load and off-load refueling, respectively. The optimizer has been linked to the reactor analysis code PANTHER for the automated evaluation of loading patterns in a two-dimensional geometry, which is collapsed from the three-dimensional reactor model. GAOPT uses a directed stochastic (Monte Carlo) algorithm to generate initial population members, within predetermined constraints, for use in GAs, which apply the standard genetic operators: selection by tournament, crossover, and mutation. The GAOPT is able to generate and optimize loading patterns for successive reactor cycles (multicycle) within acceptable CPU times even on single-processor systems. The algorithm allows radial shuffling of fuel assemblies in a multicycle refueling optimization, which is constructed to aid long-term core management planning decisions. This paper presents the application of the GA-based optimization to two AGR stations, which apply different in-core management operational rules. Results obtained from the testing of GAOPT are discussed
Energy Technology Data Exchange (ETDEWEB)
Ziver, A.K. E-mail: a.k.ziver@imperial.ac.uk; Pain, C.C; Carter, J.N.; Oliveira, C.R.E. de; Goddard, A.J.H.; Overton, R.S
2004-03-01
A non-generational genetic algorithm (GA) has been developed for fuel management optimisation of Advanced Gas-Cooled Reactors, which are operated by British Energy and produce around 20% of the UK's electricity requirements. An evolutionary search is coded using the genetic operators; namely selection by tournament, two-point crossover, mutation and random assessment of population for multi-cycle loading pattern (LP) optimisation. A detailed description of the chromosomes in the genetic algorithm coded is presented. Artificial Neural Networks (ANNs) have been constructed and trained to accelerate the GA-based search during the optimisation process. The whole package, called GAOPT, is linked to the reactor analysis code PANTHER, which performs fresh fuel loading, burn-up and power shaping calculations for each reactor cycle by imposing station-specific safety and operational constraints. GAOPT has been verified by performing a number of tests, which are applied to the Hinkley Point B and Hartlepool reactors. The test results giving loading pattern (LP) scenarios obtained from single and multi-cycle optimisation calculations applied to realistic reactor states of the Hartlepool and Hinkley Point B reactors are discussed. The results have shown that the GA/ANN algorithms developed can help the fuel engineer to optimise loading patterns in an efficient and more profitable way than currently available for multi-cycle refuelling of AGRs. Research leading to parallel GAs applied to LP optimisation are outlined, which can be adapted to present day LWR fuel management problems.
Physics Based Model for Cryogenic Chilldown and Loading. Part I: Algorithm
Luchinsky, Dmitry G.; Smelyanskiy, Vadim N.; Brown, Barbara
2014-01-01
We report the progress in the development of the physics based model for cryogenic chilldown and loading. The chilldown and loading is model as fully separated non-equilibrium two-phase flow of cryogenic fluid thermally coupled to the pipe walls. The solution follow closely nearly-implicit and semi-implicit algorithms developed for autonomous control of thermal-hydraulic systems developed by Idaho National Laboratory. A special attention is paid to the treatment of instabilities. The model is applied to the analysis of chilldown in rapid loading system developed at NASA-Kennedy Space Center. The nontrivial characteristic feature of the analyzed chilldown regime is its active control by dump valves. The numerical predictions are in reasonable agreement with the experimental time traces. The obtained results pave the way to the development of autonomous loading operation on the ground and space.
云计算环境下的DPSO资源负载均衡算法%DPSO resource load balancing in cloud computing
Institute of Scientific and Technical Information of China (English)
冯小靖; 潘郁
2013-01-01
Load balancing problem is one of the hot issues in cloud computing. Discrete particle swarm optimization algoritm is used to research load balancing on cloud computing environment. According to dynamic change of resources demand and low require of servers, each resource management node servers as node of the topological structure, and this paper establishes appropriate resource-task model which is resolved by DPSO. Verification results show that the algorithm enhances the utilization ratio and load balancing of resources.%负载均衡问题是云计算研究的热点问题之一.运用离散粒子群算法对云计算环境下的负载均衡问题进行研究,根据云计算环境下资源需求动态变化,并且对资源节点服务器的要求较低的特点,把各个资源节点当做网络拓扑结构中的各个节点,建立相应的资源-任务分配模型,运用离散粒子群算法实现资源负载均衡.验证表明,该算法提高了资源利用率和云计算资源的负载均衡.
Amien, S.; Yoga, W.; Fahmi, F.
2018-02-01
Synchronous generators are a major tool in an electrical energy generating systems, the load supplied by the generator is unbalanced. This paper discusses the effect of synchronous generator temperature on the condition of balanced load and unbalanced load, which will then be compared with the measurement result of both states of the generator. Unbalanced loads can be caused by various asymmetric disturbances in the power system and the failure of load forecasting studies so that the load distribution in each phase is not the same and causing the excessive heat of the generator. The method used in data collection was by using an infrared thermometer and resistance calculation method. The temperature comparison result between the resistive, inductive and capacitive loads in the highest temperature balance occured when the generator is loaded with a resistive load, where T = 31.9 ° C and t = 65 minutes. While in a state of unbalanced load the highest temperature occured when the generator is loaded with a capacitive load, where T = 40.1 ° C and t = 60 minutes. By understanding this behavior, we can maintain the generator for longer operation life.
Operational Strategy of CBPs for load balancing of Operators in Advanced Main Control Room
International Nuclear Information System (INIS)
Kim, Seunghwan; Kim, Yochan; Jung, Wondea
2014-01-01
With the using of a computer-based control room in an APR1400 (Advanced Pressurized Reactor-1400), the operators' behaviors in the main control room had changed. However, though the working environment of operators has been changed a great deal, digitalized interfaces can also change the cognitive tasks or activities of operators. First, a shift supervisor (SS) can confirm/check the conduction of the procedures and the execution of actions of board operators (BOs) while confirming directly the operation variables without relying on the BOs. Second, all operators added to their work the use of a new CBP and Soft Controls, increasing their procedural workload. New operational control strategies of CBPs are necessary for load balancing of operator's task load in APR1400. In this paper, we compared the workloads of operators in an APR1400 who work with two different usages of the CBP. They are SS oriented usage and SS-BO collaborative usage. In this research, we evaluated the workloads of operators in an advanced main control room by the COCOA method. Two types of CBP usages were defined and the effects of these usages on the workloads were investigated. The obtained results showed that the workloads between operators in a control room can be balanced according to the CBP usages by assigning control authority to the operators
Operational Strategy of CBPs for load balancing of Operators in Advanced Main Control Room
Energy Technology Data Exchange (ETDEWEB)
Kim, Seunghwan; Kim, Yochan; Jung, Wondea [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)
2014-05-15
With the using of a computer-based control room in an APR1400 (Advanced Pressurized Reactor-1400), the operators' behaviors in the main control room had changed. However, though the working environment of operators has been changed a great deal, digitalized interfaces can also change the cognitive tasks or activities of operators. First, a shift supervisor (SS) can confirm/check the conduction of the procedures and the execution of actions of board operators (BOs) while confirming directly the operation variables without relying on the BOs. Second, all operators added to their work the use of a new CBP and Soft Controls, increasing their procedural workload. New operational control strategies of CBPs are necessary for load balancing of operator's task load in APR1400. In this paper, we compared the workloads of operators in an APR1400 who work with two different usages of the CBP. They are SS oriented usage and SS-BO collaborative usage. In this research, we evaluated the workloads of operators in an advanced main control room by the COCOA method. Two types of CBP usages were defined and the effects of these usages on the workloads were investigated. The obtained results showed that the workloads between operators in a control room can be balanced according to the CBP usages by assigning control authority to the operators.
Li, Bai; Gong, Li-gang; Yang, Wen-lun
2014-01-01
Unmanned combat aerial vehicles (UCAVs) have been of great interest to military organizations throughout the world due to their outstanding capabilities to operate in dangerous or hazardous environments. UCAV path planning aims to obtain an optimal flight route with the threats and constraints in the combat field well considered. In this work, a novel artificial bee colony (ABC) algorithm improved by a balance-evolution strategy (BES) is applied in this optimization scheme. In this new algorithm, convergence information during the iteration is fully utilized to manipulate the exploration/exploitation accuracy and to pursue a balance between local exploitation and global exploration capabilities. Simulation results confirm that BE-ABC algorithm is more competent for the UCAV path planning scheme than the conventional ABC algorithm and two other state-of-the-art modified ABC algorithms.
Directory of Open Access Journals (Sweden)
Bai Li
2014-01-01
Full Text Available Unmanned combat aerial vehicles (UCAVs have been of great interest to military organizations throughout the world due to their outstanding capabilities to operate in dangerous or hazardous environments. UCAV path planning aims to obtain an optimal flight route with the threats and constraints in the combat field well considered. In this work, a novel artificial bee colony (ABC algorithm improved by a balance-evolution strategy (BES is applied in this optimization scheme. In this new algorithm, convergence information during the iteration is fully utilized to manipulate the exploration/exploitation accuracy and to pursue a balance between local exploitation and global exploration capabilities. Simulation results confirm that BE-ABC algorithm is more competent for the UCAV path planning scheme than the conventional ABC algorithm and two other state-of-the-art modified ABC algorithms.
Simultaneous optimization of the cavity heat load and trip rates in linacs using a genetic algorithm
Directory of Open Access Journals (Sweden)
Balša Terzić
2014-10-01
Full Text Available In this paper, a genetic algorithm-based optimization is used to simultaneously minimize two competing objectives guiding the operation of the Jefferson Lab’s Continuous Electron Beam Accelerator Facility linacs: cavity heat load and radio frequency cavity trip rates. The results represent a significant improvement to the standard linac energy management tool and thereby could lead to a more efficient Continuous Electron Beam Accelerator Facility configuration. This study also serves as a proof of principle of how a genetic algorithm can be used for optimizing other linac-based machines.
Directory of Open Access Journals (Sweden)
Cheng-Wen Lee
2017-11-01
Full Text Available Accurate electricity forecasting is still the critical issue in many energy management fields. The applications of hybrid novel algorithms with support vector regression (SVR models to overcome the premature convergence problem and improve forecasting accuracy levels also deserve to be widely explored. This paper applies chaotic function and quantum computing concepts to address the embedded drawbacks including crossover and mutation operations of genetic algorithms. Then, this paper proposes a novel electricity load forecasting model by hybridizing chaotic function and quantum computing with GA in an SVR model (named SVRCQGA to achieve more satisfactory forecasting accuracy levels. Experimental examples demonstrate that the proposed SVRCQGA model is superior to other competitive models.
Patel, Jitendra Kumar; Natarajan, Ganesh
2017-12-01
We discuss the development and assessment of a robust numerical algorithm for simulating multiphase flows with complex interfaces and high density ratios on arbitrary polygonal meshes. The algorithm combines the volume-of-fluid method with an incremental projection approach for incompressible multiphase flows in a novel hybrid staggered/non-staggered framework. The key principles that characterise the algorithm are the consistent treatment of discrete mass and momentum transport and the similar discretisation of force terms appearing in the momentum equation. The former is achieved by invoking identical schemes for convective transport of volume fraction and momentum in the respective discrete equations while the latter is realised by representing the gravity and surface tension terms as gradients of suitable scalars which are then discretised in identical fashion resulting in a balanced formulation. The hybrid staggered/non-staggered framework employed herein solves for the scalar normal momentum at the cell faces, while the volume fraction is computed at the cell centroids. This is shown to naturally lead to similar terms for pressure and its correction in the momentum and pressure correction equations respectively, which are again treated discretely in a similar manner. We show that spurious currents that corrupt the solution may arise both from an unbalanced formulation where forces (gravity and surface tension) are discretised in dissimilar manner and from an inconsistent approach where different schemes are used to convect the mass and momentum, with the latter prominent in flows which are convection-dominant with high density ratios. Interestingly, the inconsistent approach is shown to perform as well as the consistent approach even for high density ratio flows in some cases while it exhibits anomalous behaviour for other scenarios, even at low density ratios. Using a plethora of test problems of increasing complexity, we conclusively demonstrate that the
Directory of Open Access Journals (Sweden)
Hammoudi Abderazek
2015-09-01
Full Text Available Profile shift has an immense effect on the sliding, load capacity, and stability of involute cylindrical gears. Available standards such as ISO/DIS 6336 and BS 436 DIN/3990 currently give the recommendation for the selection of profile shift coefficients. It is, however, very approximate and usually given in the form of implicit graphs or charts. In this article, the optimal selection values of profile shift coefficients for cylindrical involute spur and helical gears are described, using a differential evolution algorithm. The optimization procedure is developed specifically for exact balancing specific sliding coefficients at extremes of contact path and account for gear design constraints. The obtained results are compared with those of standards and research of other authors. They demonstrate the effectiveness and robustness of the applied method. A substantial improvement in balancing specific sliding coefficients is found in this work.
The effect of load imbalances on the performance of Monte Carlo algorithms in LWR analysis
International Nuclear Information System (INIS)
Siegel, A.R.; Smith, K.; Romano, P.K.; Forget, B.; Felker, K.
2013-01-01
A model is developed to predict the impact of particle load imbalances on the performance of domain-decomposed Monte Carlo neutron transport algorithms. Expressions for upper bound performance “penalties” are derived in terms of simple machine characteristics, material characterizations and initial particle distributions. The hope is that these relations can be used to evaluate tradeoffs among different memory decomposition strategies in next generation Monte Carlo codes, and perhaps as a metric for triggering particle redistribution in production codes
An Advanced Coupled Genetic Algorithm for Identifying Unknown Moving Loads on Bridge Decks
Directory of Open Access Journals (Sweden)
Sang-Youl Lee
2014-01-01
Full Text Available This study deals with an inverse method to identify moving loads on bridge decks using the finite element method (FEM and a coupled genetic algorithm (c-GA. We developed the inverse technique using a coupled genetic algorithm that can make global solution searches possible as opposed to classical gradient-based optimization techniques. The technique described in this paper allows us to not only detect the weight of moving vehicles but also find their moving velocities. To demonstrate the feasibility of the method, the algorithm is applied to a bridge deck model with beam elements. In addition, 1D and 3D finite element models are simulated to study the influence of measurement errors and model uncertainty between numerical and real structures. The results demonstrate the excellence of the method from the standpoints of computation efficiency and avoidance of premature convergence.
Investigation of balancing problem for a planar mechanism using genetic algorithm
International Nuclear Information System (INIS)
Erkaya, Selcuk
2013-01-01
In this study, optimal balancing of a planar articulated mechanism is investigated to minimize the shaking force and moment fluctuations. Balancing of a four-bar mechanism is formulated as an optimization problem. On the other hand, an objective function based on the sub-components of shaking force and moment is constituted, and design variables consisting of kinematic and dynamic parameters are defined. Genetic algorithm is used to solve the optimization problem under the appropriate constraints. By using commercial simulation software, optimized values of design variables are also tested to evaluate the effectiveness of the proposed optimization process. This work provides a practical method for reducing the shaking force and moment fluctuations. The results show that both the structure of objective function and particularly the selection of weighting factors have a crucial role to obtain the optimum values of design parameters. By adjusting the value of weighting factor according to the relative sensitivity of the related term, there is a certain decrease at the shaking force and moment fluctuations. Moreover, these arrangements also decrease the initiative of mechanism designer on choosing the values of weighting factors.
Rodríguez, Félix R.; Barrena, Manuel
2011-07-01
The spatial indexing of eventually all the available topographic information of Earth is a highly valuable tool for different geoscientific application domains. The Shuttle Radar Topography Mission (SRTM) collected and made available to the public one of the world's largest digital elevation models (DEMs). With the aim of providing on easier and faster access to these data by improving their further analysis and processing, we have indexed the SRTM DEM by means of a spatial index based on the kd-tree data structure, called the Q-tree. This paper is the second in a two-part series that includes a thorough performance analysis to validate the bulk-load algorithm efficiency of the Q-tree. We investigate performance measuring elapsed time in different contexts, analyzing disk space usage, testing response time with typical queries, and validating the final index structure balance. In addition, the paper includes performance comparisons with Oracle 11g that helps to understand the real cost of our proposal. Our tests prove that the proposed algorithm outperforms Oracle 11g using around a 9% of the elapsed time, taking six times less storage with more than 96% of page utilization, and getting faster response times to spatial queries issued on 4.5 million points. In addition to this, the behavior of the spatial index has been successfully tested on both an open GIS (VT Builder) and a visualizer tool derived from the previous one.
International Nuclear Information System (INIS)
Gomes, Alvaro; Antunes, Carlos Henggeler; Martins, Antonio Gomes
2005-01-01
This paper aims at presenting a multiple objective model to evaluate the attractiveness of the use of demand resources (through load management control actions) by different stakeholders and in diverse structure scenarios in electricity systems. For the sake of model flexibility, the multiple (and conflicting) objective functions of technical, economical and quality of service nature are able to capture distinct market scenarios and operating entities that may be interested in promoting load management activities. The computation of compromise solutions is made by resorting to evolutionary algorithms, which are well suited to tackle multiobjective problems of combinatorial nature herein involving the identification and selection of control actions to be applied to groups of loads. (Author)
Bunnoon, Pituk; Chalermyanont, Kusumal; Limsakul, Chusak
2010-02-01
This paper proposed the discrete transform and neural network algorithms to obtain the monthly peak load demand in mid term load forecasting. The mother wavelet daubechies2 (db2) is employed to decomposed, high pass filter and low pass filter signals from the original signal before using feed forward back propagation neural network to determine the forecasting results. The historical data records in 1997-2007 of Electricity Generating Authority of Thailand (EGAT) is used as reference. In this study, historical information of peak load demand(MW), mean temperature(Tmean), consumer price index (CPI), and industrial index (economic:IDI) are used as feature inputs of the network. The experimental results show that the Mean Absolute Percentage Error (MAPE) is approximately 4.32%. This forecasting results can be used for fuel planning and unit commitment of the power system in the future.
Directory of Open Access Journals (Sweden)
Ming Yang
2018-03-01
Full Text Available In this paper, an on-line parameter identification algorithm to iteratively compute the numerical values of inertia and load torque is proposed. Since inertia and load torque are strongly coupled variables due to the degenerate-rank problem, it is hard to estimate relatively accurate values for them in the cases such as when load torque variation presents or one cannot obtain a relatively accurate priori knowledge of inertia. This paper eliminates this problem and realizes ideal online inertia identification regardless of load condition and initial error. The algorithm in this paper integrates a full-order Kalman Observer and Recursive Least Squares, and introduces adaptive controllers to enhance the robustness. It has a better performance when iteratively computing load torque and moment of inertia. Theoretical sensitivity analysis of the proposed algorithm is conducted. Compared to traditional methods, the validity of the proposed algorithm is proved by simulation and experiment results.
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Masoud Rabbani
2016-12-01
Full Text Available This paper deals with mixed model assembly line (MMAL balancing problem of type-I. In MMALs several products are made on an assembly line while the similarity of these products is so high. As a result, it is possible to assemble several types of products simultaneously without any additional setup times. The problem has some particular features such as parallel workstations and precedence constraints in dynamic periods in which each period also effects on its next period. The research intends to reduce the number of workstations and maximize the workload smoothness between workstations. Dynamic periods are used to determine all variables in different periods to achieve efficient solutions. A non-dominated sorting genetic algorithm (NSGA-II and multi-objective particle swarm optimization (MOPSO are used to solve the problem. The proposed model is validated with GAMS software for small size problem and the performance of the foregoing algorithms is compared with each other based on some comparison metrics. The NSGA-II outperforms MOPSO with respect to some comparison metrics used in this paper, but in other metrics MOPSO is better than NSGA-II. Finally, conclusion and future research is provided.
a New Graduation Algorithm for Color Balance of Remote Sensing Image
Zhou, G.; Liu, X.; Yue, T.; Wang, Q.; Sha, H.; Huang, S.; Pan, Q.
2018-05-01
In order to expand the field of view to obtain more data and information when doing research on remote sensing image, workers always need to mosaicking images together. However, the image after mosaic always has the large color differences and produces the gap line. This paper based on the graduation algorithm of tarigonometric function proposed a new algorithm of Two Quarter-rounds Curves (TQC). The paper uses the Gaussian filter to solve the program about the image color noise and the gap line. The paper used one of Greenland compiled data acquired in 1963 from Declassified Intelligence Photography Project (DISP) by ARGON KH-5 satellite, and used the photography of North Gulf, China, by Landsat satellite to experiment. The experimental results show that the proposed method has improved the accuracy of the results in two parts: on the one hand, for the large color differences remote sensing image will become more balanced. On the other hands, the remote sensing image will achieve more smooth transition.
International Nuclear Information System (INIS)
Thakur, Amit; Singh, Baltej; Gupta, Anurag; Duggal, Vibhuti; Bhatt, Kislay; Krishnani, P.D.
2016-01-01
Highlights: • EDA has been applied to optimize initial core of AHWR-LEU. • Suitable value of weighing factor ‘α’ and population size in EDA was estimated. • The effect of varying initial distribution function on optimized solution was studied. • For comparison, Genetic algorithm was also applied. - Abstract: Population based evolutionary algorithms now form an integral part of fuel management in nuclear reactors and are frequently being used for fuel loading pattern optimization (LPO) problems. In this paper we have applied Estimation of distribution algorithm (EDA) to optimize initial core loading pattern (LP) of AHWR-LEU. In EDA, new solutions are generated by sampling the probability distribution model estimated from the selected best candidate solutions. The weighing factor ‘α’ decides the fraction of current best solution for updating the probability distribution function after each generation. A wider use of EDA warrants a comprehensive study on parameters like population size, weighing factor ‘α’ and initial probability distribution function. In the present study, we have done an extensive analysis on these parameters (population size, weighing factor ‘α’ and initial probability distribution function) in EDA. It is observed that choosing a very small value of ‘α’ may limit the search of optimized solutions in the near vicinity of initial probability distribution function and better loading patterns which are away from initial distribution function may not be considered with due weightage. It is also observed that increasing the population size improves the optimized loading pattern, however the algorithm still fails if the initial distribution function is not close to the expected optimized solution. We have tried to find out the suitable values for ‘α’ and population size to be considered for AHWR-LEU initial core loading pattern optimization problem. For sake of comparison and completeness, we have also addressed the
A Secure and Stable Multicast Overlay Network with Load Balancing for Scalable IPTV Services
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Tsao-Ta Wei
2012-01-01
Full Text Available The emerging multimedia Internet application IPTV over P2P network preserves significant advantages in scalability. IPTV media content delivered in P2P networks over public Internet still preserves the issues of privacy and intellectual property rights. In this paper, we use SIP protocol to construct a secure application-layer multicast overlay network for IPTV, called SIPTVMON. SIPTVMON can secure all the IPTV media delivery paths against eavesdroppers via elliptic-curve Diffie-Hellman (ECDH key exchange on SIP signaling and AES encryption. Its load-balancing overlay tree is also optimized from peer heterogeneity and churn of peer joining and leaving to minimize both service degradation and latency. The performance results from large-scale simulations and experiments on different optimization criteria demonstrate SIPTVMON's cost effectiveness in quality of privacy protection, stability from user churn, and good perceptual quality of objective PSNR values for scalable IPTV services over Internet.
Kizilkaya, Elif A.; Gupta, Surendra M.
2005-11-01
In this paper, we compare the impact of different disassembly line balancing (DLB) algorithms on the performance of our recently introduced Dynamic Kanban System for Disassembly Line (DKSDL) to accommodate the vagaries of uncertainties associated with disassembly and remanufacturing processing. We consider a case study to illustrate the impact of various DLB algorithms on the DKSDL. The approach to the solution, scenario settings, results and the discussions of the results are included.
Acid Balance, Dietary Acid Load, and Bone Effects—A Controversial Subject
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Lynda Frassetto
2018-04-01
Full Text Available Modern Western diets, with higher contents of animal compared to fruits and vegetable products, have a greater content of acid precursors vs. base precursors, which results in a net acid load to the body. To prevent inexorable accumulation of acid in the body and progressively increasing degrees of metabolic acidosis, the body has multiple systems to buffer and titrate acid, including bone which contains large quantities of alkaline salts of calcium. Both in vitro and in vivo studies in animals and humans suggest that bone base helps neutralize part of the dietary net acid load. This raises the question of whether decades of eating a high acid diet might contribute to the loss of bone mass in osteoporosis. If this idea is true, then additional alkali ingestion in the form of net base-producing foods or alkalinizing salts could potentially prevent this acid-related loss of bone. Presently, data exists that support both the proponents as well as the opponents of this hypothesis. Recent literature reviews have tended to support either one side or the other. Assuming that the data cited by both sides is correct, we suggest a way to reconcile the discordant findings. This overview will first discuss dietary acids and bases and the idea of changes in acid balance with increasing age, then review the evidence for and against the usefulness of alkali therapy as a treatment for osteoporosis, and finally suggest a way of reconciling these two opposing points of view.
A strategy to load balancing for non-connectivity MapReduce job
Zhou, Huaping; Liu, Guangzong; Gui, Haixia
2017-09-01
MapReduce has been widely used in large scale and complex datasets as a kind of distributed programming model. Original Hash partitioning function in MapReduce often results the problem of data skew when data distribution is uneven. To solve the imbalance of data partitioning, we proposes a strategy to change the remaining partitioning index when data is skewed. In Map phase, we count the amount of data which will be distributed to each reducer, then Job Tracker monitor the global partitioning information and dynamically modify the original partitioning function according to the data skew model, so the Partitioner can change the index of these partitioning which will cause data skew to the other reducer that has less load in the next partitioning process, and can eventually balance the load of each node. Finally, we experimentally compare our method with existing methods on both synthetic and real datasets, the experimental results show our strategy can solve the problem of data skew with better stability and efficiency than Hash method and Sampling method for non-connectivity MapReduce task.
Vries, de W.; Groenenberg, J.E.; Posch, M.
2015-01-01
Critical loads of heavy metals address not only ecotoxicological effects on organisms in soils and surface waters, but also food quality in view of public health. A critical load for metals is the load resulting at steady state in a metal concentration in a compartment (e.g. soil solution, surface
Advanced and flexible genetic algorithms for BWR fuel loading pattern optimization
International Nuclear Information System (INIS)
Martin-del-Campo, Cecilia; Palomera-Perez, Miguel-Angel; Francois, Juan-Luis
2009-01-01
This work proposes advances in the implementation of a flexible genetic algorithm (GA) for fuel loading pattern optimization for Boiling Water Reactors (BWRs). In order to avoid specific implementations of genetic operators and to obtain a more flexible treatment, a binary representation of the solution was implemented; this representation had to take into account that a little change in the genotype must correspond to a little change in the phenotype. An identifier number is assigned to each assembly by means of a Gray Code of 7 bits and the solution (the loading pattern) is represented by a binary chain of 777 bits of length. Another important contribution is the use of a Fitness Function which includes a Heuristic Function and an Objective Function. The Heuristic Function which is defined to give flexibility on the application of a set of positioning rules based on knowledge, and the Objective Function that contains all the parameters which qualify the neutronic and thermal hydraulic performances of each loading pattern. Experimental results illustrating the effectiveness and flexibility of this optimization algorithm are presented and discussed.
An Efficient Meta Heuristic Algorithm to Solve Economic Load Dispatch Problems
Directory of Open Access Journals (Sweden)
R Subramanian
2013-12-01
Full Text Available The Economic Load Dispatch (ELD problems in power generation systems are to reduce the fuel cost by reducing the total cost for the generation of electric power. This paper presents an efficient Modified Firefly Algorithm (MFA, for solving ELD Problem. The main objective of the problems is to minimize the total fuel cost of the generating units having quadratic cost functions subjected to limits on generator true power output and transmission losses. The MFA is a stochastic, Meta heuristic approach based on the idealized behaviour of the flashing characteristics of fireflies. This paper presents an application of MFA to ELD for six generator test case system. MFA is applied to ELD problem and compared its solution quality and computation efficiency to Genetic algorithm (GA, Differential Evolution (DE, Particle swarm optimization (PSO, Artificial Bee Colony optimization (ABC, Biogeography-Based Optimization (BBO, Bacterial Foraging optimization (BFO, Firefly Algorithm (FA techniques. The simulation result shows that the proposed algorithm outperforms previous optimization methods.
Comparison between dynamic programming and genetic algorithm for hydro unit economic load dispatch
Directory of Open Access Journals (Sweden)
Bin Xu
2014-10-01
Full Text Available The hydro unit economic load dispatch (ELD is of great importance in energy conservation and emission reduction. Dynamic programming (DP and genetic algorithm (GA are two representative algorithms for solving ELD problems. The goal of this study was to examine the performance of DP and GA while they were applied to ELD. We established numerical experiments to conduct performance comparisons between DP and GA with two given schemes. The schemes included comparing the CPU time of the algorithms when they had the same solution quality, and comparing the solution quality when they had the same CPU time. The numerical experiments were applied to the Three Gorges Reservoir in China, which is equipped with 26 hydro generation units. We found the relation between the performance of algorithms and the number of units through experiments. Results show that GA is adept at searching for optimal solutions in low-dimensional cases. In some cases, such as with a number of units of less than 10, GA's performance is superior to that of a coarse-grid DP. However, GA loses its superiority in high-dimensional cases. DP is powerful in obtaining stable and high-quality solutions. Its performance can be maintained even while searching over a large solution space. Nevertheless, due to its exhaustive enumerating nature, it costs excess time in low-dimensional cases.
Modification of the algorithm for steam turbine control under loading drop
International Nuclear Information System (INIS)
Nikitin, Yu.V.; Mirnyj, V.A.; Gritsenko, V.N.; Nesterov, L.V.
1989-01-01
Problem related to powerful steam turbine control in case of emergency loading drop is considered. Two laws of control creating conditions for qualitative operation of control system under conditions considered are compared. The system of turbine control comprises the turbine major actuating mechanisms (electrohydraulic transducer, high-pressure servomotor, cut-off slide valve) actuating mechanisms of pulse discharge channel (low-pressure servomotor cut-off slide valve, low-pressure servomotor) and regulator. The frequency of the turbine rotor rotation is the parameter to be controlled in the mode of loading drop. The algorithms considered are based on linear variant of the optimal control theory. One of them is realized in electrohydraulic system of the K-750-65/3000 turbine control at the Ignalinsk NPP
Automatic provisioning, deployment and orchestration for load-balancing THREDDS instances
Cofino, A. S.; Fernández-Tejería, S.; Kershaw, P.; Cimadevilla, E.; Petri, R.; Pryor, M.; Stephens, A.; Herrera, S.
2017-12-01
THREDDS is a widely used web server to provide to different scientific communities with data access and discovery. Due to THREDDS's lack of horizontal scalability and automatic configuration management and deployment, this service usually deals with service downtimes and time consuming configuration tasks, mainly when an intensive use is done as is usual within the scientific community (e.g. climate). Instead of the typical installation and configuration of a single or multiple independent THREDDS servers, manually configured, this work presents an automatic provisioning, deployment and orchestration cluster of THREDDS servers. This solution it's based on Ansible playbooks, used to control automatically the deployment and configuration setup on a infrastructure and to manage the datasets available in THREDDS instances. The playbooks are based on modules (or roles) of different backends and frontends load-balancing setups and solutions. The frontend load-balancing system enables horizontal scalability by delegating requests to backend workers, consisting in a variable number of instances for the THREDDS server. This implementation allows to configure different infrastructure and deployment scenario setups, as more workers are easily added to the cluster by simply declaring them as Ansible variables and executing the playbooks, and also provides fault-tolerance and better reliability since if any of the workers fail another instance of the cluster can take over it. In order to test the solution proposed, two real scenarios are analyzed in this contribution: The JASMIN Group Workspaces at CEDA and the User Data Gateway (UDG) at the Data Climate Service from the University of Cantabria. On the one hand, the proposed configuration has provided CEDA with a higher level and more scalable Group Workspaces (GWS) service than the previous one based on Unix permissions, improving also the data discovery and data access experience. On the other hand, the UDG has improved its
Discrete PSO algorithm based optimization of transmission lines loading in TNEP problem
International Nuclear Information System (INIS)
Shayeghi, H.; Mahdavi, M.; Bagheri, A.
2010-01-01
Transmission network expansion planning (TNEP) is a basic part of power system planning that determines where, when and how many new transmission lines should be added to the network. Up till now, various methods have been presented to solve the static transmission network expansion planning (STNEP) problem. But in all of these methods, lines adequacy rate has not been considered at the end of planning horizon, i.e. expanded network misses adequacy after some times and needs to be expanded again. In this paper, expansion planning has been implemented by merging lines loading parameter in the STNEP and inserting investment cost into the fitness function constraints using discrete particle swarm optimization (DPSO) algorithm. Expanded network will possess a maximum adequacy to provide load demand and also the transmission lines overloaded later. The proposed idea has been tested on the Garvers network and an actual transmission network of the Azerbaijan regional electric company, Iran, and the results are compared with the decimal codification genetic algorithm (DCGA) technique. The results evaluation shows that the network will possess maximum efficiency economically. Also, it is shown that precision and convergence speed of the proposed DPSO based method for the solution of the STNEP problem is superior to DCGA approach.
Automatic boiling water reactor loading pattern design using ant colony optimization algorithm
Energy Technology Data Exchange (ETDEWEB)
Wang, C.-D. [Department of Engineering and System Science, National Tsing Hua University, 101, Section 2 Kuang Fu Road, Hsinchu 30013, Taiwan (China); Nuclear Engineering Division, Institute of Nuclear Energy Research, No. 1000, Wenhua Rd., Jiaan Village, Longtan Township, Taoyuan County 32546, Taiwan (China)], E-mail: jdwang@iner.gov.tw; Lin Chaung [Department of Engineering and System Science, National Tsing Hua University, 101, Section 2 Kuang Fu Road, Hsinchu 30013, Taiwan (China)
2009-08-15
An automatic boiling water reactor (BWR) loading pattern (LP) design methodology was developed using the rank-based ant system (RAS), which is a variant of the ant colony optimization (ACO) algorithm. To reduce design complexity, only the fuel assemblies (FAs) of one eight-core positions were determined using the RAS algorithm, and then the corresponding FAs were loaded into the other parts of the core. Heuristic information was adopted to exclude the selection of the inappropriate FAs which will reduce search space, and thus, the computation time. When the LP was determined, Haling cycle length, beginning of cycle (BOC) shutdown margin (SDM), and Haling end of cycle (EOC) maximum fraction of limit for critical power ratio (MFLCPR) were calculated using SIMULATE-3 code, which were used to evaluate the LP for updating pheromone of RAS. The developed design methodology was demonstrated using FAs of a reference cycle of the BWR6 nuclear power plant. The results show that, the designed LP can be obtained within reasonable computation time, and has a longer cycle length than that of the original design.
SPORT: An Algorithm for Divisible Load Scheduling with Result Collection on Heterogeneous Systems
Ghatpande, Abhay; Nakazato, Hidenori; Beaumont, Olivier; Watanabe, Hiroshi
Divisible Load Theory (DLT) is an established mathematical framework to study Divisible Load Scheduling (DLS). However, traditional DLT does not address the scheduling of results back to source (i. e., result collection), nor does it comprehensively deal with system heterogeneity. In this paper, the DLSRCHETS (DLS with Result Collection on HET-erogeneous Systems) problem is addressed. The few papers to date that have dealt with DLSRCHETS, proposed simplistic LIFO (Last In, First Out) and FIFO (First In, First Out) type of schedules as solutions to DLSRCHETS. In this paper, a new polynomial time heuristic algorithm, SPORT (System Parameters based Optimized Result Transfer), is proposed as a solution to the DLSRCHETS problem. With the help of simulations, it is proved that the performance of SPORT is significantly better than existing algorithms. The other major contributions of this paper include, for the first time ever, (a) the derivation of the condition to identify the presence of idle time in a FIFO schedule for two processors, (b) the identification of the limiting condition for the optimality of FIFO and LIFO schedules for two processors, and (c) the introduction of the concept of equivalent processor in DLS for heterogeneous systems with result collection.
The effects of cognitive loading on balance control in patients with multiple sclerosis.
Negahban, Hossein; Mofateh, Razieh; Arastoo, Ali Asghar; Mazaheri, Masood; Yazdi, Mohammad Jafar Shaterzadeh; Salavati, Mahyar; Majdinasab, Nastaran
2011-10-01
The aim of this study was to compare the effects of concurrent cognitive task (silent backward counting) on balance performance between two groups of multiple sclerosis (MS) (n=23) and healthy (n=23) participates. Three levels of postural difficulty were studied on a force platform, i.e. rigid surface with eyes open, rigid surface with eyes closed, and foam surface with eyes closed. A mixed model analysis of variance showed that under difficult sensory condition of foam surface with eyes closed, execution of concurrent cognitive task caused a significant decrement in variability of sway velocity in anteroposterior direction for the patient group (P<0.01) while this was not the case for healthy participants (P=0.22). Also, the variability of sway velocity in mediolateral direction was significantly decreased during concurrent execution of cognitive task in patient group (P<0.01) and not in healthy participants (P=0.39). Furthermore, in contrast to single tasking, dual tasking had the ability to discriminate between the 2 groups in all conditions of postural difficulty. In conclusion, findings of variability in sway velocity seem to confirm the different response to cognitive loading between two groups of MS and healthy participants. Copyright © 2011 Elsevier B.V. All rights reserved.
A balancing act of the brain: activations and deactivations driven by cognitive load.
Arsalidou, Marie; Pascual-Leone, Juan; Johnson, Janice; Morris, Drew; Taylor, Margot J
2013-05-01
The majority of neuroimaging studies focus on brain activity during performance of cognitive tasks; however, some studies focus on brain areas that activate in the absence of a task. Despite the surge of research comparing these contrasted areas of brain function, their interrelation is not well understood. We systematically manipulated cognitive load in a working memory task to examine concurrently the relation between activity elicited by the task versus activity during control conditions. We presented adults with six levels of task demand, and compared those with three conditions without a task. Using whole-brain analysis, we found positive linear relations between cortical activity and task difficulty in areas including middle frontal gyrus and dorsal cingulate; negative linear relations were found in medial frontal gyrus and posterior cingulate. These findings demonstrated balancing of activation patterns between two mental processes, which were both modulated by task difficulty. Frontal areas followed a graded pattern more closely than other regions. These data also showed that working memory has limited capacity in adults: an upper bound of seven items and a lower bound of four items. Overall, working memory and default-mode processes, when studied concurrently, reveal mutually competing activation patterns.
CAC DPLB MCN: A Distributed Load Balancing Scheme in Multimedia Mobile Cellular Networks
Directory of Open Access Journals (Sweden)
Sharma Abhijit
2016-11-01
Full Text Available The problem of non-uniform traffic demand in different cells of a cellular network may lead to a gross imbalance in the system performance. Thus, the users in hot cells may suffer from low throughput. In this paper, an effective and simple load balancing scheme CAC_DPLB_MCN is proposed that can effectively reduce the overall call blocking. This model considers dealing with multi-media traffic as well as time-varying geographical traffic distribution. The proposed scheme uses the concept of cell-tiering thereby creating fractional frequency reuse environment. A message exchange based distributed scheme instead of centralized one is used which help the proposed scheme be implemented in a multiple hot cell environment also. Furthermore, concept of dynamic pricing is used to serve the best interest of the users as well as for the service providers. The performance of the proposed scheme is compared with two other existing schemes in terms of call blocking probability and bandwidth utilization. Simulation results show that the proposed scheme can reduce the call blocking significantly in highly congested cell with highest bandwidth utilization. Use of dynamic pricing also makes the scheme useful to increase revenue of the service providers in contrast with compared schemes.
UE-Initiated Cell Reselection Game for Cell Load Balancing in a Wireless Network
Directory of Open Access Journals (Sweden)
Jaesung Park
2018-01-01
Full Text Available A user changes its serving cell if the quality of experience (QoE provided by the current serving cell is not satisfactory. Since users reselect cells to increase their QoEs selfishly, the system resource efficiency can be deteriorated and a system can be unstable if users are not driven to cooperate appropriately. In this paper, inspired by the minority game (MG model, we design a UE-initiated cell reselection policy. The MG has a salient characteristic that the number of players who win the game converges to a prespecified value even though players act selfishly without knowing the actions taken by the other players. Using the MG model, we devise a rule by which each UE plays a cell reselection game. We also design a criterion that a system controller uses to determine the result of a game and public information sent by a system controller to induce implicit cooperation among UEs. The simulation results show that compared with noncooperative method the proposed method increases not only the system performance, such as cell load balance index and system utility, but also the performance of UEs in terms of a downlink data rate and an outage probability received from a system.
Interference of Heavy Aerosol Loading on the VIIRS Aerosol Optical Depth (AOD Retrieval Algorithm
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Yang Wang
2017-04-01
Full Text Available Aerosol optical depth (AOD has been widely used in climate research, atmospheric environmental observations, and other applications. However, high AOD retrieval remains challenging over heavily polluted regions, such as the North China Plain (NCP. The Visible Infrared Imaging Radiometer Suite (VIIRS, which was designed as a successor to the Moderate Resolution Imaging Spectroradiometer (MODIS, will undertake the aerosol observations mission in the coming years. Using the VIIRS AOD retrieval algorithm as an example, we analyzed the influence of heavy aerosol loading through the 6SV radiative transfer model (RTM with a focus on three aspects: cloud masking, ephemeral water body tests, and data quality estimation. First, certain pixels were mistakenly screened out as clouds and ephemeral water bodies because of heavy aerosols, resulting in the loss of AOD retrievals. Second, the greenness of the surface could not be accurately identified by the top of atmosphere (TOA index, and the quality of the aggregation data may be artificially high. Thus, the AOD retrieval algorithm did not perform satisfactorily, indicated by the low availability of data coverage (at least 37.97% of all data records were missing according to ground-based observations and overestimation of the data quality (high-quality data increased from 63.42% to 80.97% according to radiative simulations. To resolve these problems, the implementation of a spatial variability cloud mask method and surficial index are suggested in order to improve the algorithm.
International Nuclear Information System (INIS)
Shayeghi, H.; Mahdavi, M.; Bagheri, A.
2010-01-01
Static transmission network expansion planning (STNEP) problem acquires a principal role in power system planning and should be evaluated carefully. Up till now, various methods have been presented to solve the STNEP problem. But only in one of them, lines adequacy rate has been considered at the end of planning horizon and the problem has been optimized by discrete particle swarm optimization (DPSO). DPSO is a new population-based intelligence algorithm and exhibits good performance on solution of the large-scale, discrete and non-linear optimization problems like STNEP. However, during the running of the algorithm, the particles become more and more similar, and cluster into the best particle in the swarm, which make the swarm premature convergence around the local solution. In order to overcome these drawbacks and considering lines adequacy rate, in this paper, expansion planning has been implemented by merging lines loading parameter in the STNEP and inserting investment cost into the fitness function constraints using an improved DPSO algorithm. The proposed improved DPSO is a new conception, collectivity, which is based on similarity between the particle and the current global best particle in the swarm that can prevent the premature convergence of DPSO around the local solution. The proposed method has been tested on the Garver's network and a real transmission network in Iran, and compared with the DPSO based method for solution of the TNEP problem. The results show that the proposed improved DPSO based method by preventing the premature convergence is caused that with almost the same expansion costs, the network adequacy is increased considerably. Also, regarding the convergence curves of both methods, it can be seen that precision of the proposed algorithm for the solution of the STNEP problem is more than DPSO approach.
Energy Technology Data Exchange (ETDEWEB)
He, Fulin; Cao, Yang; Zhang, Jun Jason; Wei, Jiaolong; Zhang, Yingchen; Muljadi, Eduard; Gao, Wenzhong
2016-11-21
Ensuring flexible and reliable data routing is indispensable for the integration of Advanced Metering Infrastructure (AMI) networks, we propose a secure-oriented and load-balancing wireless data routing scheme. A novel utility function is designed based on security routing scheme. Then, we model the interactive security-oriented routing strategy among meter data concentrators or smart grid meters as a mixed-strategy network formation game. Finally, such problem results in a stable probabilistic routing scheme with proposed distributed learning algorithm. One contributions is that we studied that different types of applications affect the routing selection strategy and the strategy tendency. Another contributions is that the chosen strategy of our mixed routing can adaptively to converge to a new mixed strategy Nash equilibrium (MSNE) during the learning process in the smart grid.
Directory of Open Access Journals (Sweden)
Ashutosh K. AGARWAL
2011-10-01
Full Text Available Genetic algorithms are robust search techniques based on the principles of evolution. A genetic algorithm maintains a population of encoded solutions and guides the population towards the optimum solution. This important property of genetic algorithm is used in this paper to stabilize the Inverted pendulum system. This paper highlights the application and stability of inverted pendulum using PID controller with fuzzy logic genetic algorithm supervisor . There are a large number of well established search techniques in use within the information technology industry. We propose a method to control inverted pendulum steady state error and overshoot using genetic algorithm technique.
Esin, S. B.; Trifonov, N. N.; Sukhorukov, Yu. G.; Yurchenko, A. Yu.; Grigor'eva, E. B.; Snegin, I. P.; Zhivykh, D. A.; Medvedkin, A. V.; Ryabich, V. A.
2015-09-01
More than 30 power units of thermal power stations, based on the nondeaerating heat balance diagram, successfully operate in the former Soviet Union. Most of them are power units with a power of 300 MW, equipped with HTGZ and LMZ turbines. They operate according to a variable electric load curve characterized by deep reductions when undergoing night minimums. Additional extension of the range of power unit adjustment makes it possible to maintain the dispatch load curve and obtain profit for the electric power plant. The objective of this research is to carry out estimated and experimental processing of the operating regimes of the regeneration system of steam-turbine plants within the extended adjustment range and under the conditions when the constraints on the regeneration system and its equipment are removed. Constraints concerning the heat balance diagram that reduce the power unit efficiency when extending the adjustment range have been considered. Test results are presented for the nondeaerating heat balance diagram with the HTGZ turbine. Turbine pump and feed electric pump operation was studied at a power unit load of 120-300 MW. The reliability of feed pump operation is confirmed by a stable vibratory condition and the absence of cavitation noise and vibration at a frequency that characterizes the cavitation condition, as well as by oil temperature maintenance after bearings within normal limits. Cavitation performance of pumps in the studied range of their operation has been determined. Technical solutions are proposed on providing a profitable and stable operation of regeneration systems when extending the range of adjustment of power unit load. A nondeaerating diagram of high-pressure preheater (HPP) condensate discharge to the mixer. A regeneration system has been developed and studied on the operating power unit fitted with a deaeratorless thermal circuit of the system for removing the high-pressure preheater heating steam condensate to the mixer
Directory of Open Access Journals (Sweden)
K. Roshangar
2016-09-01
Full Text Available Introduction: Exact prediction of transported sediment rate by rivers in water resources projects is of utmost importance. Basically erosion and sediment transport process is one of the most complexes hydrodynamic. Although different studies have been developed on the application of intelligent models based on neural, they are not widely used because of lacking explicitness and complexity governing on choosing and architecting of proper network. In this study, a Genetic expression programming model (as an important branches of evolutionary algorithems for predicting of sediment load is selected and investigated as an intelligent approach along with other known classical and imperical methods such as Larsen´s equation, Engelund-Hansen´s equation and Bagnold´s equation. Materials and Methods: In this study, in order to improve explicit prediction of sediment load of Gotoorchay, located in Aras catchment, Northwestern Iran latitude: 38°24´33.3˝ and longitude: 44°46´13.2˝, genetic programming (GP and Genetic Algorithm (GA were applied. Moreover, the semi-empirical models for predicting of total sediment load and rating curve have been used. Finally all the methods were compared and the best ones were introduced. Two statistical measures were used to compare the performance of the different models, namely root mean square error (RMSE and determination coefficient (DC. RMSE and DC indicate the discrepancy between the observed and computed values. Results and Discussions: The statistical characteristics results obtained from the analysis of genetic programming method for both selected model groups indicated that the model 4 including the only discharge of the river, relative to other studied models had the highest DC and the least RMSE in the testing stage (DC= 0.907, RMSE= 0.067. Although there were several parameters applied in other models, these models were complicated and had weak results of prediction. Our results showed that the model 9
Modified Cuckoo Search Algorithm for Solving Nonconvex Economic Load Dispatch Problems
Directory of Open Access Journals (Sweden)
Thang Trung Nguyen
2016-01-01
Full Text Available This paper presents the application of modified cuckoo search algorithm (MCSA for solving economic load dispatch (ELD problems. The MCSA method is developed to improve the search ability and solution quality of the conventional CSA method. In the MCSA, the evaluation of eggs has divided the initial eggs into two groups, the top egg group with good quality and the abandoned group with worse quality. Moreover, the value of the updated step size in MCSA is adapted as generating a new solution for the abandoned group and the top group via the Levy flights so that a large zone is searched at the beginning and a local zone is foraged as the maximum number of iterations is nearly reached. The MCSA method has been tested on different systems with different characteristics of thermal units and constraints. The result comparison with other methods in the literature has indicated that the MCSA method can be a powerful method for solving the ELD.
Koloch, Grzegorz; Kaminski, Bogumil
2010-10-01
In the paper we examine a modification of the classical Vehicle Routing Problem (VRP) in which shapes of transported cargo are accounted for. This problem, known as a three-dimensional VRP with loading constraints (3D-VRP), is appropriate when transported commodities are not perfectly divisible, but they have fixed and heterogeneous dimensions. In the paper restrictions on allowable cargo positionings are also considered. These restrictions are derived from business practice and they extended the baseline 3D-VRP formulation as considered by Koloch and Kaminski (2010). In particular, we investigate how additional restrictions influence relative performance of two proposed optimization algorithms: the nested and the joint one. Performance of both methods is compared on artificial problems and on a big-scale real life case study.
Algorithms for balancing demand-side load and micro-generation in Islanded Operation
Molderink, Albert; Bakker, Vincent; Hurink, Johann L.; Smit, Gerardus Johannes Maria
2008-01-01
Micro-generators are devices installed in houses pro- ducing electricity at kilowatt level. These appliances can increase energy ef��?ciency signi��?cantly, especially when their runtime is optimized. During power outages micro- generators can supply critical systems and decrease dis- comfort. In
Optimization of Boiling Water Reactor Loading Pattern Using Two-Stage Genetic Algorithm
International Nuclear Information System (INIS)
Kobayashi, Yoko; Aiyoshi, Eitaro
2002-01-01
A new two-stage optimization method based on genetic algorithms (GAs) using an if-then heuristic rule was developed to generate optimized boiling water reactor (BWR) loading patterns (LPs). In the first stage, the LP is optimized using an improved GA operator. In the second stage, an exposure-dependent control rod pattern (CRP) is sought using GA with an if-then heuristic rule. The procedure of the improved GA is based on deterministic operators that consist of crossover, mutation, and selection. The handling of the encoding technique and constraint conditions by that GA reflects the peculiar characteristics of the BWR. In addition, strategies such as elitism and self-reproduction are effectively used in order to improve the search speed. The LP evaluations were performed with a three-dimensional diffusion code that coupled neutronic and thermal-hydraulic models. Strong axial heterogeneities and constraints dependent on three dimensions have always necessitated the use of three-dimensional core simulators for BWRs, so that optimization of computational efficiency is required. The proposed algorithm is demonstrated by successfully generating LPs for an actual BWR plant in two phases. One phase is only LP optimization applying the Haling technique. The other phase is an LP optimization that considers the CRP during reactor operation. In test calculations, candidates that shuffled fresh and burned fuel assemblies within a reasonable computation time were obtained
Energy Technology Data Exchange (ETDEWEB)
Dall-Anese, Emiliano [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhou, Xinyang [University of Colorado; Liu, Zhiyuan [University of Colorado; Chen, Lijun [University of Colorado
2017-10-03
This paper considers distribution networks with distributed energy resources and discrete-rate loads, and designs an incentive-based algorithm that allows the network operator and the customers to pursue given operational and economic objectives, while concurrently ensuring that voltages are within prescribed limits. Four major challenges include: (1) the non-convexity from discrete decision variables, (2) the non-convexity due to a Stackelberg game structure, (3) unavailable private information from customers, and (4) different update frequency from two types of devices. In this paper, we first make convex relaxation for discrete variables, then reformulate the non-convex structure into a convex optimization problem together with pricing/reward signal design, and propose a distributed stochastic dual algorithm for solving the reformulated problem while restoring feasible power rates for discrete devices. By doing so, we are able to statistically achieve the solution of the reformulated problem without exposure of any private information from customers. Stability of the proposed schemes is analytically established and numerically corroborated.
A Power Load Distribution Algorithm to Optimize Data Center Electrical Flow
Directory of Open Access Journals (Sweden)
Paulo Maciel
2013-07-01
Full Text Available Energy consumption is a matter of common concern in the world today. Research demonstrates that as a consequence of the constantly evolving and expanding field of information technology, data centers are now major consumers of electrical energy. Such high electrical energy consumption emphasizes the issues of sustainability and cost. Against this background, the present paper proposes a power load distribution algorithm (PLDA to optimize energy distribution of data center power infrastructures. The PLDA, which is based on the Ford-Fulkerson algorithm, is supported by an environment called ASTRO, capable of performing the integrated evaluation of dependability, cost and sustainability. More specifically, the PLDA optimizes the flow distribution of the energy flow model (EFM. EFMs are responsible for estimating sustainability and cost issues of data center infrastructures without crossing the restrictions of the power capacity that each device can provide (power system or extract (cooling system. Additionally, a case study is presented that analyzed seven data center power architectures. Significant results were observed, achieving a reduction in power consumption of up to 15.5%.
An IPv6 routing lookup algorithm using weight-balanced tree based on prefix value for virtual router
Chen, Lingjiang; Zhou, Shuguang; Zhang, Qiaoduo; Li, Fenghua
2016-10-01
Virtual router enables the coexistence of different networks on the same physical facility and has lately attracted a great deal of attention from researchers. As the number of IPv6 addresses is rapidly increasing in virtual routers, designing an efficient IPv6 routing lookup algorithm is of great importance. In this paper, we present an IPv6 lookup algorithm called weight-balanced tree (WBT). WBT merges Forwarding Information Bases (FIBs) of virtual routers into one spanning tree, and compresses the space cost. WBT's average time complexity and the worst case time complexity of lookup and update process are both O(logN) and space complexity is O(cN) where N is the size of routing table and c is a constant. Experiments show that WBT helps reduce more than 80% Static Random Access Memory (SRAM) cost in comparison to those separation schemes. WBT also achieves the least average search depth comparing with other homogeneous algorithms.
DEFF Research Database (Denmark)
Sangwongwanich, Ariya; Máthé, Lászlo; Teodorescu, Remus
2016-01-01
With the aim to solve the unbalanced thermal behavior in the modular multilevel converter, introduced by mismatch in the submodule parameters, a thermal balancing control strategy is proposed here. The proposed solution ensures a balanced junction temperature for the power devices, while the bala...
Thiruvenkadam, T; Karthikeyani, V
2014-01-01
Mapping the virtual machines to the physical machines cluster is called the VM placement. Placing the VM in the appropriate host is necessary for ensuring the effective resource utilization and minimizing the datacenter cost as well as power. Here we present an efficient hybrid genetic based host load aware algorithm for scheduling and optimization of virtual machines in a cluster of Physical hosts. We developed the algorithm based on two different methods, first initial VM packing is done by...
Indian Academy of Sciences (India)
polynomial) division have been found in Vedic Mathematics which are dated much before Euclid's algorithm. A programming language Is used to describe an algorithm for execution on a computer. An algorithm expressed using a programming.
Cache-aware data structure model for parallelism and dynamic load balancing
International Nuclear Information System (INIS)
Sridi, Marwa
2016-01-01
for parallel processing where groups are distributed on available cores and a group size ensuring the complete filling of the private cache memories (i.e. L2 level). The strategy logically suggests the experimentation of a two levels parallel solution for nodes composed of several multi-core processors: one group is thus attached to one processor and an inner parallel loop is used inside the group based on the internal cores of the processor. This latter approach still requires consolidation to avoid contention upon the internal processor memory due to coherency enforcement between the different private cache memories. It is noticeable that the best performances are obtained through load balancing based on a dynamic scheduling approach with work stealing, achieved via the XKAAPI library (INRIA). (author) [fr
Heuristic rules embedded genetic algorithm to solve VVER loading pattern optimization problem
International Nuclear Information System (INIS)
Fatih, Alim; Kostandi, Ivanov
2006-01-01
Full text: Loading Pattern (LP) optimization is one of the most important aspects of the operation of nuclear reactors. A genetic algorithm (GA) code GARCO (Genetic Algorithm Reactor Optimization Code) has been developed with embedded heuristic techniques to perform optimization calculations for in-core fuel management tasks. GARCO is a practical tool that includes a unique methodology applicable for all types of Pressurized Water Reactor (PWR) cores having different geometries with an unlimited number of FA types in the inventory. GARCO was developed by modifying the classical representation of the genotype. Both the genotype representation and the basic algorithm have been modified to incorporate the in-core fuel management heuristics rules so as to obtain the best results in a shorter time. GARCO has three modes. Mode 1 optimizes the locations of the fuel assemblies (FAs) in the nuclear reactor core, Mode 2 optimizes the placement of the burnable poisons (BPs) in a selected LP, and Mode 3 optimizes simultaneously both the LP and the BP placement in the core. This study describes the basic algorithm for Mode 1. The GARCO code is applied to the VVER-1000 reactor hexagonal geometry core in this study. The M oby-Dick i s used as reactor physics code to deplete FAs in the core. It was developed to analyze the VVER reactors by SKODA Inc. To use these rules for creating the initial population with GA operators, the worth definition application is developed. Each FA has a worth value for each location. This worth is between 0 and 1. If worth of any FA for a location is larger than 0.5, this FA in this location is a good choice. When creating the initial population of LPs, a subroutine provides a percent of individuals, which have genes with higher than the 0.5 worth. The percentage of the population to be created without using worth definition is defined in the GARCO input. And also age concept has been developed to accelerate the GA calculation process in reaching the
Estimating sediment loads in an intra-Apennine catchments: balance between modeling and monitoring
Pelacani, Samanta; Cassi, Paola; Borselli, Lorenzo
2010-05-01
In this study we compare the results of a soil erosion model applied at watershed scale to the suspended sediment measured in the stream network affected by a motor way construction. A sediment delivery model is applied at watershed scale; the evaluation of sediment delivery is related to a connectivity fluxes index that describes the internal linkages between runoff and sediment sources in upper parts of catchments and the receiving sinks. An analysis of the fine suspended sediment transport and storage was conducted for a streams inlet of the Bilancino reservoir, a principal water supply of the city of Florence. The suspended sediment were collected from a section of river defined as a close systems using a time integrating suspended sediment sampling. The sediment deposited within the sampling traps was recovered after storm events and provide information of the overall contribution of the potential sediment sources. Hillslope gross erosion was assessed by a USLE-TYPE approach. A soil survey at 1:25.000 scale and a soil database was create to calculate, for each soil unit, the erodibility coefficient K using a new algorithm (Salvador Sanchis et al. 2007). Erosivity coefficient R was obtained applying geostatistical methods taking into account elevation and valley morphology. Furthermore, we evaluate a sediment delivery factor (SDR) for the entire watershed. This factor is used to correct the output of the USLE Type model. The innovative approach consist in a SDR factor variable in space and in time because it is related to a fluxes connectivity index IC (Borselli et al. 2008) based on the distribution of land use and topographic features. The aim of this study is to understand how the model simulates the real processes that intervene in the watershed and subsequently to calibrate the model with the result obtained from the monitoring of suspend sediment in the streams. From first results, it appears that human activities by highway construction, have resulted in
Battery pack state of charge balancing algorithm for cascaded H-Bridge multilevel converters
DEFF Research Database (Denmark)
Máthé, Lászlo; Burlacu, Paul Dan; Schaltz, Erik
2016-01-01
For most of the Multilevel Converter (MC) applications a commonly discussed issue is the maintenance of balance between the energy storage elements from the SubModules (SM). In applications where a battery pack is also part of the SM storage, such as STATCOMs or motor drives, the SM voltage...... is not in linear relation with the State Of Charge (SOC) of the entire battery; thus, the balancing becomes more cumbersome. A method to balance the SOC of the battery packs in a system using cascaded H-Bridge is proposed in this paper. The method uses nearest level control followed by sorting and selection based...... on the SOC of the battery packs. Based on the simulation results the number of switching is reduced considerably compared to the method where the phase shifted PWM is used. In addition, the time needed to achieve the balanced SOC is also reduced. The proposed method has been verified through experiments...
Wu, Junfeng; Dai, Fang; Hu, Gang; Mou, Xuanqin
2018-04-18
Excessive radiation exposure in computed tomography (CT) scans increases the chance of developing cancer and has become a major clinical concern. Recently, statistical iterative reconstruction (SIR) with l0-norm dictionary learning regularization has been developed to reconstruct CT images from the low dose and few-view dataset in order to reduce radiation dose. Nonetheless, the sparse regularization term adopted in this approach is l0-norm, which cannot guarantee the global convergence of the proposed algorithm. To address this problem, in this study we introduced the l1-norm dictionary learning penalty into SIR framework for low dose CT image reconstruction, and developed an alternating minimization algorithm to minimize the associated objective function, which transforms CT image reconstruction problem into a sparse coding subproblem and an image updating subproblem. During the image updating process, an efficient model function approach based on balancing principle is applied to choose the regularization parameters. The proposed alternating minimization algorithm was evaluated first using real projection data of a sheep lung CT perfusion and then using numerical simulation based on sheep lung CT image and chest image. Both visual assessment and quantitative comparison using terms of root mean square error (RMSE) and structural similarity (SSIM) index demonstrated that the new image reconstruction algorithm yielded similar performance with l0-norm dictionary learning penalty and outperformed the conventional filtered backprojection (FBP) and total variation (TV) minimization algorithms.
Multi-Stage Admission Control for Load Balancing in Next Generation Systems
DEFF Research Database (Denmark)
Mihovska, Albena D.; Anggorojati, Bayu; Luo, Jijun
2008-01-01
This paper describes a load-dependent multi-stage admission control suitable for next generation systems. The concept uses decision polling in entities located at different levels of the architecture hierarchy and based on the load to activate a sequence of actions related to the admission...
International Nuclear Information System (INIS)
Braumann, Andreas; Kraft, Markus; Wagner, Wolfgang
2010-01-01
This paper is concerned with computational aspects of a multidimensional population balance model of a wet granulation process. Wet granulation is a manufacturing method to form composite particles, granules, from small particles and binders. A detailed numerical study of a stochastic particle algorithm for the solution of a five-dimensional population balance model for wet granulation is presented. Each particle consists of two types of solids (containing pores) and of external and internal liquid (located in the pores). Several transformations of particles are considered, including coalescence, compaction and breakage. A convergence study is performed with respect to the parameter that determines the number of numerical particles. Averaged properties of the system are computed. In addition, the ensemble is subdivided into practically relevant size classes and analysed with respect to the amount of mass and the particle porosity in each class. These results illustrate the importance of the multidimensional approach. Finally, the kinetic equation corresponding to the stochastic model is discussed.
DEFF Research Database (Denmark)
Guan, Yajuan; Meng, Lexuan; Li, Chendan
2018-01-01
A dynamic consensus algorithm (DCA)-based coordinated secondary control with an autonomous current-sharing control strategy is proposed in this paper for balancing the discharge rate of energy storage systems (ESSs) in an islanded AC microgrid. The DCA is applied for information sharing between......, the proposed approach can provide higher system reliability, expandability, and flexibility due to its distributed control architecture. The proposed controller can effectively prevent operation failure caused by over-current and unintentional outage of DGs by means of balanced discharge rate control. It can...... also provide fast response and accurate current sharing performance. A generalizable linearized state-space model for n-DG network in the z-domain is also derived and proposed in this paper; the model includes electrical, controller, and communication parts. The system stability and parameter...
International Nuclear Information System (INIS)
Wang, Bo; Tai, Neng-ling; Zhai, Hai-qing; Ye, Jian; Zhu, Jia-dong; Qi, Liang-bo
2008-01-01
In this paper, a new ARMAX model based on evolutionary algorithm and particle swarm optimization for short-term load forecasting is proposed. Auto-regressive (AR) and moving average (MA) with exogenous variables (ARMAX) has been widely applied in the load forecasting area. Because of the nonlinear characteristics of the power system loads, the forecasting function has many local optimal points. The traditional method based on gradient searching may be trapped in local optimal points and lead to high error. While, the hybrid method based on evolutionary algorithm and particle swarm optimization can solve this problem more efficiently than the traditional ways. It takes advantage of evolutionary strategy to speed up the convergence of particle swarm optimization (PSO), and applies the crossover operation of genetic algorithm to enhance the global search ability. The new ARMAX model for short-term load forecasting has been tested based on the load data of Eastern China location market, and the results indicate that the proposed approach has achieved good accuracy. (author)
Directory of Open Access Journals (Sweden)
Balajee Maram K.
2016-02-01
Full Text Available Data security is a major issue because of rapid evolution of data communication over unsecured internetwork. Here the proposed system is concerned with the problem of randomly generated S-box. The generation of S-box depends on Pseudo-Random-Number-Generators and shared-secret-key. The process of Pseudo-Random-Number-Generator depends on large prime numbers. All Pseudo-Random-Numbers are scrambled according to shared-secret-key. After scrambling, the S-box is generated. In this research, large prime numbers are the inputs to the Pseudo-Random-Number-Generator. The proposed S-box will reduce the complexity of S-box generation. Based on S-box parameters, it experimentally investigates the quality and robustness of the proposed algorithm which was tested. It yields better results with the S-box parameters like Hamming Distance, Balanced Output and Avalanche Effect and can be embedded to popular cryptography algorithms
Energy Technology Data Exchange (ETDEWEB)
Kim, Jong-Soo; Choe, Gyu-Yeong; Lee, Byoung-Kuk [School of Information and Communication Engineering, Sungkyunkwan University, 300 Cheoncheon-dong, Jangan-gu, Suwon, Gyeonggi-do 440-746 (Korea, Republic of); Kang, Hyun-Soo [R and D Center, Advanced Drive Technology (ADT) Company, 689-26 Geumjeong-dong, Gunpo-si, Gyeonggi-do 435-862 (Korea, Republic of)
2011-05-15
The low frequency current ripple in grid-connected fuel cell systems is generated from dc-ac inverter operation, which generates 60 Hz fundamental component, and gives harmful effects on fuel cell stack itself, such as making cathode surface responses slower, causing an increase of more than 10% in the fuel consumption, creating oxygen starvation, causing a reduction in the operating lifetime, and incurring a nuisance tripping such as overload situation. With these reasons, low frequency current ripple makes fuel cell system unstable and lifetime of fuel cell stack itself short. This paper presents a fast and robust control algorithm to eliminate low frequency current ripple in grid-connected fuel cell systems. Compared with the conventional methods, in the proposed control algorithm, dc link voltage controller is shifted from dc-dc converter to dc-ac inverter, resulting that dc-ac inverter handles dc link voltage control and output current control simultaneously with help of power balancing technique. The results indicate that the proposed algorithm can not only completely eliminate current ripple but also significantly reduce the overshoot or undershoot during transient states without any extra hardware. The validity of the proposed algorithm is verified by computer simulations and also by experiments with a 1 kW laboratory prototype. (author)
Power balance provision through co-ordinated control of modern storage heater load
Qazi, Hassan Wajahat; Flynn, Damian
2013-01-01
Operational inflexibility due to wind variability at high penetration levels can be mitigated through flexible demand. However, most flexible loads entail a subsequent short-term higher energy payback and aggregated load coincidence. Storage heaters operating on a dual tariff, that typically charge during a fixed time window, can be considered as distributed thermal storage without an associated energy payback period. Modern storage heaters have improved heat retention, the capability to esti...
Dynamic Harmony Search with Polynomial Mutation Algorithm for Valve-Point Economic Load Dispatch
Directory of Open Access Journals (Sweden)
M. Karthikeyan
2015-01-01
mutation (DHSPM algorithm to solve ORPD problem. In DHSPM algorithm the key parameters of HS algorithm like harmony memory considering rate (HMCR and pitch adjusting rate (PAR are changed dynamically and there is no need to predefine these parameters. Additionally polynomial mutation is inserted in the updating step of HS algorithm to favor exploration and exploitation of the search space. The DHSPM algorithm is tested with three power system cases consisting of 3, 13, and 40 thermal units. The computational results show that the DHSPM algorithm is more effective in finding better solutions than other computational intelligence based methods.
Directory of Open Access Journals (Sweden)
Yan Hong Chen
2016-01-01
Full Text Available This paper proposes a new electric load forecasting model by hybridizing the fuzzy time series (FTS and global harmony search algorithm (GHSA with least squares support vector machines (LSSVM, namely GHSA-FTS-LSSVM model. Firstly, the fuzzy c-means clustering (FCS algorithm is used to calculate the clustering center of each cluster. Secondly, the LSSVM is applied to model the resultant series, which is optimized by GHSA. Finally, a real-world example is adopted to test the performance of the proposed model. In this investigation, the proposed model is verified using experimental datasets from the Guangdong Province Industrial Development Database, and results are compared against autoregressive integrated moving average (ARIMA model and other algorithms hybridized with LSSVM including genetic algorithm (GA, particle swarm optimization (PSO, harmony search, and so on. The forecasting results indicate that the proposed GHSA-FTS-LSSVM model effectively generates more accurate predictive results.
Directory of Open Access Journals (Sweden)
Hussein Jassas
2015-04-01
Full Text Available Increasing dependence on groundwater requires a detailed determination of the different outputs and inputs of a basin for better water management. Determination of spatial and temporal actual evapotranspiration (ETa, in this regard, is of vital importance as there is significant water loss from drainage basins. This research paper uses the Surface Energy Balance Algorithm for Land (SEBAL, as well as the water balance, to estimate the spatial and temporal ETa in the Al-Khazir Gomal Basin, Northern Iraq. To compensate for the shortage in rainfall, and to irrigate summer crops, farmers in this basin have been depending, to a large extent, on groundwater extracted from the underlying unconfined aquifer, which is considered the major source for both domestic and agricultural uses in this basin. Rainfed farming of wheat and barley is one of the most important activities in the basin in the winter season, while in the summer season, agricultural activity is limited to small rice fields and narrow strips of vegetable cultivation along the Al-Khazir River. The Landsat Thematic Mapper images (TM5 acquired on 21 November 2006, 9 March 2007, 5 May 2007, 21 July 2007, and 23 September 2007 were used, along with a digital elevation model (DEM and ground-based meteorological data, measured within the area of interest. Estimation of seasonal ETa from periods between satellite overpasses was computed using the evaporative fraction (Ʌ. The water balance approach was utilized, using meteorological data and river hydrograph analysis, to estimate the ETa as the only missing input in the predefined water balance equation. The results of the two applied methods were comparable. SEBAL results were compared with the land use land cover (LULC map. The river showed the highest ETa, as evaporation from the free-water surface. Rice fields, irrigated in the summer season, have a high ETa in the images, as these fields are immersed in water during June, July and August
Directory of Open Access Journals (Sweden)
Yongquan Dong
2018-04-01
Full Text Available Providing accurate electric load forecasting results plays a crucial role in daily energy management of the power supply system. Due to superior forecasting performance, the hybridizing support vector regression (SVR model with evolutionary algorithms has received attention and deserves to continue being explored widely. The cuckoo search (CS algorithm has the potential to contribute more satisfactory electric load forecasting results. However, the original CS algorithm suffers from its inherent drawbacks, such as parameters that require accurate setting, loss of population diversity, and easy trapping in local optima (i.e., premature convergence. Therefore, proposing some critical improvement mechanisms and employing an improved CS algorithm to determine suitable parameter combinations for an SVR model is essential. This paper proposes the SVR with chaotic cuckoo search (SVRCCS model based on using a tent chaotic mapping function to enrich the cuckoo search space and diversify the population to avoid trapping in local optima. In addition, to deal with the cyclic nature of electric loads, a seasonal mechanism is combined with the SVRCCS model, namely giving a seasonal SVR with chaotic cuckoo search (SSVRCCS model, to produce more accurate forecasting performances. The numerical results, tested by using the datasets from the National Electricity Market (NEM, Queensland, Australia and the New York Independent System Operator (NYISO, NY, USA, show that the proposed SSVRCCS model outperforms other alternative models.
Wu, Hsiu; Cohen, Stephanie E; Westheimer, Emily; Gay, Cynthia L; Hall, Laura; Rose, Charles; Hightow-Weidman, Lisa B; Gose, Severin; Fu, Jie; Peters, Philip J
2017-08-01
New recommendations for laboratory diagnosis of HIV infection in the United States were published in 2014. The updated testing algorithm includes a qualitative HIV-1 RNA assay to resolve discordant immunoassay results and to identify acute HIV-1 infection (AHI). The qualitative HIV-1 RNA assay is not widely available; therefore, we evaluated the performance of a more widely available quantitative HIV-1 RNA assay, viral load, for diagnosing AHI. We determined that quantitative viral loads consistently distinguished AHI from a false-positive immunoassay result. Among 100 study participants with AHI and a viral load result, the estimated geometric mean viral load was 1,377,793copies/mL. Copyright © 2017 Elsevier B.V. All rights reserved.
Preciat Gonzalez, German A; El Assal, Lemmer R P; Noronha, Alberto; Thiele, Ines; Haraldsdóttir, Hulda S; Fleming, Ronan M T
2017-06-14
The mechanism of each chemical reaction in a metabolic network can be represented as a set of atom mappings, each of which relates an atom in a substrate metabolite to an atom of the same element in a product metabolite. Genome-scale metabolic network reconstructions typically represent biochemistry at the level of reaction stoichiometry. However, a more detailed representation at the underlying level of atom mappings opens the possibility for a broader range of biological, biomedical and biotechnological applications than with stoichiometry alone. Complete manual acquisition of atom mapping data for a genome-scale metabolic network is a laborious process. However, many algorithms exist to predict atom mappings. How do their predictions compare to each other and to manually curated atom mappings? For more than four thousand metabolic reactions in the latest human metabolic reconstruction, Recon 3D, we compared the atom mappings predicted by six atom mapping algorithms. We also compared these predictions to those obtained by manual curation of atom mappings for over five hundred reactions distributed among all top level Enzyme Commission number classes. Five of the evaluated algorithms had similarly high prediction accuracy of over 91% when compared to manually curated atom mapped reactions. On average, the accuracy of the prediction was highest for reactions catalysed by oxidoreductases and lowest for reactions catalysed by ligases. In addition to prediction accuracy, the algorithms were evaluated on their accessibility, their advanced features, such as the ability to identify equivalent atoms, and their ability to map hydrogen atoms. In addition to prediction accuracy, we found that software accessibility and advanced features were fundamental to the selection of an atom mapping algorithm in practice.
Directory of Open Access Journals (Sweden)
Ahmet Koksoy
2018-03-01
Full Text Available Wind turbine generating systems (WTGSs, which are conventionally connected to high voltage transmission networks, have frequently been employed as distributed generation units in today’s distribution networks. In practice, the distribution networks always have unbalanced bus voltages and line currents due to uneven distribution of single or double phase loads over three phases and asymmetry of the lines, etc. Accordingly, in this study, for the load flow analysis of the distribution networks, Conventional Fixed speed Induction Generator (CFIG based WTGS, one of the most widely used WTGS types, is modelled under unbalanced voltage conditions. The Developed model has active and reactive power expressions in terms of induction machine impedance parameters, terminal voltages and input power. The validity of the Developed model is confirmed with the experimental results obtained in a test system. The results of the slip calculation based phase-domain model (SCP Model, which was previously proposed in the literature for CFIG based WTGSs under unbalanced voltages, are also given for the comparison. Finally, the Developed model and the SCP model are implemented in the load flow analysis of the IEEE 34 bus test system with the CFIG based WTGSs and unbalanced loads. Thus, it is clearly pointed out that the results of the load flow analysis implemented with both models are very close to each other, and the Developed model is computationally more efficient than the SCP model.
Energy Technology Data Exchange (ETDEWEB)
Tom, Nathan M.; Yu, Yi-Hsiang; Wright, Alan D.; Lawson, Michael
2016-06-01
The aim of this paper is to describe how to control the power-to-load ratio of a novel wave energy converter (WEC) in irregular waves. The novel WEC that is being developed at the National Renewable Energy Laboratory combines an oscillating surge wave energy converter (OSWEC) with control surfaces as part of the structure; however, this work only considers one fixed geometric configuration. This work extends the optimal control problem so as to not solely maximize the time-averaged power, but to also consider the power-take-off (PTO) torque and foundation forces that arise because of WEC motion. The objective function of the controller will include competing terms that force the controller to balance power capture with structural loading. Separate penalty weights were placed on the surge-foundation force and PTO torque magnitude, which allows the controller to be tuned to emphasize either power absorption or load shedding. Results of this study found that, with proper selection of penalty weights, gains in time-averaged power would exceed the gains in structural loading while minimizing the reactive power requirement.
International Nuclear Information System (INIS)
Yu, Feng; Xu, Xiaozhong
2014-01-01
Highlights: • A detailed data processing will make more accurate results prediction. • Taking a full account of more load factors to improve the prediction precision. • Improved BP network obtains higher learning convergence. • Genetic algorithm optimized by chaotic cat map enhances the global search ability. • The combined GA–BP model improved by modified additional momentum factor is superior to others. - Abstract: This paper proposes an appropriate combinational approach which is based on improved BP neural network for short-term gas load forecasting, and the network is optimized by the real-coded genetic algorithm. Firstly, several kinds of modifications are carried out on the standard neural network to accelerate the convergence speed of network, including improved additional momentum factor, improved self-adaptive learning rate and improved momentum and self-adaptive learning rate. Then, it is available to use the global search capability of optimized genetic algorithm to determine the initial weights and thresholds of BP neural network to avoid being trapped in local minima. The ability of GA is enhanced by cat chaotic mapping. In light of the characteristic of natural gas load for Shanghai, a series of data preprocessing methods are adopted and more comprehensive load factors are taken into account to improve the prediction accuracy. Such improvements facilitate forecasting efficiency and exert maximum performance of the model. As a result, the integration model improved by modified additional momentum factor gets more ideal solutions for short-term gas load forecasting, through analyses and comparisons of the above several different combinational algorithms
Directory of Open Access Journals (Sweden)
Bao Wang
2012-11-01
Full Text Available The accuracy of annual electric load forecasting plays an important role in the economic and social benefits of electric power systems. The least squares support vector machine (LSSVM has been proven to offer strong potential in forecasting issues, particularly by employing an appropriate meta-heuristic algorithm to determine the values of its two parameters. However, these meta-heuristic algorithms have the drawbacks of being hard to understand and reaching the global optimal solution slowly. As a novel meta-heuristic and evolutionary algorithm, the fruit fly optimization algorithm (FOA has the advantages of being easy to understand and fast convergence to the global optimal solution. Therefore, to improve the forecasting performance, this paper proposes a LSSVM-based annual electric load forecasting model that uses FOA to automatically determine the appropriate values of the two parameters for the LSSVM model. By taking the annual electricity consumption of China as an instance, the computational result shows that the LSSVM combined with FOA (LSSVM-FOA outperforms other alternative methods, namely single LSSVM, LSSVM combined with coupled simulated annealing algorithm (LSSVM-CSA, generalized regression neural network (GRNN and regression model.
International Nuclear Information System (INIS)
Wang Jianzhou; Jia Ruiling; Zhao Weigang; Wu Jie; Dong Yao
2012-01-01
Highlights: ► The maximal predictive step size is determined by the largest Lyapunov exponent. ► A proper forecasting step size is applied to load demand forecasting. ► The improved approach is validated by the actual load demand data. ► Non-linear fractal extrapolation method is compared with three forecasting models. ► Performance of the models is evaluated by three different error measures. - Abstract: Precise short-term load forecasting (STLF) plays a key role in unit commitment, maintenance and economic dispatch problems. Employing a subjective and arbitrary predictive step size is one of the most important factors causing the low forecasting accuracy. To solve this problem, the largest Lyapunov exponent is adopted to estimate the maximal predictive step size so that the step size in the forecasting is no more than this maximal one. In addition, in this paper a seldom used forecasting model, which is based on the non-linear fractal extrapolation (NLFE) algorithm, is considered to develop the accuracy of predictions. The suitability and superiority of the two solutions are illustrated through an application to real load forecasting using New South Wales electricity load data from the Australian National Electricity Market. Meanwhile, three forecasting models: the gray model, the seasonal autoregressive integrated moving average approach and the support vector machine method, which received high approval in STLF, are selected to compare with the NLFE algorithm. Comparison results also show that the NLFE model is outstanding, effective, practical and feasible.
Simple Models for Model-based Portfolio Load Balancing Controller Synthesis
DEFF Research Database (Denmark)
Edlund, Kristian Skjoldborg; Mølbak, Tommy; Bendtsen, Jan Dimon
2010-01-01
of generation units existing in an electrical power supply network, for instance in model-based predictive control or declarative control schemes. We focus on the effectuators found in the Danish power system. In particular, the paper presents models for boiler load, district heating, condensate throttling...
Queue balancing of load and expedition service in a cement industry in Brazil
Directory of Open Access Journals (Sweden)
David Custódio de Sena
2013-11-01
Full Text Available The load and weight process in a cement industry is one of logistic step that shows the biggest time of occurrence, increasing the queues. This study aims to do a scenarios to solve this queue problem. This way, it pretends to find an better resources distribuition.
Directory of Open Access Journals (Sweden)
Duka Adrian-Vasile
2011-12-01
Full Text Available This paper examines the development of a genetic adaptive fuzzy control system for the Inverted Pendulum. The inverted pendulum is a classical problem in Control Engineering, used for testing different control algorithms. The goal is to balance the inverted pendulum in the upright position by controlling the horizontal force applied to its cart. Because it is unstable and has a complicated nonlinear dynamics, the inverted pendulum is a good testbed for the development of nonconventional advanced control techniques. Fuzzy logic technique has been successfully applied to control this type of system, however most of the time the design of the fuzzy controller is done in an ad-hoc manner, and choosing certain parameters (controller gains, membership functions proves difficult. This paper examines the implementation of an adaptive control method based on genetic algorithms (GA, which can be used on-line to produce the adaptation of the fuzzy controller’s gains in order to achieve the stabilization of the pendulum. The performances of the proposed control algorithms are evaluated and shown by means of digital simulation.
Two Dimensional Array Based Overlay Network for Balancing Load of Peer-to-Peer Live Video Streaming
Faruq Ibn Ibrahimy, Abdullah; Rafiqul, Islam Md; Anwar, Farhat; Ibn Ibrahimy, Muhammad
2013-12-01
The live video data is streaming usually in a tree-based overlay network or in a mesh-based overlay network. In case of departure of a peer with additional upload bandwidth, the overlay network becomes very vulnerable to churn. In this paper, a two dimensional array-based overlay network is proposed for streaming the live video stream data. As there is always a peer or a live video streaming server to upload the live video stream data, so the overlay network is very stable and very robust to churn. Peers are placed according to their upload and download bandwidth, which enhances the balance of load and performance. The overlay network utilizes the additional upload bandwidth of peers to minimize chunk delivery delay and to maximize balance of load. The procedure, which is used for distributing the additional upload bandwidth of the peers, distributes the additional upload bandwidth to the heterogeneous strength peers in a fair treat distribution approach and to the homogeneous strength peers in a uniform distribution approach. The proposed overlay network has been simulated by Qualnet from Scalable Network Technologies and results are presented in this paper.
Two Dimensional Array Based Overlay Network for Balancing Load of Peer-to-Peer Live Video Streaming
International Nuclear Information System (INIS)
Ibrahimy, Abdullah Faruq Ibn; Rafiqul, Islam Md; Anwar, Farhat; Ibrahimy, Muhammad Ibn
2013-01-01
The live video data is streaming usually in a tree-based overlay network or in a mesh-based overlay network. In case of departure of a peer with additional upload bandwidth, the overlay network becomes very vulnerable to churn. In this paper, a two dimensional array-based overlay network is proposed for streaming the live video stream data. As there is always a peer or a live video streaming server to upload the live video stream data, so the overlay network is very stable and very robust to churn. Peers are placed according to their upload and download bandwidth, which enhances the balance of load and performance. The overlay network utilizes the additional upload bandwidth of peers to minimize chunk delivery delay and to maximize balance of load. The procedure, which is used for distributing the additional upload bandwidth of the peers, distributes the additional upload bandwidth to the heterogeneous strength peers in a fair treat distribution approach and to the homogeneous strength peers in a uniform distribution approach. The proposed overlay network has been simulated by Qualnet from Scalable Network Technologies and results are presented in this paper
Utilization of Model Predictive Control to Balance Power Absorption Against Load Accumulation
Energy Technology Data Exchange (ETDEWEB)
Abbas, Nikhar [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Tom, Nathan M [National Renewable Energy Laboratory (NREL), Golden, CO (United States)
2017-06-03
Wave energy converter (WEC) control strategies have been primarily focused on maximizing power absorption. The use of model predictive control strategies allows for a finite-horizon, multiterm objective function to be solved. This work utilizes a multiterm objective function to maximize power absorption while minimizing the structural loads on the WEC system. Furthermore, a Kalman filter and autoregressive model were used to estimate and forecast the wave exciting force and predict the future dynamics of the WEC. The WEC's power-take-off time-averaged power and structural loads under a perfect forecast assumption in irregular waves were compared against results obtained from the Kalman filter and autoregressive model to evaluate model predictive control performance.
Automated load balancing in the ATLAS high-performance storage software
Le Goff, Fabrice; The ATLAS collaboration
2017-01-01
The ATLAS experiment collects proton-proton collision events delivered by the LHC accelerator at CERN. The ATLAS Trigger and Data Acquisition (TDAQ) system selects, transports and eventually records event data from the detector at several gigabytes per second. The data are recorded on transient storage before being delivered to permanent storage. The transient storage consists of high-performance direct-attached storage servers accounting for about 500 hard drives. The transient storage operates dedicated software in the form of a distributed multi-threaded application. The workload includes both CPU-demanding and IO-oriented tasks. This paper presents the original application threading model for this particular workload, discussing the load-sharing strategy among the available CPU cores. The limitations of this strategy were reached in 2016 due to changes in the trigger configuration involving a new data distribution pattern. We then describe a novel data-driven load-sharing strategy, designed to automatical...
Energy Technology Data Exchange (ETDEWEB)
Abbas, Nikhar; Tom, Nathan
2017-09-01
Wave energy converter (WEC) control strategies have been primarily focused on maximizing power absorption. The use of model predictive control strategies allows for a finite-horizon, multiterm objective function to be solved. This work utilizes a multiterm objective function to maximize power absorption while minimizing the structural loads on the WEC system. Furthermore, a Kalman filter and autoregressive model were used to estimate and forecast the wave exciting force and predict the future dynamics of the WEC. The WEC's power-take-off time-averaged power and structural loads under a perfect forecast assumption in irregular waves were compared against results obtained from the Kalman filter and autoregressive model to evaluate model predictive control performance.
A balancing act of the brain: activations and deactivations driven by cognitive load
Arsalidou, Marie; Pascual-Leone, Juan; Johnson, Janice; Morris, Drew; Taylor, Margot J
2013-01-01
The majority of neuroimaging studies focus on brain activity during performance of cognitive tasks; however, some studies focus on brain areas that activate in the absence of a task. Despite the surge of research comparing these contrasted areas of brain function, their interrelation is not well understood. We systematically manipulated cognitive load in a working memory task to examine concurrently the relation between activity elicited by the task versus activity during control conditions. ...
Balance of alkaline and acidic pollution loads in the area affected by oil shale combustion
International Nuclear Information System (INIS)
Kaasik, M.
2000-01-01
Field measurements of concentrations of SO 2 and NO 2 in the air and deposition of Ca 2+ , Mg 2+ , K + , Na + , SO 4 2- , NO 3 - and Cl - in northeastern Estonia were carried out in the end of winter 1998/99. Concentrations in the air were measured by passive sampling method (Palmes tubes); snow samples were used to quantify the deposition loads. The measurement domain covered entire Ida-Viru County, eastern part of Laeaene-Viru County and a few sites in Jogeva County. These measurements and comparison with earlier investigations show that in wintertime most of sulfate over the area affected by oil shale industrial complex appears to be deposited with fly ash particles. The regression formulae for wintertime sulfate and calcium deposition loads for oil-shale region are derived. The inhomogeneous chemical composition of fly ash and influence of other (domestic, traffic) emissions are suggested as possible factors affecting the ratio of sulfate and calcium deposition loads. (author)
Paramestha, D. L.; Santosa, B.
2018-04-01
Two-dimensional Loading Heterogeneous Fleet Vehicle Routing Problem (2L-HFVRP) is a combination of Heterogeneous Fleet VRP and a packing problem well-known as Two-Dimensional Bin Packing Problem (BPP). 2L-HFVRP is a Heterogeneous Fleet VRP in which these costumer demands are formed by a set of two-dimensional rectangular weighted item. These demands must be served by a heterogeneous fleet of vehicles with a fix and variable cost from the depot. The objective function 2L-HFVRP is to minimize the total transportation cost. All formed routes must be consistent with the capacity and loading process of the vehicle. Sequential and unrestricted scenarios are considered in this paper. We propose a metaheuristic which is a combination of the Genetic Algorithm (GA) and the Cross Entropy (CE) named Cross Entropy Genetic Algorithm (CEGA) to solve the 2L-HFVRP. The mutation concept on GA is used to speed up the algorithm CE to find the optimal solution. The mutation mechanism was based on local improvement (2-opt, 1-1 Exchange, and 1-0 Exchange). The probability transition matrix mechanism on CE is used to avoid getting stuck in the local optimum. The effectiveness of CEGA was tested on benchmark instance based 2L-HFVRP. The result of experiments shows a competitive result compared with the other algorithm.
Importance measures and genetic algorithms for designing a risk-informed optimally balanced system
International Nuclear Information System (INIS)
Zio, Enrico; Podofillini, Luca
2007-01-01
This paper deals with the use of importance measures for the risk-informed optimization of system design and management. An optimization approach is presented in which the information provided by the importance measures is incorporated in the formulation of a multi-objective optimization problem to drive the design towards a solution which, besides being optimal from the points of view of economics and safety, is also 'balanced' in the sense that all components have similar importance values. The approach allows identifying design systems without bottlenecks or unnecessarily high-performing components and with test/maintenance activities calibrated according to the components' importance ranking. The approach is tested at first against a multi-state system design optimization problem in which off-the-shelf components have to be properly allocated. Then, the more realistic problem of risk-informed optimization of the technical specifications of a safety system of a nuclear power plant is addressed
Zamani, Abbasali; Barakati, S Masoud; Yousofi-Darmian, Saeed
2016-09-01
Load-frequency control is one of the most important issues in power system operation. In this paper, a Fractional Order PID (FOPID) controller based on Gases Brownian Motion Optimization (GBMO) is used in order to mitigate frequency and exchanged power deviation in two-area power system with considering governor saturation limit. In a FOPID controller derivative and integrator parts have non-integer orders which should be determined by designer. FOPID controller has more flexibility than PID controller. The GBMO algorithm is a recently introduced search method that has suitable accuracy and convergence rate. Thus, this paper uses the advantages of FOPID controller as well as GBMO algorithm to solve load-frequency control. However, computational load will higher than conventional controllers due to more complexity of design procedure. Also, a GBMO based fuzzy controller is designed and analyzed in detail. The performance of the proposed controller in time domain and its robustness are verified according to comparison with other controllers like GBMO based fuzzy controller and PI controller that used for load-frequency control system in confronting with model parameters variations. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
A Load Balancing Scheme Using Federate Migration Based on Virtual Machines for Cloud Simulations
Directory of Open Access Journals (Sweden)
Xiao Song
2015-01-01
Full Text Available A maturing and promising technology, Cloud computing can benefit large-scale simulations by providing on-demand, anywhere simulation services to users. In order to enable multitask and multiuser simulation systems with Cloud computing, Cloud simulation platform (CSP was proposed and developed. To use key techniques of Cloud computing such as virtualization to promote the running efficiency of large-scale military HLA systems, this paper proposes a new type of federate container, virtual machine (VM, and its dynamic migration algorithm considering both computation and communication cost. Experiments show that the migration scheme effectively improves the running efficiency of HLA system when the distributed system is not saturated.
Optimizing the Loads of multi-player online game Servers using Markov Chains
DEFF Research Database (Denmark)
Saeed, Aamir; Olsen, Rasmus Løvenstein; Pedersen, Jens Myrup
2015-01-01
that is created due to the load balancing of servers. Load balancing among servers is sensitive to correct status information. The Markov based load prediction was introduced in this paper to predict load of under-loaded servers, based on arrival (μ) and departure (λ) rates of players. The prediction based...... that need to be considered when developing load balancing algorithm, that is the reliability of the information that is shared. Simulation results show that Markov based prediction of load information performed better from the normal load status information sharing....
Innovation of genetic algorithm code GenA for WWER fuel loading optimization
International Nuclear Information System (INIS)
Sustek, J.
2005-01-01
One of the stochastic search techniques - genetic algorithms - was recently used for optimization of arrangement of fuel assemblies (FA) in core of reactors WWER-440 and WWER-1000. Basic algorithm was modified by incorporation of SPEA scheme. Both were enhanced and some results are presented (Authors)
Load Balancing Metric with Diversity for Energy Efficient Routing in Wireless Sensor Networks
DEFF Research Database (Denmark)
Moad, Sofiane; Hansen, Morten Tranberg; Jurdak, Raja
2011-01-01
The expected number of transmission (ETX) represents a routing metric that considers the highly variable link qualities for a specific radio in Wireless Sensor Networks (WSNs). To adapt to these differences, radio diversity is a recently explored solution for WSNs. In this paper, we propose...... an energy balancing metric which explores the diversity in link qualities present at different radios. The goal is to effectively use the energy of the network and therefore extend the network lifetime. The proposed metric takes into account the transmission and reception costs for a specific radio in order...... to choose an energy efficient radio. In addition, the metric uses the remaining energy of nodes in order to regulate the traffic so that critical nodes are avoided. We show by simulations that our metric can improve the network lifetime up to 20%....
DEFF Research Database (Denmark)
Kepler, Jørgen Asbøl; Hansen, Michael Rygaard
2007-01-01
thickness but significantly smaller than panel length dimensions. Experimental data for the total loss in impactor kinetic energy and momentum and estimated damage energy are described. For a selection of impactor tip shapes, the numerical model is used to evaluate different simplified force histories...... between the impactor and the panel during penetration. The force histories are selected from a primary criterion of conservation of linear momentum in the impactor-panel system, and evaluated according to agreement with the total measured energy balance.......A sandwich panel is described by an axisymmetric lumped mass- spring model. The panel compliance is simplified, considering only core shear deformation uniformly distributed across the core thickness. Transverse penetrating impact is modeled for impactors of diameters comparable to the panel...
Zampini, Stefano; Tu, Xuemin
2017-01-01
Multilevel balancing domain decomposition by constraints (BDDC) deluxe algorithms are developed for the saddle point problems arising from mixed formulations of Darcy flow in porous media. In addition to the standard no-net-flux constraints on each face, adaptive primal constraints obtained from the solutions of local generalized eigenvalue problems are included to control the condition number. Special deluxe scaling and local generalized eigenvalue problems are designed in order to make sure that these additional primal variables lie in a benign subspace in which the preconditioned operator is positive definite. The current multilevel theory for BDDC methods for porous media flow is complemented with an efficient algorithm for the computation of the so-called malign part of the solution, which is needed to make sure the rest of the solution can be obtained using the conjugate gradient iterates lying in the benign subspace. We also propose a new technique, based on the Sherman--Morrison formula, that lets us preserve the complexity of the subdomain local solvers. Condition number estimates are provided under certain standard assumptions. Extensive numerical experiments confirm the theoretical estimates; additional numerical results prove the effectiveness of the method with higher order elements and high-contrast problems from real-world applications.
Zampini, Stefano
2017-08-03
Multilevel balancing domain decomposition by constraints (BDDC) deluxe algorithms are developed for the saddle point problems arising from mixed formulations of Darcy flow in porous media. In addition to the standard no-net-flux constraints on each face, adaptive primal constraints obtained from the solutions of local generalized eigenvalue problems are included to control the condition number. Special deluxe scaling and local generalized eigenvalue problems are designed in order to make sure that these additional primal variables lie in a benign subspace in which the preconditioned operator is positive definite. The current multilevel theory for BDDC methods for porous media flow is complemented with an efficient algorithm for the computation of the so-called malign part of the solution, which is needed to make sure the rest of the solution can be obtained using the conjugate gradient iterates lying in the benign subspace. We also propose a new technique, based on the Sherman--Morrison formula, that lets us preserve the complexity of the subdomain local solvers. Condition number estimates are provided under certain standard assumptions. Extensive numerical experiments confirm the theoretical estimates; additional numerical results prove the effectiveness of the method with higher order elements and high-contrast problems from real-world applications.
Indian Academy of Sciences (India)
ticians but also forms the foundation of computer science. Two ... with methods of developing algorithms for solving a variety of problems but ... applications of computers in science and engineer- ... numerical calculus are as important. We will ...
Directory of Open Access Journals (Sweden)
Y. A. Gatchin
2016-05-01
Full Text Available Subject of Research.This paper presents solution of authentication problem for all components of information interoperabilityin process of operation system network loading on thin client from terminal server. System Definition. In the proposed solution operation system integrity check is made by hardware-software module, including USB-token with protected memory for secure storage of cryptographic keys and loader. The key requirement for the solution is mutual authentication of four participants: terminal server, thin client, token and user. We have created two algorithms for the problem solution. The first of the designed algorithms compares the encrypted one-time password (random number with the reference value stored in the memory of the token and updates this number in case of successful authentication. The second algorithm uses the public and private keys of the token and the server. As a result of cryptographic transformation, participants are authenticated and the secure channel is formed between the token, thin client and terminal server. Main Results. Additional research was carried out to find out if the designed algorithms meet the necessary requirements. Criteria used included applicability in a multi-access terminal system architecture, potential threats evaluation and overall system security. According to analysis results, it is recommended to use the algorithm based on PKI due to its high scalability and usability. High level of data security is proved as a result of asymmetric cryptography application with the guarantee that participants' private keys are never sent in the authentication process. Practical Relevance. The designed PKI-based algorithm allows solving the problem with the use of cryptographic algorithms according to state standard even in its absence on asymmetric cryptography. Thus, it can be applied in the State Information Systems with increased requirements to information security.
Directory of Open Access Journals (Sweden)
R. Mageshvaran
2015-09-01
The proposed algorithm is tested on IEEE 14, 30 and 118 bus test systems. The viability of the proposed method in terms of solution quality and convergence properties is compared with the other conventional methods reported earlier.
Directory of Open Access Journals (Sweden)
Jiani Heng
2016-01-01
Full Text Available Power load forecasting always plays a considerable role in the management of a power system, as accurate forecasting provides a guarantee for the daily operation of the power grid. It has been widely demonstrated in forecasting that hybrid forecasts can improve forecast performance compared with individual forecasts. In this paper, a hybrid forecasting approach, comprising Empirical Mode Decomposition, CSA (Cuckoo Search Algorithm, and WNN (Wavelet Neural Network, is proposed. This approach constructs a more valid forecasting structure and more stable results than traditional ANN (Artificial Neural Network models such as BPNN (Back Propagation Neural Network, GABPNN (Back Propagation Neural Network Optimized by Genetic Algorithm, and WNN. To evaluate the forecasting performance of the proposed model, a half-hourly power load in New South Wales of Australia is used as a case study in this paper. The experimental results demonstrate that the proposed hybrid model is not only simple but also able to satisfactorily approximate the actual power load and can be an effective tool in planning and dispatch for smart grids.
tongqing, Wu; liang, Li; xinjian, Liu; Xu, nianchun; Tian, Mao
2018-03-01
Self-balanced method is carried out on the large diameter rock-socketed filling piles of high-pile wharf at Inland River, to explore the distribution laws of load-displacement curve, pile internal force, pile tip friction resistance and pile side friction resistance under load force. The results showed that: the tip resistance of S1 and S2 test piles accounted for 53.4% and 53.6% of the pile bearing capacity, respectively, while the total side friction resistance accounted for 46.6% and 46.4% of the pile bearing capacity, respectively; both the pile tip friction resistance and pile side friction resistance can be fully played, and reach to the design requirements. The reasonability of large diameter rock-socketed filling design is verified through test analysis, which can provide basis for the optimization of high-pile wharf structural type, thus reducing the wharf project cost, and also providing reference for the similar large diameter rock-socketed filling piles of high-pile wharf at Inland River.
Effects of nutrient loading on the carbon balance of coastal wetland sediments
Morris, J.T.; Bradley, P.M.
1999-01-01
Results of a 12-yr study in an oligotrophic South Carolina salt marsh demonstrate that soil respiration increased by 795 g C m-2 yr-1 and that carbon inventories decreased in sediments fertilized with nitrogen and phosphorus. Fertilized plots became net sources of carbon to the atmosphere, and sediment respiration continues in these plots at an accelerated pace. After 12 yr of treatment, soil macroorganic matter in the top 5 cm of sediment was 475 g C m-2 lower in fertilized plots than in controls, which is equivalent to a constant loss rate of 40 g C m-2 yr-1. It is not known whether soil carbon in fertilized plots has reached a new equilibrium or continues to decline. The increase in soil respiration in the fertilized plots was far greater than the loss of sediment organic matter, which indicates that the increase in soil respiration was largely due to an increase in primary production. Sediment respiration in laboratory incubations also demonstrated positive effects of nutrients. Thus, the results indicate that increased nutrient loading of oligotrophic wetlands can lead to an increased rate of sediment carbon turnover and a net loss of carbon from sediments.
Cho, Jae Heon; Lee, Jong Ho
2015-11-01
Manual calibration is common in rainfall-runoff model applications. However, rainfall-runoff models include several complicated parameters; thus, significant time and effort are required to manually calibrate the parameters individually and repeatedly. Automatic calibration has relative merit regarding time efficiency and objectivity but shortcomings regarding understanding indigenous processes in the basin. In this study, a watershed model calibration framework was developed using an influence coefficient algorithm and genetic algorithm (WMCIG) to automatically calibrate the distributed models. The optimization problem used to minimize the sum of squares of the normalized residuals of the observed and predicted values was solved using a genetic algorithm (GA). The final model parameters were determined from the iteration with the smallest sum of squares of the normalized residuals of all iterations. The WMCIG was applied to a Gomakwoncheon watershed located in an area that presents a total maximum daily load (TMDL) in Korea. The proportion of urbanized area in this watershed is low, and the diffuse pollution loads of nutrients such as phosphorus are greater than the point-source pollution loads because of the concentration of rainfall that occurs during the summer. The pollution discharges from the watershed were estimated for each land-use type, and the seasonal variations of the pollution loads were analyzed. Consecutive flow measurement gauges have not been installed in this area, and it is difficult to survey the flow and water quality in this area during the frequent heavy rainfall that occurs during the wet season. The Hydrological Simulation Program-Fortran (HSPF) model was used to calculate the runoff flow and water quality in this basin. Using the water quality results, a load duration curve was constructed for the basin, the exceedance frequency of the water quality standard was calculated for each hydrologic condition class, and the percent reduction
Indian Academy of Sciences (India)
algorithm design technique called 'divide-and-conquer'. One of ... Turtle graphics, September. 1996. 5. ... whole list named 'PO' is a pointer to the first element of the list; ..... Program for computing matrices X and Y and placing the result in C *).
Indian Academy of Sciences (India)
algorithm that it is implicitly understood that we know how to generate the next natural ..... Explicit comparisons are made in line (1) where maximum and minimum is ... It can be shown that the function T(n) = 3/2n -2 is the solution to the above ...
A Modified Load Flow Algorithm in Power Systems with Alternative Energy Sources
International Nuclear Information System (INIS)
Contreras, D.L.; Cañedo, J.M.
2017-01-01
In this paper an algorithm for calculating the steady state of electrical networks including wind and photovoltaic generation is presented. The wind generators considered are; asynchronous (squirrel cage and doubly fed) and synchronous generators using permanent magnets. The proposed algorithm is based on the formulation of nodal power injections that is solved with the modified Newton Raphson technique in its polar formulation using complex matrices notation. Each power injection of wind and photovoltaic generators is calculated independently in each iteration according to its particular mathematical model, which is generally non-linear. Results are presented with a 30-node test system. The computation time of the proposed algorithm is compared with the conventional methodology to include alternative energy sources in power flows studies. (author)
Directory of Open Access Journals (Sweden)
Z. Q. Gao
2011-01-01
Full Text Available Evapotranspiration (ET may be used as an ecological indicator to address the ecosystem complexity. The accurate measurement of ET is of great significance for studying environmental sustainability, global climate changes, and biodiversity. Remote sensing technologies are capable of monitoring both energy and water fluxes on the surface of the Earth. With this advancement, existing models, such as SEBAL, S_SEBI and SEBS, enable us to estimate the regional ET with limited temporal and spatial coverage in the study areas. This paper extends the existing modeling efforts with the inclusion of new components for ET estimation at different temporal and spatial scales under heterogeneous terrain with varying elevations, slopes and aspects. Following a coupled remote sensing and surface energy balance approach, this study emphasizes the structure and function of the Surface Energy Balance with Topography Algorithm (SEBTA. With the aid of the elevation and landscape information, such as slope and aspect parameters derived from the digital elevation model (DEM, and the vegetation cover derived from satellite images, the SEBTA can account for the dynamic impacts of heterogeneous terrain and changing land cover with some varying kinetic parameters (i.e., roughness and zero-plane displacement. Besides, the dry and wet pixels can be recognized automatically and dynamically in image processing thereby making the SEBTA more sensitive to derive the sensible heat flux for ET estimation. To prove the application potential, the SEBTA was carried out to present the robust estimates of 24 h solar radiation over time, which leads to the smooth simulation of the ET over seasons in northern China where the regional climate and vegetation cover in different seasons compound the ET calculations. The SEBTA was validated by the measured data at the ground level. During validation, it shows that the consistency index reached 0.92 and the correlation coefficient was 0.87.
Directory of Open Access Journals (Sweden)
Abdul Rahim Siti Rafidah
2018-01-01
Full Text Available This paper presents the effect of load model prior to the distributed generation (DG planning in distribution system. In achieving optimal allocation and placement of DG, a ranking identification technique was proposed in order to study the DG planning using pre-developed Embedded Meta Evolutionary Programming–Firefly Algorithm. The aim of this study is to analyze the effect of different type of DG in order to reduce the total losses considering load factor. To realize the effectiveness of the proposed technique, the IEEE 33 bus test systems was utilized as the test specimen. In this study, the proposed techniques were used to determine the DG sizing and the suitable location for DG planning. The results produced are utilized for the optimization process of DG for the benefit of power system operators and planners in the utility. The power system planner can choose the suitable size and location from the result obtained in this study with the appropriate company’s budget. The modeling of voltage dependent loads has been presented and the results show the voltage dependent load models have a significant effect on total losses of a distribution system for different DG type.
DEFF Research Database (Denmark)
Hansen, Rico Hjerm; Andersen, Torben Ole; Pedersen, Henrik C.
2010-01-01
The relevance of electronic control of mobile hydraulic systems is increasing as hydraulic components are implemented with more electrical sensors and actuators. This paper presents how the traditional Hydro-mechanical Load Sensing (HLS) control of a specific mobile hydraulic application......, a telehandler, can be replaced with electronic control, i.e. Electronic Load Sensing (ELS). The motivation is the potential of improved dynamic performance and power utilization, along with reducing the mechanical complexity by moving traditional hydro-mechanical implemented features such as pressure control...
Directory of Open Access Journals (Sweden)
Nazarenko Inna М.
2017-04-01
Full Text Available The publication is aimed to provide scientific substantiation for the organizational-methodical aspects and the algorithmization of the financial audit process of the «Balance (financial status report». It has been proven that financial auditing through transformation has expanded the functional role of auditing. The author emphasizes that the financial audit of the «Balance (financial status report» should be directed to confirming the validity and consistency of showings in this form of financial reporting with the requirements of Ukrainian legislation, the internal regulations of the economic entities, and the expert assessment of the financial state. Financial auditing is also designed to diagnose solvency (financial sustainability, liquidity and business activity; to assess the threats of bankruptcy; to determine the worthiness and value of entrepreneur. An algorithm for financial auditing of the «Balance (financial status report» of enterprise has been developed, with organizational, research, and performance phases as constituent parts.
Indian Academy of Sciences (India)
will become clear in the next article when we discuss a simple logo like programming language. ... Rod B may be used as an auxiliary store. The problem is to find an algorithm which performs this task. ... No disks are moved from A to Busing C as auxiliary rod. • move _disk (A, C);. (No + l)th disk is moved from A to C directly ...
Zhu, Yanwei; Yi, Fajun; Meng, Songhe; Zhuo, Lijun; Pan, Weizhen
2017-11-01
Improving the surface heat load measurement technique for vehicles in aerodynamic heating environments is imperative, regarding aspects of both the apparatus design and identification efficiency. A simple novel apparatus is designed for heat load identification, taking into account the lessons learned from several aerodynamic heating measurement devices. An inverse finite difference scheme (invFDM) for the apparatus is studied to identify its surface heat flux from the interior temperature measurements with high efficiency. A weighted piecewise regression filter is also proposed for temperature measurement prefiltering. Preliminary verification of the invFDM scheme and the filter is accomplished via numerical simulation experiments. Three specific pieces of apparatus have been concretely designed and fabricated using different sensing materials. The aerodynamic heating process is simulated by an inductively coupled plasma wind tunnel facility. The identification of surface temperature and heat flux from the temperature measurements is performed by invFDM. The results validate the high efficiency, reliability and feasibility of heat load measurements with different heat flux levels utilizing the designed apparatus and proposed method.
International Nuclear Information System (INIS)
Zhu, Yanwei; Yi, Fajun; Meng, Songhe; Zhuo, Lijun; Pan, Weizhen
2017-01-01
Improving the surface heat load measurement technique for vehicles in aerodynamic heating environments is imperative, regarding aspects of both the apparatus design and identification efficiency. A simple novel apparatus is designed for heat load identification, taking into account the lessons learned from several aerodynamic heating measurement devices. An inverse finite difference scheme (invFDM) for the apparatus is studied to identify its surface heat flux from the interior temperature measurements with high efficiency. A weighted piecewise regression filter is also proposed for temperature measurement prefiltering. Preliminary verification of the invFDM scheme and the filter is accomplished via numerical simulation experiments. Three specific pieces of apparatus have been concretely designed and fabricated using different sensing materials. The aerodynamic heating process is simulated by an inductively coupled plasma wind tunnel facility. The identification of surface temperature and heat flux from the temperature measurements is performed by invFDM. The results validate the high efficiency, reliability and feasibility of heat load measurements with different heat flux levels utilizing the designed apparatus and proposed method. (paper)
Robust PD Sway Control of a Lifted Load for a Crane Using a Genetic Algorithm
Kawada, Kazuo; Sogo, Hiroyuki; Yamamoto, Toru; Mada, Yasuhiro
PID control schemes still continue to be widely used for most industrial control systems. This is mainly because PID controllers have simple control structures, and are simple to maintain and tune. However, it is difficult to find a set of suitable control parameters in the case of time-varying and/or nonlinear systems. For such a problem, the robust controller has been proposed.Although it is important to choose the suitable nominal model in designing the robust controller, it is not usually easy.In this paper, a new robust PD controller design scheme is proposed, which utilizes a genetic algorithm.
Directory of Open Access Journals (Sweden)
Tamilselvan V.
2016-06-01
Full Text Available The radial distribution system is a rugged system, it is also the most commonly used system, which suffers by loss and low voltage at the end bus. This loss can be reduced by the use of a capacitor in the system, which injects reactive current and also improves the voltage magnitude in the buses. The real power loss in the distribution line is the I2R loss which depends on the current and resistance. The connection of the capacitor in the bus reduces the reactive current and losses. The loss reduction is equal to the increase in generation, necessary for the electric power provided by firms. For consumers, the quality of power supply depends on the voltage magnitude level, which is also considered and hence the objective of the problem becomes the multi objective of loss minimization and the minimization of voltage deviation. In this paper, the optimal location and size of the capacitor is found using a new computational intelligent algorithm called Flower Pollination Algorithm (FPA. To calculate the power flow and losses in the system, novel data structure load flow is introduced. In this, each bus is considered as a node with bus associated data. Links between the nodes are distribution lines and their own resistance and reactance. To validate the developed FPA solutions standard test cases, IEEE 33 and IEEE 69 radial distribution systems are considered.
International Nuclear Information System (INIS)
Zhuravleva, A.M.; Litvinov, V.B.
1982-01-01
The problem of dynamic analysis of stressed-strained state of vacuum chambers is vital for large thermonuclear devices during the stall of the plasma-filament apd other tpansitional operation regimes when loading for a chamber are nonstationary. To plot a mathematical model the design of the vacuum chamber is discreted on the basis of the method of final elements. To approximate vacuum shell, a plate triangular element with 3 joint points and 5 parameters in the joint is used. It is obtained due to the unity of the bemded element and the element for the flat problem. To investigate nonstationary oscillations of vacuum chambers discreted on the basis of the method of final elements, it is suggested to use the numeric conversion of the Japlace transformation. On the basis of the algorithm suggested a program of numerical function conversion is developed. Test calculations have shown a good stability of the algorithm when selecting the values of transformation parameter in the range of lower intrinsic system frequencies. The advantage of the above method is in the fact that the time-structure shift function is found instantly in the form of the series for the whole time interval and does not require temporary steps, which bring about large expenses of counting time and error accumulation
Sriwana, I. K.; Marie, I. A.; Mangala, D.
2017-12-01
Kencana Gemilang, Co. is one electronics industry engaging in the manufacture sector. This company manufactures and assembles household electronic products, such as rice cooker, fan, iron, blender, etc. The company deals with an issue of underachievement of an established production target on MCM products line 1. This study aimed to calculate line efficiencies, delay times, and initial line smoothness indexes. The research was carried out by means of depicting a precedence diagram and gathering time data of each work element followed by examination and calculation of standard time as well as line balancing using methods of Moodie Young and Generics Algorithm. Based on results of calculation, better line balancing than the existing initial conditions, i.e. improvement in the line efficiency by 18.39%, deterioration in balanced delay by 28.39%, and deterioration of a smoothness index by 23.85% was obtained.
Directory of Open Access Journals (Sweden)
Marcelo Botelho da Costa Moraes
2012-10-01
Full Text Available This work aimed to apply genetic algorithms (GA and particle swarm optimization (PSO in cash balance management using Miller-Orr model, which consists in a stochastic model that does not define a single ideal point for cash balance, but an oscillation range between a lower bound, an ideal balance and an upper bound. Thus, this paper proposes the application of GA and PSO to minimize the Total Cost of cash maintenance, obtaining the parameter of the lower bound of the Miller-Orr model, using for this the assumptions presented in literature. Computational experiments were applied in the development and validation of the models. The results indicated that both the GA and PSO are applicable in determining the cash level from the lower limit, with best results of PSO model, which had not yet been applied in this type of problem.
A distributed scheduling algorithm for heterogeneous real-time systems
Zeineldine, Osman; El-Toweissy, Mohamed; Mukkamala, Ravi
1991-01-01
Much of the previous work on load balancing and scheduling in distributed environments was concerned with homogeneous systems and homogeneous loads. Several of the results indicated that random policies are as effective as other more complex load allocation policies. The effects of heterogeneity on scheduling algorithms for hard real time systems is examined. A distributed scheduler specifically to handle heterogeneities in both nodes and node traffic is proposed. The performance of the algorithm is measured in terms of the percentage of jobs discarded. While a random task allocation is very sensitive to heterogeneities, the algorithm is shown to be robust to such non-uniformities in system components and load.
Directory of Open Access Journals (Sweden)
Shuyu Dai
2018-01-01
Full Text Available Daily peak load forecasting is an important part of power load forecasting. The accuracy of its prediction has great influence on the formulation of power generation plan, power grid dispatching, power grid operation and power supply reliability of power system. Therefore, it is of great significance to construct a suitable model to realize the accurate prediction of the daily peak load. A novel daily peak load forecasting model, CEEMDAN-MGWO-SVM (Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Support Vector Machine Optimized by Modified Grey Wolf Optimization Algorithm, is proposed in this paper. Firstly, the model uses the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN algorithm to decompose the daily peak load sequence into multiple sub sequences. Then, the model of modified grey wolf optimization and support vector machine (MGWO-SVM is adopted to forecast the sub sequences. Finally, the forecasting sequence is reconstructed and the forecasting result is obtained. Using CEEMDAN can realize noise reduction for non-stationary daily peak load sequence, which makes the daily peak load sequence more regular. The model adopts the grey wolf optimization algorithm improved by introducing the population dynamic evolution operator and the nonlinear convergence factor to enhance the global search ability and avoid falling into the local optimum, which can better optimize the parameters of the SVM algorithm for improving the forecasting accuracy of daily peak load. In this paper, three cases are used to test the forecasting accuracy of the CEEMDAN-MGWO-SVM model. We choose the models EEMD-MGWO-SVM (Ensemble Empirical Mode Decomposition and Support Vector Machine Optimized by Modified Grey Wolf Optimization Algorithm, MGWO-SVM (Support Vector Machine Optimized by Modified Grey Wolf Optimization Algorithm, GWO-SVM (Support Vector Machine Optimized by Grey Wolf Optimization Algorithm, SVM (Support Vector
A 10 bit 200 MS/s pipeline ADC using loading-balanced architecture in 0.18 μm CMOS
Wang, Linfeng; Meng, Qiao; Zhi, Hao; Li, Fei
2017-07-01
A new loading-balanced architecture for high speed and low power consumption pipeline analog-to-digital converter (ADC) is presented in this paper. The proposed ADC uses SHA-less, op-amp and capacitor-sharing technique, capacitor-scaling scheme to reduce the die area and power consumption. A new capacitor-sharing scheme was proposed to cancel the extra reset phase of the feedback capacitors. The non-standard inter-stage gain increases the feedback factor of the first stage and makes it equal to the second stage, by which, the load capacitor of op-amp shared by the first and second stages is balanced. As for the fourth stage, the capacitor and op-amp no longer scale down. From the system’s point of view, all load capacitors of the shared OTAs are balanced by employing a loading-balanced architecture. The die area and power consumption are optimized maximally. The ADC is implemented in a 0.18 μm 1P6M CMOS technology, and occupies a die area of 1.2 × 1.2 mm{}2. The measurement results show a 55.58 dB signal-to-noise-and-distortion ratio (SNDR) and 62.97 dB spurious-free dynamic range (SFDR) with a 25 MHz input operating at a 200 MS/s sampling rate. The proposed ADC consumes 115 mW at 200 MS/s from a 1.8 V supply.
Shigaki, Leonardo; Vieira, Edgar Ramos; de Oliveira Gil, André Wilson; Araújo, Cynthia Gobbi Alves; Carmargo, Mariana Zingari; Sturion, Leandro Amaral; de Oliveira, Marcio Roǵerio; da Silva, Rubens A
2017-05-01
The purpose of this study was to assess the effect of holding an external load on the standing balance of younger and older adults with and without chronic low back pain (CLBP). Twenty participants with and 20 without CLBP participated in the study. Each group contained 10 younger (50% men) and 10 older adults (50% men). Participants were instructed to look straight ahead while standing on a force platform during two 120-second trials with and without holding an external load (10% of body mass). The center of pressure area, mean velocity, and mean frequency in the anteroposterior and mediolateral directions were measured. Older adults had worse standing balance than younger adults did (P external load significantly increased postural instability for both age groups and CLBP status, with mean effect size across center of pressure variables of d = 0.82 for older participants without CLBP and d = 2.65 for younger participants without CLBP. These effects for people with CLBP were d = 1.65 for subgroup of older and d = 1.60 for subgroup of younger participants. Holding an external load of 10% of body mass increased postural instability of both younger and older adults with and without CLBP. Copyright © 2017. Published by Elsevier Inc.
International Nuclear Information System (INIS)
Budny, Christoph; Madlener, Reinhard; Hilgers, Christoph
2015-01-01
Highlights: • Study of cost effectiveness of power-to-gas and storage of H 2 and renewable methane. • NPV analysis and Monte Carlo simulation to address fuel and electricity price risks. • Gas sale is compared with power and gas market arbitrage and balancing market gains. • Power-to-gas for linking the balancing markets for power and gas is not profitable. • Pipe storage is the preferred option for temporal arbitrage and balancing energy. - Abstract: This paper investigates the economic feasibility of power-to-gas (P2G) systems and gas storage options for both hydrogen and renewable methane. The study is based on a techno-economic model in which the net present value (NPV) method and Monte Carlo simulation of risks and price forward curves for the electricity and the gas market are used. We study three investment cases: a Base Case where the gas is directly sold in the market, a Storage & Arbitrage Case where temporal arbitrage opportunities between the electricity and the gas market are exploited, and a Storage & Balancing Case where the balancing markets (secondary reserve market for electricity, external balancing market for natural gas) are addressed. The optimal type and size of different centralized and decentralized storage facilities are determined and compared with each other. In a detailed sensitivity and cost analysis, we identify the key factors which could potentially improve the economic viability of the technological concepts assessed. We find that the P2G system used for bridging the balancing markets for power and gas cannot be operated profitably. For both, temporal arbitrage and balancing energy, pipe storage is preferred. Relatively high feed-in tariffs (100 € MW −1 for hydrogen, 130 € MW −1 for methane) are required to render pipe storage for P2G economically viable
International Nuclear Information System (INIS)
Koohi-Kamali, Sam; Rahim, N.A.; Mokhlis, H.
2014-01-01
Highlights: • A novel power management algorithm is developed. • An effective power smoothing index is derived. • Application of battery storage in smoothing the power fluctuations is investigated. • An applicable battery sizing and designing algorithm is proposed. • An efficient battery current control algorithm is designed. - Abstract: Integration of utility scaled solar electricity generator into power networks can negatively affect the performance of next generation smartgrid. Rapidly changing output power of this kind is unpredictable and thus one solution is to mitigate it by short-term to mid-term electrical storage systems like battery. The main objective of this paper is to propose a power management system (PMS) which is capable of suppressing these adverse impacts on the main supply. A smart microgrid (MG) including diesel, battery storage, and solar plants has been suggested for this purpose. MG is able to supply its local load based on operator decision and decline the power oscillations caused by solar system together with variable loads. A guideline algorithm is also proposed which helps to precisely design the battery plant. A novel application of time domain signal processing approach to filter oscillating output power of the solar plant is presented as well. In this case, a power smoothing index (PSI) is formulated, which considers both load and generation, and used to dispatch the battery plant. A droop reference estimator to schedule generation is also introduced where diesel plant can share the local load with grid. A current control algorithm is designed as well which adjusts for PSI to ensure battery current magnitude is allowable. MG along with its communication platform and PMS are simulated using PSCAD software. PMS is tested under different scenarios using real load profiles and environmental data in Malaysia to verify the operational abilities of proposed MG. The results indicate that PMS can effectively control the MG
Rohman, Muhamad Nur; Hidayat, Mas Irfan P.; Purniawan, Agung
2018-04-01
Neural networks (NN) have been widely used in application of fatigue life prediction. In the use of fatigue life prediction for polymeric-base composite, development of NN model is necessary with respect to the limited fatigue data and applicable to be used to predict the fatigue life under varying stress amplitudes in the different stress ratios. In the present paper, Multilayer-Perceptrons (MLP) model of neural network is developed, and Genetic Algorithm was employed to optimize the respective weights of NN for prediction of polymeric-base composite materials under variable amplitude loading. From the simulation result obtained with two different composite systems, named E-glass fabrics/epoxy (layups [(±45)/(0)2]S), and E-glass/polyester (layups [90/0/±45/0]S), NN model were trained with fatigue data from two different stress ratios, which represent limited fatigue data, can be used to predict another four and seven stress ratios respectively, with high accuracy of fatigue life prediction. The accuracy of NN prediction were quantified with the small value of mean square error (MSE). When using 33% from the total fatigue data for training, the NN model able to produce high accuracy for all stress ratios. When using less fatigue data during training (22% from the total fatigue data), the NN model still able to produce high coefficient of determination between the prediction result compared with obtained by experiment.
Directory of Open Access Journals (Sweden)
Mauricio Granada Echeverri
2012-06-01
Full Text Available Unbalanced operation of distribution systems deteriorates power quality andincreases investment and operation costs. Feeder reconfiguration and phaseswapping are the two main approaches for load balancing, being the formermore difficult to execute due to the reduced number of sectionalizing switchesavailable in most distribution systems. On the other hand, phase swappingconstitutes a direct, effective and low cost alternative for load balancing. The main contribution of this paper is the proposal of an optimization model anda solution technique for phase balancing planning in distribution systems. Asregards the optimization model, a mixed integer nonlinear programming formulationis proposed. On the other hand, the proposed solution techniqueconsists on a specialized genetic algorithm. To show the effectiveness of theproposed approach, several tests are carried out with two distribution systemsof 37 and 19 buses, this last one with different load models. Results showedthat in addition to the achievement of the primary objective of loss reduction,phase balancing allows obtaining other technical benefits such as improvementof voltage profile and alleviation of congested lines.La operación desbalanceada de los sistemas de distribución deteriora la calidad de la potencia y aumenta los costos de inversión y operación. La reconﬁguración de alimentadores y el intercambio de fases son los dos principales enfoques para balance de fases, siendo el primero más difícil de llevar a cabo debido al número reducido de seccionalizadores disponibles en la mayoría de los sistemas de distribución. Por otro lado, el intercambio de fases constituye una alternativa directa, efectiva y de bajo costo para el balance de fases. La contribución principal de este artículo es la propuesta de un modelo de optimización y una técnica de solución para el planeamiento de balance de fases en sistemas de distribución. En cuanto al modelo de optimización, se
Energy Technology Data Exchange (ETDEWEB)
Tom, Nathan M [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Yu, Yi-Hsiang [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Wright, Alan D [National Renewable Energy Laboratory (NREL), Golden, CO (United States)
2017-09-28
This work attempts to balance power absorption against structural loading for a novel variable geometry wave energy converter. The variable geometry consists of four identical flaps that will be opened in ascending order starting with the flap closest to the seafloor and moving to the free surface. The influence of a pitch motion constraint on power absorption when utilizing a nonideal power take-off (PTO) is examined and found to reduce the losses associated with bidirectional energy flow. The power-to-load ratio is evaluated using pseudo-spectral control to determine the optimum PTO torque based on a multiterm objective function. The pseudo-spectral optimal control problem is extended to include load metrics in the objective function, which may now consist of competing terms. Separate penalty weights are attached to the surge-foundation force and PTO control torque to tune the optimizer performance to emphasize either power absorption or load shedding. PTO efficiency is not included in the objective function, but the penalty weights are utilized to limit the force and torque amplitudes, thereby reducing losses associated with bidirectional energy flow. Results from pseudo-spectral control demonstrate that shedding a portion of the available wave energy can provide greater reductions in structural loads and reactive power.
Manodham, Thavisak; Loyola, Luis; Miki, Tetsuya
IEEE 802.11 wirelesses LANs (WLANs) have been rapidly deployed in enterprises, public areas, and households. Voice-over-IP (VoIP) and similar applications are now commonly used in mobile devices over wireless networks. Recent works have improved the quality of service (QoS) offering higher data rates to support various kinds of real-time applications. However, besides the need for higher data rates, seamless handoff and load balancing among APs are key issues that must be addressed in order to continue supporting real-time services across wireless LANs and providing fair services to all users. In this paper, we introduce a novel access point (AP) with two transceivers that improves network efficiency by supporting seamless handoff and traffic load balancing in a wireless network. In our proposed scheme, the novel AP uses the second transceiver to scan and find neighboring STAs in the transmission range and then sends the results to neighboring APs, which compare and analyze whether or not the STA should perform a handoff. The initial results from our simulations show that the novel AP module is more effective than the conventional scheme and a related work in terms of providing a handoff process with low latency and sharing traffic load with neighbor APs.
A NetCDF version of the two-dimensional energy balance model based on the full multigrid algorithm
Zhuang, Kelin; North, Gerald R.; Stevens, Mark J.
A NetCDF version of the two-dimensional energy balance model based on the full multigrid method in Fortran is introduced for both pedagogical and research purposes. Based on the land-sea-ice distribution, orbital elements, greenhouse gases concentration, and albedo, the code calculates the global seasonal surface temperature. A step-by-step guide with examples is provided for practice.
Karpievitch, Yuliya V; Almeida, Jonas S
2006-03-15
Matlab, a powerful and productive language that allows for rapid prototyping, modeling and simulation, is widely used in computational biology. Modeling and simulation of large biological systems often require more computational resources then are available on a single computer. Existing distributed computing environments like the Distributed Computing Toolbox, MatlabMPI, Matlab*G and others allow for the remote (and possibly parallel) execution of Matlab commands with varying support for features like an easy-to-use application programming interface, load-balanced utilization of resources, extensibility over the wide area network, and minimal system administration skill requirements. However, all of these environments require some level of access to participating machines to manually distribute the user-defined libraries that the remote call may invoke. mGrid augments the usual process distribution seen in other similar distributed systems by adding facilities for user code distribution. mGrid's client-side interface is an easy-to-use native Matlab toolbox that transparently executes user-defined code on remote machines (i.e. the user is unaware that the code is executing somewhere else). Run-time variables are automatically packed and distributed with the user-defined code and automated load-balancing of remote resources enables smooth concurrent execution. mGrid is an open source environment. Apart from the programming language itself, all other components are also open source, freely available tools: light-weight PHP scripts and the Apache web server. Transparent, load-balanced distribution of user-defined Matlab toolboxes and rapid prototyping of many simple parallel applications can now be done with a single easy-to-use Matlab command. Because mGrid utilizes only Matlab, light-weight PHP scripts and the Apache web server, installation and configuration are very simple. Moreover, the web-based infrastructure of mGrid allows for it to be easily extensible over
Saito, Masatoshi
2010-08-01
This article describes the spectral optimization of dual-energy computed tomography using balanced filters (bf-DECT) to reduce the tube loadings and dose by dedicating to the acquisition of electron density information, which is essential for treatment planning in radiotherapy. For the spectral optimization of bf-DECT, the author calculated the beam-hardening error and air kerma required to achieve a desired noise level in an electron density image of a 50-cm-diameter cylindrical water phantom. The calculation enables the selection of beam parameters such as tube voltage, balanced filter material, and its thickness. The optimal combination of tube voltages was 80 kV/140 kV in conjunction with Tb/Hf and Bi/Mo filter pairs; this combination agrees with that obtained in a previous study [M. Saito, "Spectral optimization for measuring electron density by the dual-energy computed tomography coupled with balanced filter method," Med. Phys. 36, 3631-3642 (2009)], although the thicknesses of the filters that yielded a minimum tube output were slightly different from those obtained in the previous study. The resultant tube loading of a low-energy scan of the present bf-DECT significantly decreased from 57.5 to 4.5 times that of a high-energy scan for conventional DECT. Furthermore, the air kerma of bf-DECT could be reduced to less than that of conventional DECT, while obtaining the same figure of merit for the measurement of electron density and effective atomic number. The tube-loading and dose efficiencies of bf-DECT were considerably improved by sacrificing the quality of the noise level in the images of effective atomic number.
Directory of Open Access Journals (Sweden)
Almeida Jonas S
2006-03-01
Full Text Available Abstract Background Matlab, a powerful and productive language that allows for rapid prototyping, modeling and simulation, is widely used in computational biology. Modeling and simulation of large biological systems often require more computational resources then are available on a single computer. Existing distributed computing environments like the Distributed Computing Toolbox, MatlabMPI, Matlab*G and others allow for the remote (and possibly parallel execution of Matlab commands with varying support for features like an easy-to-use application programming interface, load-balanced utilization of resources, extensibility over the wide area network, and minimal system administration skill requirements. However, all of these environments require some level of access to participating machines to manually distribute the user-defined libraries that the remote call may invoke. Results mGrid augments the usual process distribution seen in other similar distributed systems by adding facilities for user code distribution. mGrid's client-side interface is an easy-to-use native Matlab toolbox that transparently executes user-defined code on remote machines (i.e. the user is unaware that the code is executing somewhere else. Run-time variables are automatically packed and distributed with the user-defined code and automated load-balancing of remote resources enables smooth concurrent execution. mGrid is an open source environment. Apart from the programming language itself, all other components are also open source, freely available tools: light-weight PHP scripts and the Apache web server. Conclusion Transparent, load-balanced distribution of user-defined Matlab toolboxes and rapid prototyping of many simple parallel applications can now be done with a single easy-to-use Matlab command. Because mGrid utilizes only Matlab, light-weight PHP scripts and the Apache web server, installation and configuration are very simple. Moreover, the web
Schuster, David M.; Panda, Jayanta; Ross, James C.; Roozeboom, Nettie H.; Burnside, Nathan J.; Ngo, Christina L.; Kumagai, Hiro; Sellers, Marvin; Powell, Jessica M.; Sekula, Martin K.;
2016-01-01
This NESC assessment examined the accuracy of estimating buffet loads on in-line launch vehicles without booster attachments using sparse unsteady pressure measurements. The buffet loads computed using sparse sensor data were compared with estimates derived using measurements with much higher spatial resolution. The current method for estimating launch vehicle buffet loads is through wind tunnel testing of models with approximately 400 unsteady pressure transducers. Even with this relatively large number of sensors, the coverage can be insufficient to provide reliable integrated unsteady loads on vehicles. In general, sparse sensor spacing requires the use of coherence-length-based corrections in the azimuthal and axial directions to integrate the unsteady pressures and obtain reasonable estimates of the buffet loads. Coherence corrections have been used to estimate buffet loads for a variety of launch vehicles with the assumption methodology results in reasonably conservative loads. For the Space Launch System (SLS), the first estimates of buffet loads exceeded the limits of the vehicle structure, so additional tests with higher sensor density were conducted to better define the buffet loads and possibly avoid expensive modifications to the vehicle design. Without the additional tests and improvements to the coherence-length analysis methods, there would have been significant impacts to the vehicle weight, cost, and schedule. If the load estimates turn out to be too low, there is significant risk of structural failure of the vehicle. This assessment used a combination of unsteady pressure-sensitive paint (uPSP), unsteady pressure transducers, and a dynamic force and moment balance to investigate the integration schemes used with limited unsteady pressure data by comparing them with direct integration of extremely dense fluctuating pressure measurements. An outfall of the assessment was to evaluate the potential of using the emerging uPSP technique in a production
Optimal Load Control via Frequency Measurement and Neighborhood Area Communication
Energy Technology Data Exchange (ETDEWEB)
Zhao, CH; Topcu, U; Low, SH
2013-11-01
We propose a decentralized optimal load control scheme that provides contingency reserve in the presence of sudden generation drop. The scheme takes advantage of flexibility of frequency responsive loads and neighborhood area communication to solve an optimal load control problem that balances load and generation while minimizing end-use disutility of participating in load control. Local frequency measurements enable individual loads to estimate the total mismatch between load and generation. Neighborhood area communication helps mitigate effects of inconsistencies in the local estimates due to frequency measurement noise. Case studies show that the proposed scheme can balance load with generation and restore the frequency within seconds of time after a generation drop, even when the loads use a highly simplified power system model in their algorithms. We also investigate tradeoffs between the amount of communication and the performance of the proposed scheme through simulation-based experiments.
Directory of Open Access Journals (Sweden)
Jin-peng Liu
2017-07-01
Full Text Available Short-term power load forecasting is an important basis for the operation of integrated energy system, and the accuracy of load forecasting directly affects the economy of system operation. To improve the forecasting accuracy, this paper proposes a load forecasting system based on wavelet least square support vector machine and sperm whale algorithm. Firstly, the methods of discrete wavelet transform and inconsistency rate model (DWT-IR are used to select the optimal features, which aims to reduce the redundancy of input vectors. Secondly, the kernel function of least square support vector machine LSSVM is replaced by wavelet kernel function for improving the nonlinear mapping ability of LSSVM. Lastly, the parameters of W-LSSVM are optimized by sperm whale algorithm, and the short-term load forecasting method of W-LSSVM-SWA is established. Additionally, the example verification results show that the proposed model outperforms other alternative methods and has a strong effectiveness and feasibility in short-term power load forecasting.
A NetCDF version of the two-dimensional energy balance model based on the full multigrid algorithm
Directory of Open Access Journals (Sweden)
Kelin Zhuang
2017-01-01
Full Text Available A NetCDF version of the two-dimensional energy balance model based on the full multigrid method in Fortran is introduced for both pedagogical and research purposes. Based on the land–sea–ice distribution, orbital elements, greenhouse gases concentration, and albedo, the code calculates the global seasonal surface temperature. A step-by-step guide with examples is provided for practice.
International Nuclear Information System (INIS)
Yang, Fangfang; Xing, Yinjiao; Wang, Dong; Tsui, Kwok-Leung
2016-01-01
Highlights: • Three different model-based filtering algorithms for SOC estimation are compared. • A combined dynamic loading profile is proposed to evaluate the three algorithms. • Robustness against uncertainty of initial states of SOC estimators are investigated. • Battery capacity degradation is considered in SOC estimation. - Abstract: Accurate state-of-charge (SOC) estimation is critical for the safety and reliability of battery management systems in electric vehicles. Because SOC cannot be directly measured and SOC estimation is affected by many factors, such as ambient temperature, battery aging, and current rate, a robust SOC estimation approach is necessary to be developed so as to deal with time-varying and nonlinear battery systems. In this paper, three popular model-based filtering algorithms, including extended Kalman filter, unscented Kalman filter, and particle filter, are respectively used to estimate SOC and their performances regarding to tracking accuracy, computation time, robustness against uncertainty of initial values of SOC, and battery degradation, are compared. To evaluate the performances of these algorithms, a new combined dynamic loading profile composed of the dynamic stress test, the federal urban driving schedule and the US06 is proposed. The comparison results showed that the unscented Kalman filter is the most robust to different initial values of SOC, while the particle filter owns the fastest convergence ability when an initial guess of SOC is far from a true initial SOC.
Directory of Open Access Journals (Sweden)
Wei Sun
2015-01-01
Full Text Available Electric power is a kind of unstorable energy concerning the national welfare and the people’s livelihood, the stability of which is attracting more and more attention. Because the short-term power load is always interfered by various external factors with the characteristics like high volatility and instability, a single model is not suitable for short-term load forecasting due to low accuracy. In order to solve this problem, this paper proposes a new model based on wavelet transform and the least squares support vector machine (LSSVM which is optimized by fruit fly algorithm (FOA for short-term load forecasting. Wavelet transform is used to remove error points and enhance the stability of the data. Fruit fly algorithm is applied to optimize the parameters of LSSVM, avoiding the randomness and inaccuracy to parameters setting. The result of implementation of short-term load forecasting demonstrates that the hybrid model can be used in the short-term forecasting of the power system.
Energy Technology Data Exchange (ETDEWEB)
Tom, Nathan M.; Madhi, Farshad; Yeung, Ronald W.
2016-07-01
The aim of this paper is to maximize the power-to-load ratio of the Berkeley Wedge: a one-degree-of-freedom, asymmetrical, energy-capturing, floating breakwater of high performance that is relatively free of viscosity effects. Linear hydrodynamic theory was used to calculate bounds on the expected time-averaged power (TAP) and corresponding surge restraining force, pitch restraining torque, and power take-off (PTO) control force when assuming that the heave motion of the wave energy converter remains sinusoidal. This particular device was documented to be an almost-perfect absorber if one-degree-of-freedom motion is maintained. The success of such or similar future wave energy converter technologies would require the development of control strategies that can adapt device performance to maximize energy generation in operational conditions while mitigating hydrodynamic loads in extreme waves to reduce the structural mass and overall cost. This paper formulates the optimal control problem to incorporate metrics that provide a measure of the surge restraining force, pitch restraining torque, and PTO control force. The optimizer must now handle an objective function with competing terms in an attempt to maximize power capture while minimizing structural and actuator loads. A penalty weight is placed on the surge restraining force, pitch restraining torque, and PTO actuation force, thereby allowing the control focus to be placed either on power absorption or load mitigation. Thus, in achieving these goals, a per-unit gain in TAP would not lead to a greater per-unit demand in structural strength, hence yielding a favorable benefit-to-cost ratio. Demonstrative results in the form of TAP, reactive TAP, and the amplitudes of the surge restraining force, pitch restraining torque, and PTO control force are shown for the Berkeley Wedge example.
Institute of Scientific and Technical Information of China (English)
郭小宝; 赵振; 陈落根; 张东海
2015-01-01
In the process of heavy load palletizing robot work,large swing arm drooping frequent cause the motor to overcome the gravitational potential energy work constantly which leads to the motor torque fluctuation and huge invalid work.These affect the service life of motor drive and parts costs increasing.In this article from the perspective of energy balance,of arm can drive the movement of the coupling relationship between many parts are analyzed in detail ,balance device when the stored elastic energy change in gravitational poten-tial energy of release or storage is designed so as to achieve the gravitational potential energy balance complete-ly,and implement all the energy of the motor drive is used to transfer the motion of the moving parts,avoid the gravitational potential energy of irrational consumption.Finally Lagrange equation and general expression of gravity balance optimization algorithm are obtained.%在重载码垛机器人的工作过程中，大臂的频繁上升摆动使得电机要不断克服重力势能做功，导致电机扭矩出现波动和克服重力导致驱动能量的耗散，这将影响电机和驱动器的寿命，造成零部件成本提高。从能量平衡的角度，详细分析大臂驱动的众多零部件之间的运动耦合关系，设计并分析平衡装置存储弹性势能在重力势能发生变化时的释放或存储，从而达到重力势能完全平衡，实现电机驱动的能量全部用于运动部件的动能传递，避免重力势能的无端消耗。最后采用拉格朗日方程得出重力平衡的通用表达式和优化算法。
Xu, Lina; O'Hare, Gregory M P; Collier, Rem
2017-07-05
Wireless Sensor Networks (WSNs) are typically composed of thousands of sensors powered by limited energy resources. Clustering techniques were introduced to prolong network longevity offering the promise of green computing. However, most existing work fails to consider the network coverage when evaluating the lifetime of a network. We believe that balancing the energy consumption in per unit area rather than on each single sensor can provide better-balanced power usage throughout the network. Our former work-Balanced Energy-Efficiency (BEE) and its Multihop version BEEM can not only extend the network longevity, but also maintain the network coverage. Following WSNs, Internet of Things (IoT) technology has been proposed with higher degree of diversities in terms of communication abilities and user scenarios, supporting a large range of real world applications. The IoT devices are embedded with multiple communication interfaces, normally referred as Multiple-In and Multiple-Out (MIMO) in 5G networks. The applications running on those devices can generate various types of data. Every interface has its own characteristics, which may be preferred and beneficial in some specific user scenarios. With MIMO becoming more available on the IoT devices, an advanced clustering solution for highly dynamic IoT systems is missing and also pressingly demanded in order to cater for differing user applications. In this paper, we present a smart clustering algorithm (Smart-BEEM) based on our former work BEE(M) to accomplish energy efficient and Quality of user Experience (QoE) supported communication in cluster based IoT networks. It is a user behaviour and context aware approach, aiming to facilitate IoT devices to choose beneficial communication interfaces and cluster headers for data transmission. Experimental results have proved that Smart-BEEM can further improve the performance of BEE and BEEM for coverage sensitive longevity.
O’Hare, Gregory M. P.; Collier, Rem
2017-01-01
Wireless Sensor Networks (WSNs) are typically composed of thousands of sensors powered by limited energy resources. Clustering techniques were introduced to prolong network longevity offering the promise of green computing. However, most existing work fails to consider the network coverage when evaluating the lifetime of a network. We believe that balancing the energy consumption in per unit area rather than on each single sensor can provide better-balanced power usage throughout the network. Our former work—Balanced Energy-Efficiency (BEE) and its Multihop version BEEM can not only extend the network longevity, but also maintain the network coverage. Following WSNs, Internet of Things (IoT) technology has been proposed with higher degree of diversities in terms of communication abilities and user scenarios, supporting a large range of real world applications. The IoT devices are embedded with multiple communication interfaces, normally referred as Multiple-In and Multiple-Out (MIMO) in 5G networks. The applications running on those devices can generate various types of data. Every interface has its own characteristics, which may be preferred and beneficial in some specific user scenarios. With MIMO becoming more available on the IoT devices, an advanced clustering solution for highly dynamic IoT systems is missing and also pressingly demanded in order to cater for differing user applications. In this paper, we present a smart clustering algorithm (Smart-BEEM) based on our former work BEE(M) to accomplish energy efficient and Quality of user Experience (QoE) supported communication in cluster based IoT networks. It is a user behaviour and context aware approach, aiming to facilitate IoT devices to choose beneficial communication interfaces and cluster headers for data transmission. Experimental results have proved that Smart-BEEM can further improve the performance of BEE and BEEM for coverage sensitive longevity. PMID:28678164
Directory of Open Access Journals (Sweden)
Milosz Ciznicki
2015-01-01
Full Text Available The recent advent of novel multi- and many-core architectures forces application programmers to deal with hardware-specific implementation details and to be familiar with software optimisation techniques to benefit from new high-performance computing machines. Extra care must be taken for communication-intensive algorithms, which may be a bottleneck for forthcoming era of exascale computing. This paper aims to present a high-level stencil framework implemented for the EULerian or LAGrangian model (EULAG that efficiently utilises multi- and many-cores architectures. Only an efficient usage of both many-core processors (CPUs and graphics processing units (GPUs with the flexible data decomposition method can lead to the maximum performance that scales the communication-intensive Generalized Conjugate Residual (GCR elliptic solver with preconditioner.
Baiges Aznar, Joan; Bayona Roa, Camilo Andrés
2017-01-01
No separate or additional fees are collected for access to or distribution of the work. In this paper we present a novel algorithm for adaptive mesh refinement in computational physics meshes in a distributed memory parallel setting. The proposed method is developed for nodally based parallel domain partitions where the nodes of the mesh belong to a single processor, whereas the elements can belong to multiple processors. Some of the main features of the algorithm presented in this paper a...
WSN ene rgy balance multi-hop lc ustering routing algorithm%能量均衡多跳分簇路由算法
Institute of Scientific and Technical Information of China (English)
叶润; 王缓缓
2014-01-01
The lifetime of ZigBee wireless sensor network is directly related to energy consumption of nodes .In order to extend the life of the network, the clustering routing methods are used.The improved clustering routing algo-rithm-EBMHC ( energy balance multi-hop clustering routing algorithm) , which adopts centralized rotation-cluste-ring method and distributed competition method of cluster head.This makes the network’ s idle nodes sleep and cluster head node work acting as multiple transmission.It also has data fusion and routing maintenance in a single cycle, so as to make full and effective use of network energy.Hierarchical management can solve imbalance of net-work node energy consumption.The simulation shows that EBMHC algorithm outperforms LEACH and SEP, making the network energy consumption more balanced and prolonging the network lifetime.%ZigBee无线传感器网络的生存寿命与节点的能耗直接相关。为了延长网络的寿命，通常采用分簇路由方法。通过集中成簇管理以及分布簇头竞争的能量均衡多跳分簇路由算法EBMHC（ energy balance multi－hop clustering rou-ting algorithm），在一个周期内，使得网络空闲节点休眠，簇头节点担任多条传输、数据融合以及路由维护的功能，以充分有效利用网络能量。分层管理方式可以缓解网络节点能耗不均衡问题。通过仿真表明， EBMHC算法优于LEACH和SEP算法，使网络能耗更均衡，延长了网络生存周期。
Directory of Open Access Journals (Sweden)
Afsaneh Mozaffari
2012-08-01
Full Text Available The success of each organization depends undoubtedly on the quality of its management and management quality depends on decision quality and information quality on the quality of its measurement and proportion. Therefore, its accuracy and measurement has a key role in the success of the organization and the weakness of performance evaluation and managerial control system can transfer to a barrier for the growth of organization. Performance evaluation systems are now dividable to two traditional group (performance evaluation of an individual across reminding him about his performance and modern group (developing and improving the capacity of evaluated individual and inclined to achievement of organizational objectives and strategies. One of the most authoritative strategic models in this field is the balanced scorecard (BSC model in which entire aspects of an organization are dominantly investigated. However, no operational trend has been introduced for utilizing it up to now. In this paper, an operational trend is introduced to apply the foundations of BSC model and multiple criteria decision making (MCDM techniques. The most important goal of researchers in representation of new structure for creating development and growth capacity and permanent improvement is associated by a kind of providence, such that it can develop desirable organizational and work behaviors towards achieving the objectives and strategies of the organization. In addition, the strategic planning of Islamic Azad university of Semnan was modeled by suggested structure to validate the suggested structure's capacities. The results showed that outputs were more tangible for the personnel of the organization and the results were accepted by the managers of Islamic Azad university of Semnan.
International Nuclear Information System (INIS)
Giakoumis, E.G.
2007-01-01
During the last decades there has been an increasing interest in the low heat rejection (LHR) diesel engine. In an LHR engine, an increased level of temperatures inside the cylinder is achieved, resulting from the insulation applied to the walls. The steady-state, LHR engine operation has been studied so far by applying either first- or second-law balances. Only a few works, however, have treated this subject during the very important transient operation with the results limited to the engine speed response. To this aim an experimentally validated transient diesel engine simulation code has been expanded so as to include the second-law balance. Two common insulators for the engine in hand, i.e. silicon nitride and plasma spray zirconia are studied and their effect is compared to the nominal non-insulated operation from the first- and second-law perspective. It is revealed that after a step increase in load, the second-law values unlike the first-law ones are heavily impacted by the insulation scheme applied. Combustion and total engine irreversibilities decrease significantly (up to 23% for the cases examined) with increasing insulation. Unfortunately, this decrease is not transformed into an increase in the mechanical work but rather increases the potential for extra work recovery owing to the higher availability content of the exhaust gas
Energy Technology Data Exchange (ETDEWEB)
Szendrei, Danny [Westsaechsische Hochschule Zwickau (Germany)
2010-07-01
To date, measures and concepts for saving energy become more and more important. The development of prices for conventional energy sources forces public and private households and businesses to changes in consumer behaviour and purchasing behaviour. Due to the structural infrastructure, the housing construction in communes strongly is affected by these developments. Nearly 35 % of the total energy demand in Europe account for heating of buildings generally. The most common type of heating system for heating of residential buildings is the central hot water heating in the two-tube version. It is assumed that nearly 90 % of the operated plants have a hydraulic unbalance. Additionally, balanced heating systems fulfil the desired efficiency only under certain, structural design conditions. The integration of the control of heating systems in the smart home infrastructure or KNX infrastructure enables a building-independent, tunable heat supply between buildings and consumption acquisition. The hydraulic system loads can be optimized simultaneously via the direct access to the control value. Thus, a homogeneous mass distribution over the plant can be guaranteed which is derived from the dynamic needs of the system users. These heat loads are calculated by the KNX system and the application of HeatingControl.
Directory of Open Access Journals (Sweden)
Romanova Victoria
2017-01-01
Full Text Available This publication considers the issues of development of the software program for designing of 0,4 kV power supply systems with motor-actuated load under voltage unsymmetry conditions (using the example of the Trans-Baikal Territory. Voltage unsymmetry is practically constant phenomenon in the electric power networks of different voltage types. Voltage unsymmetry effects significantly the electric power consumers, including the supply mains itself. It has especially negative impact on the electrical equipment operation process and its lifetime. The urgency of the problem is confirmed by multiple research on the same topic and by significant number of damages suffered by the electric power consumers staying in service (especially in the Trans-Baikal Territory and in the Far-East regions. Voltage unsymmetry causes economic loss and reduction of the electromagnetic interference value by the voltage unsymmetry coefficient in negative-phase sequence (K2U gives inevitable economic effect accordingly. However, the payback period for the activities aimed at reduction of electromagnetic interference, will vary from some months to several years. The more accurate value of the payback period may be obtained using the developed software program. The developed software design program is implemented by means of the programming language C# in Microsoft Visual Studio environment, using the built-in cross-platform database SQLite. The software program shall allow making quick and accurate calculation of the power losses, to determine the economic feasibility of provision special measures for removal of the voltage unsymmetry, for determination of optimal application and location of the balancing devices. The software implementation in power systems loaded with electric motors will improve reliability and efficiency of asynchronous motors. The software is of interest for developers of projects on power supply systems for regions with non-linear loads.
Monte Carlo methods beyond detailed balance
Schram, Raoul D.; Barkema, Gerard T.|info:eu-repo/dai/nl/101275080
2015-01-01
Monte Carlo algorithms are nearly always based on the concept of detailed balance and ergodicity. In this paper we focus on algorithms that do not satisfy detailed balance. We introduce a general method for designing non-detailed balance algorithms, starting from a conventional algorithm satisfying
Directory of Open Access Journals (Sweden)
Y.N. Vijay Kumar
2016-12-01
Full Text Available The utilization of electrical energy due to urbanization and industrialization is increasing day by day, and due to this, there is chance of increasing the uncertainties in a given power system and that affects the economy of the country. The conventional power system in the presence of flexible AC transmission system (FACTS controllers is an alternative to solve this problem and can increase the power system capability to handle rapid changes in operating conditions of the system. In general, multi-line FACTS controllers are effective than single line FACTS controllers. In this paper, a detailed mathematical modeling of IPFC is presented and the effect of an optimal location is also analyzed. A novel optimization algorithm i.e. modified BAT algorithm is proposed to solve optimal power flow problem in the presence of IPFC including system constraints and device limits. The proposed methodology has been tested on standard test systems.
Enabling high performance computational science through combinatorial algorithms
International Nuclear Information System (INIS)
Boman, Erik G; Bozdag, Doruk; Catalyurek, Umit V; Devine, Karen D; Gebremedhin, Assefaw H; Hovland, Paul D; Pothen, Alex; Strout, Michelle Mills
2007-01-01
The Combinatorial Scientific Computing and Petascale Simulations (CSCAPES) Institute is developing algorithms and software for combinatorial problems that play an enabling role in scientific and engineering computations. Discrete algorithms will be increasingly critical for achieving high performance for irregular problems on petascale architectures. This paper describes recent contributions by researchers at the CSCAPES Institute in the areas of load balancing, parallel graph coloring, performance improvement, and parallel automatic differentiation
Enabling high performance computational science through combinatorial algorithms
Energy Technology Data Exchange (ETDEWEB)
Boman, Erik G [Discrete Algorithms and Math Department, Sandia National Laboratories (United States); Bozdag, Doruk [Biomedical Informatics, and Electrical and Computer Engineering, Ohio State University (United States); Catalyurek, Umit V [Biomedical Informatics, and Electrical and Computer Engineering, Ohio State University (United States); Devine, Karen D [Discrete Algorithms and Math Department, Sandia National Laboratories (United States); Gebremedhin, Assefaw H [Computer Science and Center for Computational Science, Old Dominion University (United States); Hovland, Paul D [Mathematics and Computer Science Division, Argonne National Laboratory (United States); Pothen, Alex [Computer Science and Center for Computational Science, Old Dominion University (United States); Strout, Michelle Mills [Computer Science, Colorado State University (United States)
2007-07-15
The Combinatorial Scientific Computing and Petascale Simulations (CSCAPES) Institute is developing algorithms and software for combinatorial problems that play an enabling role in scientific and engineering computations. Discrete algorithms will be increasingly critical for achieving high performance for irregular problems on petascale architectures. This paper describes recent contributions by researchers at the CSCAPES Institute in the areas of load balancing, parallel graph coloring, performance improvement, and parallel automatic differentiation.
Nature-inspired optimization algorithms
Yang, Xin-She
2014-01-01
Nature-Inspired Optimization Algorithms provides a systematic introduction to all major nature-inspired algorithms for optimization. The book's unified approach, balancing algorithm introduction, theoretical background and practical implementation, complements extensive literature with well-chosen case studies to illustrate how these algorithms work. Topics include particle swarm optimization, ant and bee algorithms, simulated annealing, cuckoo search, firefly algorithm, bat algorithm, flower algorithm, harmony search, algorithm analysis, constraint handling, hybrid methods, parameter tuning
A Novel Control Strategy for Autonomous Operation of Isolated Microgrid with Prioritized Loads
Kumar, R. Hari; Ushakumari, S.
2018-05-01
Maintenance of power balance between generation and demand is one of the most critical requirements for the stable operation of a power system network. To mitigate the power imbalance during the occurrence of any disturbance in the system, fast acting algorithms are inevitable. This paper proposes a novel algorithm for load shedding and network reconfiguration in an isolated microgrid with prioritized loads and multiple islands, which will help to quickly restore the system in the event of a fault. The performance of the proposed algorithm is enhanced using genetic algorithm and its effectiveness is illustrated with simulation results on modified Consortium for Electric Reliability Technology Solutions (CERTS) microgrid.
International Nuclear Information System (INIS)
Kuznetsov, D.V.; Kormilitsyn, V.M.; Proskuryakov, K.N.
2010-01-01
Calculation results of acoustic parameters fluctuations in low-pressure regenerative heating system of NPP with WWER-1000 type reactor were presented. The spectral structure of acoustic fluctuations was shown to depend on configuration of secondary circuit equipment, its geometrical sizes and operation mode. Estimations of natural oscillations frequencies of working medium pressure in the secondary circuit equipment were resulted. The developed calculation methods and algorithms are intended for revealing and prevention of initiation conditions of vibrations resonances in elements of the secondary circuit equipment with acoustic oscillations in working medium, both under operating conditions and in the design stage of the second circuit of NPP with WWER-1000 type reactor. Analysis of pass-band dependence on operation mode was carried out to solve the given problem [ru
Asymptotically optimal load balancing topologies
Mukherjee, D.; Borst, S.C.; van Leeuwaarden, J.S.H.
2017-01-01
We consider a system of N servers inter-connected by some underlying graph topology G N . Tasks arrive at the various servers as independent Poisson processes of rate λ . Each incoming task is irrevocably assigned to whichever server has the smallest number of tasks among the one where it appears
Ghaedi, M.; Azad, F. Nasiri; Dashtian, K.; Hajati, S.; Goudarzi, A.; Soylak, M.
2016-10-01
Maximum malachite green (MG) adsorption onto ZnO Nanorod-loaded activated carbon (ZnO-NR-AC) was achieved following the optimization of conditions, while the mass transfer was accelerated by ultrasonic. The central composite design (CCD) and genetic algorithm (GA) were used to estimate the effect of individual variables and their mutual interactions on the MG adsorption as response and to optimize the adsorption process. The ZnO-NR-AC surface morphology and its properties were identified via FESEM, XRD and FTIR. The adsorption equilibrium isotherm and kinetic models investigation revealed the well fit of the experimental data to Langmuir isotherm and pseudo-second-order kinetic model, respectively. It was shown that a small amount of ZnO-NR-AC (with adsorption capacity of 20 mg g- 1) is sufficient for the rapid removal of high amount of MG dye in short time (3.99 min).
A parallel neural network training algorithm for control of discrete dynamical systems.
Energy Technology Data Exchange (ETDEWEB)
Gordillo, J. L.; Hanebutte, U. R.; Vitela, J. E.
1998-01-20
In this work we present a parallel neural network controller training code, that uses MPI, a portable message passing environment. A comprehensive performance analysis is reported which compares results of a performance model with actual measurements. The analysis is made for three different load assignment schemes: block distribution, strip mining and a sliding average bin packing (best-fit) algorithm. Such analysis is crucial since optimal load balance can not be achieved because the work load information is not available a priori. The speedup results obtained with the above schemes are compared with those corresponding to the bin packing load balance scheme with perfect load prediction based on a priori knowledge of the computing effort. Two multiprocessor platforms: a SGI/Cray Origin 2000 and a IBM SP have been utilized for this study. It is shown that for the best load balance scheme a parallel efficiency of over 50% for the entire computation is achieved by 17 processors of either parallel computers.
Wang, Yaping; Lin, Shunjiang; Yang, Zhibin
2017-05-01
In the traditional three-phase power flow calculation of the low voltage distribution network, the load model is described as constant power. Since this model cannot reflect the characteristics of actual loads, the result of the traditional calculation is always different from the actual situation. In this paper, the load model in which dynamic load represented by air conditioners parallel with static load represented by lighting loads is used to describe characteristics of residents load, and the three-phase power flow calculation model is proposed. The power flow calculation model includes the power balance equations of three-phase (A,B,C), the current balance equations of phase 0, and the torque balancing equations of induction motors in air conditioners. And then an alternating iterative algorithm of induction motor torque balance equations with each node balance equations is proposed to solve the three-phase power flow model. This method is applied to an actual low voltage distribution network of residents load, and by the calculation of three different operating states of air conditioners, the result demonstrates the effectiveness of the proposed model and the algorithm.
Energy Technology Data Exchange (ETDEWEB)
Rodriguez-MartInez R; Lugo-Gonzalez E; Urriolagoitia-Calderon G; Urriolagoitia-Sosa G; Hernandez-Gomez L H; Romero-Angeles B; Torres-San Miguel Ch, E-mail: rrodriguezm@ipn.mx, E-mail: urrio332@hotmail.com, E-mail: guiurri@hotmail.com, E-mail: luishector56@hotmail.com, E-mail: romerobeatriz98@hotmail.com, E-mail: napor@hotmail.com [INSTITUTO POLITECNICO NACIONAL Seccion de Estudios de Posgrado e Investigacion (SEPI), Escuela Superior de Ingenieria Mecanica y Electrica (ESIME), Edificio 5. 2do Piso, Unidad Profesional Adolfo Lopez Mateos ' Zacatenco' Col. Lindavista, C.P. 07738, Mexico, D.F. (Mexico)
2011-07-19
Crack growth direction has been studied in many ways. Particularly Sih's strain energy theory predicts that a fracture under a three-dimensional state of stress spreads in direction of the minimum strain energy density. In this work a study for angle of fracture growth was made, considering a biaxial stress state at the crack tip on SEN specimens. The stress state applied on a tension-compression SEN specimen is biaxial one on crack tip, as it can observed in figure 1. A solution method proposed to obtain a mathematical model considering genetic algorithms, which have demonstrated great capacity for the solution of many engineering problems. From the model given by Sih one can deduce the density of strain energy stored for unit of volume at the crack tip as dW = [1/2E({sigma}{sup 2}{sub x} + {sigma}{sup 2}{sub y}) - {nu}/E({sigma}{sub x}{sigma}{sub y})]dV (1). From equation (1) a mathematical deduction to solve in terms of {theta} of this case was developed employing Genetic Algorithms, where {theta} is a crack propagation direction in plane x-y. Steel and aluminium mechanical properties to modelled specimens were employed, because they are two of materials but used in engineering design. Obtained results show stable zones of fracture propagation but only in a range of applied loading.
International Nuclear Information System (INIS)
Rodriguez-MartInez R; Lugo-Gonzalez E; Urriolagoitia-Calderon G; Urriolagoitia-Sosa G; Hernandez-Gomez L H; Romero-Angeles B; Torres-San Miguel Ch
2011-01-01
Crack growth direction has been studied in many ways. Particularly Sih's strain energy theory predicts that a fracture under a three-dimensional state of stress spreads in direction of the minimum strain energy density. In this work a study for angle of fracture growth was made, considering a biaxial stress state at the crack tip on SEN specimens. The stress state applied on a tension-compression SEN specimen is biaxial one on crack tip, as it can observed in figure 1. A solution method proposed to obtain a mathematical model considering genetic algorithms, which have demonstrated great capacity for the solution of many engineering problems. From the model given by Sih one can deduce the density of strain energy stored for unit of volume at the crack tip as dW = [1/2E(σ 2 x + σ 2 y ) - ν/E(σ x σy)]dV (1). From equation (1) a mathematical deduction to solve in terms of θ of this case was developed employing Genetic Algorithms, where θ is a crack propagation direction in plane x-y. Steel and aluminium mechanical properties to modelled specimens were employed, because they are two of materials but used in engineering design. Obtained results show stable zones of fracture propagation but only in a range of applied loading.
Directory of Open Access Journals (Sweden)
Aidin Delgoshaei
2016-06-01
Full Text Available In this paper, a new method is proposed for scheduling dynamic cellular manufacturing systems (D-CMS in the presence of uncertain product demands. The aim of this method is to control the process of trading off between in-house manufacturing and outsourcing while product demands are uncertain and can be varied from period to period. To solve the proposed problem, a hybrid Tabu Search and Simulated Annealing are developed to overcome hardness of the proposed model and then results are compared with a Branch and Bound and Simulated Annealing algorithms. A Taguchi method (L_27 orthogonal optimization is used to estimate parameters of the proposed method in order to solve experiments derived from literature. An in-depth analysis is conducted on the results in consideration of various factors. For evaluating the system imbalance in dynamic market demands, a new measuring index is developed. Our findings indicate that the uncertain condition of market demands affects the routing of product parts and may induce machine-load variations that yield to cell-load diversity. The results showed that the proposed hybrid method can provide solutions with better quality.
Directory of Open Access Journals (Sweden)
Wendong Yang
2017-01-01
Full Text Available Machine learning plays a vital role in several modern economic and industrial fields, and selecting an optimized machine learning method to improve time series’ forecasting accuracy is challenging. Advanced machine learning methods, e.g., the support vector regression (SVR model, are widely employed in forecasting fields, but the individual SVR pays no attention to the significance of data selection, signal processing and optimization, which cannot always satisfy the requirements of time series forecasting. By preprocessing and analyzing the original time series, in this paper, a hybrid SVR model is developed, considering periodicity, trend and randomness, and combined with data selection, signal processing and an optimization algorithm for short-term load forecasting. Case studies of electricity power data from New South Wales and Singapore are regarded as exemplifications to estimate the performance of the developed novel model. The experimental results demonstrate that the proposed hybrid method is not only robust but also capable of achieving significant improvement compared with the traditional single models and can be an effective and efficient tool for power load forecasting.
A hybrid DE–PS algorithm for load frequency control under deregulated power system with UPFC and RFB
Directory of Open Access Journals (Sweden)
Rabindra Kumar Sahu
2015-09-01
Full Text Available In this paper, a Modified Integral Derivative (MID controller is proposed for Load Frequency Control (LFC of multi-area multi-source power system in deregulated environment. The multi-source power system is having different sources of power generation such as thermal, hydro, wind and diesel generating units considering boiler dynamics for thermal plants, Generation Rate Constraint (GRC and Governor Dead Band (GDB non-linearity. The superiority of proposed hybrid Differential Evolution and Pattern Search (hDE-PS optimized MID controller over GA and DE techniques is demonstrated. Further, the effectiveness of proposed hDE-PS optimized MID controller over Integral (I and Integral Derivative (ID controller is verified. Then, to further improve the system performance, Unified Power Flow Controller (UPFC is placed in the tie-line and Redox Flow Batteries (RFBs are considered in the first area. The performance of proposed approach is evaluated at all possible power transactions that take place in a deregulated power market.
Directory of Open Access Journals (Sweden)
Z. C. Gao
2017-01-01
Full Text Available This paper presents an integrated state-of-charge (SOC estimation model and active cell balancing of a 12-cell lithium iron phosphate (LiFePO4 battery power system. The strong tracking cubature extended Kalman filter (STCEKF gave an accurate SOC prediction compared to other Kalman-based filter algorithms. The proposed groupwise balancing of the multiple SOC exhibited a higher balancing speed and lower balancing loss than other cell balancing designs. The experimental results demonstrated the robustness and performance of the battery when subjected to current load profile of an electric vehicle under varying ambient temperature.
Walve, Jakob; Sandberg, Maria; Larsson, Ulf; Lännergren, Christer
2018-05-01
Internal phosphorus (P) loading from sediments, controlled by hypoxia, is often assumed to hamper the recovery of lakes and coastal areas from eutrophication. In the early 1970s, the external P load to the inner archipelago of Stockholm, Sweden (Baltic Sea), was drastically reduced by improved sewage treatment, but the internal P loading and its controlling factors have been poorly quantified. We use two slightly different four-layer box models to calculate the area's seasonal and annual P balance (input-export) and the internal P exchange with sediments in 1968-2015. For 10-20 years after the main P load reduction, there was a negative P balance, small in comparison to the external load, and probably due to release from legacy sediment P storage. Later, the stabilized, near-neutral P balance indicates no remaining internal loading from legacy P, but P retention is low, despite improved oxygen conditions. Seasonally, sediments are a P sink in spring and a P source in summer and autumn. Most of the deep-water P release from sediments in summer-autumn appears to be derived from the settled spring bloom and is exported to outer areas during winter. Oxygen consumption and P release in the deep water are generally tightly coupled, indicating limited iron control of P release. However, enhanced P release in years of deep-water hypoxia suggests some contribution from redox-sensitive P pools. Increasing deep-water temperatures that stimulate oxygen consumption rates in early summer have counteracted the effect of lowered organic matter sedimentation on oxygen concentrations. Since the P turnover time is short and legacy P small, measures to bind P in Stockholm inner archipelago sediments would primarily accumulate recent P inputs, imported from the Baltic Sea and from Lake Mälaren.
International Nuclear Information System (INIS)
Xu, Zuwei; Zhao, Haibo; Zheng, Chuguang
2015-01-01
This paper proposes a comprehensive framework for accelerating population balance-Monte Carlo (PBMC) simulation of particle coagulation dynamics. By combining Markov jump model, weighted majorant kernel and GPU (graphics processing unit) parallel computing, a significant gain in computational efficiency is achieved. The Markov jump model constructs a coagulation-rule matrix of differentially-weighted simulation particles, so as to capture the time evolution of particle size distribution with low statistical noise over the full size range and as far as possible to reduce the number of time loopings. Here three coagulation rules are highlighted and it is found that constructing appropriate coagulation rule provides a route to attain the compromise between accuracy and cost of PBMC methods. Further, in order to avoid double looping over all simulation particles when considering the two-particle events (typically, particle coagulation), the weighted majorant kernel is introduced to estimate the maximum coagulation rates being used for acceptance–rejection processes by single-looping over all particles, and meanwhile the mean time-step of coagulation event is estimated by summing the coagulation kernels of rejected and accepted particle pairs. The computational load of these fast differentially-weighted PBMC simulations (based on the Markov jump model) is reduced greatly to be proportional to the number of simulation particles in a zero-dimensional system (single cell). Finally, for a spatially inhomogeneous multi-dimensional (multi-cell) simulation, the proposed fast PBMC is performed in each cell, and multiple cells are parallel processed by multi-cores on a GPU that can implement the massively threaded data-parallel tasks to obtain remarkable speedup ratio (comparing with CPU computation, the speedup ratio of GPU parallel computing is as high as 200 in a case of 100 cells with 10 000 simulation particles per cell). These accelerating approaches of PBMC are
Energy Technology Data Exchange (ETDEWEB)
Klages, Marc
2011-08-19
Subject of the interdisciplinary work are the following priorities: Discussion and results of the economic opportunities and risks as well as sociotechnological relationships in the use of a campus management system (CMS) under strong college complex organizational structures. Various stages in the life cycle of a software solution are affected. The main focus lies in the context of the underlying themes on the selection, integration and migration of CMS. In particular, the research results of a complex process model for the creation of an economic analysis to integrate CMS solutions form the major focus. Investigation of the status quo of external funding and its IT-based management at German universities. Characterization of the actual situation, development of science-based target concepts and derivation of possible implications and relevant recommendations for action for the organizational and process-oriented (re)design of IT support. Green Business (GB) as a global enterprise framework to increase sustainability in supply chains for the purposes of corporate governance. IT serves as an operative trigger to the strategic sustainability goals of companies. Fluctuations caused by renewable energy (RE), endanger the stability in the European energy network and lead to inefficient compensation and balancing power. In-depth investigations show two main approaches to increase network stability: producer-sided load management through active management of virtual power plants (VPP) based on neuro simulated forecasting methods under various use of real-time information (such as weather data) and prize-controlled, semiautomated use of energy on the demand-side. All these research activities have this in common: they underscore the relevance of information systems for effective organization- and workflow-design and the development of potentials as well as fundamental benefit effects. For the organizational- and project-success, however, the choice of investment volume
Fatigue Load Sensitivity Based Optimal Active Power Dispatch For Wind Farms
DEFF Research Database (Denmark)
Zhao, Haoran; Wu, Qiuwei; Huang, Shaojun
2017-01-01
This paper proposes an optimal active power dispatch algorithm for wind farms based on Wind Turbine (WT) load sensitivity. The control objectives include tracking power references from the system operator and minimizing fatigue loads experienced by WTs. The sensitivity of WT fatigue loads to power...... sensitivity are derived, which significantly improves the computation efficiency of the local WT controller. The proposed algorithm can be implemented in different active power control schemes. Case studies were conducted with a wind farm under balance control for both low and high wind conditions...
Tarroja, Brian; Eichman, Joshua D.; Zhang, Li; Brown, Tim M.; Samuelsen, Scott
2015-03-01
A study has been performed that analyzes the effectiveness of utilizing plug-in vehicles to meet holistic environmental goals across the combined electricity and transportation sectors. In this study, plug-in hybrid electric vehicle (PHEV) penetration levels are varied from 0 to 60% and base renewable penetration levels are varied from 10 to 63%. The first part focused on the effect of installing plug-in hybrid electric vehicles on the environmental performance of the combined electricity and transportation sectors. The second part addresses impacts on the design and operation of load-balancing resources on the electric grid associated with fleet capacity factor, peaking and load-following generator capacity, efficiency, ramp rates, start-up events and the levelized cost of electricity. PHEVs using smart charging are found to counteract many of the disruptive impacts of intermittent renewable power on balancing generators for a wide range of renewable penetration levels, only becoming limited at high renewable penetration levels due to lack of flexibility and finite load size. This study highlights synergy between sustainability measures in the electric and transportation sectors and the importance of communicative dispatch of these vehicles.
ComprehensiveBench: a Benchmark for the Extensive Evaluation of Global Scheduling Algorithms
Pilla, Laércio L.; Bozzetti, Tiago C.; Castro, Márcio; Navaux, Philippe O. A.; Méhaut, Jean-François
2015-10-01
Parallel applications that present tasks with imbalanced loads or complex communication behavior usually do not exploit the underlying resources of parallel platforms to their full potential. In order to mitigate this issue, global scheduling algorithms are employed. As finding the optimal task distribution is an NP-Hard problem, identifying the most suitable algorithm for a specific scenario and comparing algorithms are not trivial tasks. In this context, this paper presents ComprehensiveBench, a benchmark for global scheduling algorithms that enables the variation of a vast range of parameters that affect performance. ComprehensiveBench can be used to assist in the development and evaluation of new scheduling algorithms, to help choose a specific algorithm for an arbitrary application, to emulate other applications, and to enable statistical tests. We illustrate its use in this paper with an evaluation of Charm++ periodic load balancers that stresses their characteristics.
Dynamic workload balancing of parallel applications with user-level scheduling on the Grid
Korkhov, Vladimir V; Krzhizhanovskaya, Valeria V
2009-01-01
This paper suggests a hybrid resource management approach for efficient parallel distributed computing on the Grid. It operates on both application and system levels, combining user-level job scheduling with dynamic workload balancing algorithm that automatically adapts a parallel application to the heterogeneous resources, based on the actual resource parameters and estimated requirements of the application. The hybrid environment and the algorithm for automated load balancing are described, the influence of resource heterogeneity level is measured, and the speedup achieved with this technique is demonstrated for different types of applications and resources.
Ghaedi, M; Shojaeipour, E; Ghaedi, A M; Sahraei, Reza
2015-05-05
In this study, copper nanowires loaded on activated carbon (Cu-NWs-AC) was used as novel efficient adsorbent for the removal of malachite green (MG) from aqueous solution. This new material was synthesized through simple protocol and its surface properties such as surface area, pore volume and functional groups were characterized with different techniques such XRD, BET and FESEM analysis. The relation between removal percentages with variables such as solution pH, adsorbent dosage (0.005, 0.01, 0.015, 0.02 and 0.1g), contact time (1-40min) and initial MG concentration (5, 10, 20, 70 and 100mg/L) was investigated and optimized. A three-layer artificial neural network (ANN) model was utilized to predict the malachite green dye removal (%) by Cu-NWs-AC following conduction of 248 experiments. When the training of the ANN was performed, the parameters of ANN model were as follows: linear transfer function (purelin) at output layer, Levenberg-Marquardt algorithm (LMA), and a tangent sigmoid transfer function (tansig) at the hidden layer with 11 neurons. The minimum mean squared error (MSE) of 0.0017 and coefficient of determination (R(2)) of 0.9658 were found for prediction and modeling of dye removal using testing data set. A good agreement between experimental data and predicted data using the ANN model was obtained. Fitting the experimental data on previously optimized condition confirm the suitability of Langmuir isotherm models for their explanation with maximum adsorption capacity of 434.8mg/g at 25°C. Kinetic studies at various adsorbent mass and initial MG concentration show that the MG maximum removal percentage was achieved within 20min. The adsorption of MG follows the pseudo-second-order with a combination of intraparticle diffusion model. Copyright © 2015 Elsevier B.V. All rights reserved.
Zafar, Mohd; Van Vinh, N; Behera, Shishir Kumar; Park, Hung-Suck
2017-04-01
Organic matters (OMs) and their oxidization products often influence the fate and transport of heavy metals in the subsurface aqueous systems through interaction with the mineral surfaces. This study investigates the ethanol (EtOH)-mediated As(III) adsorption onto Zn-loaded pinecone (PC) biochar through batch experiments conducted under Box-Behnken design. The effect of EtOH on As(III) adsorption mechanism was quantitatively elucidated by fitting the experimental data using artificial neural network and quadratic modeling approaches. The quadratic model could describe the limiting nature of EtOH and pH on As(III) adsorption, whereas neural network revealed the stronger influence of EtOH (64.5%) followed by pH (20.75%) and As(III) concentration (14.75%) on the adsorption phenomena. Besides, the interaction among process variables indicated that EtOH enhances As(III) adsorption over a pH range of 2 to 7, possibly due to facilitation of ligand-metal(Zn) binding complexation mechanism. Eventually, hybrid response surface model-genetic algorithm (RSM-GA) approach predicted a better optimal solution than RSM, i.e., the adsorptive removal of As(III) (10.47μg/g) is facilitated at 30.22mg C/L of EtOH with initial As(III) concentration of 196.77μg/L at pH5.8. The implication of this investigation might help in understanding the application of biochar for removal of various As(III) species in the presence of OM. Copyright © 2016. Published by Elsevier B.V.
Production Balance of Ship Erection
Institute of Scientific and Technical Information of China (English)
JIANG Ru-hong; TAN Jia-hua; LIU Cun-gen
2008-01-01
A network plan model of ship erection was established based on the network planning technologyand the work-package breakdown system. The load-oriented production control method was introduced to buildup a throughput diagram model thus it is possible to describe the ship erection process numerically. Based onthe digitaiized models some cases of production balance of ship erection were studied and three balance indexeswere put forward, they are the load balance rate, the input manpower balance rate and the maximum gantrycrane operating times. Such an analytic method based on the balance evaluation is the important foundationfor digitization and intelligentization of shipyard production management.
Directory of Open Access Journals (Sweden)
Ailian Jiang
2018-03-01
Full Text Available Low cost, high reliability and easy maintenance are key criteria in the design of routing protocols for wireless sensor networks (WSNs. This paper investigates the existing ant colony optimization (ACO-based WSN routing algorithms and the minimum hop count WSN routing algorithms by reviewing their strengths and weaknesses. We also consider the critical factors of WSNs, such as energy constraint of sensor nodes, network load balancing and dynamic network topology. Then we propose a hybrid routing algorithm that integrates ACO and a minimum hop count scheme. The proposed algorithm is able to find the optimal routing path with minimal total energy consumption and balanced energy consumption on each node. The algorithm has unique superiority in terms of searching for the optimal path, balancing the network load and the network topology maintenance. The WSN model and the proposed algorithm have been implemented using C++. Extensive simulation experimental results have shown that our algorithm outperforms several other WSN routing algorithms on such aspects that include the rate of convergence, the success rate in searching for global optimal solution, and the network lifetime.
González-Castro, A; Ortiz-Lasa, M; Leizaola, O; Salgado, E; Irriguible, T; Sánchez-Satorra, M; Lomas-Fernández, C; Barral-Segade, P; Cordero-Vallejo, M; Rodrigo-Calabia, E; Dierssen-Sotos, T
2017-05-01
To analyse the association between water balance during the first 24h of admission to ICU and the variables related to chloride levels (chloride loading, type of fluid administered, hyperchloraemia), with the development of acute kidney injury renal replacement therapy (AKI-RRT) during patients' admission to ICU. Multicentre case-control study. Hospital-based, national, carried out in 6 ICUs. Cases were patients older than 18 years who developed an AKI-RRT. Controls were patients older than 18 years admitted to the same institutions during the study period, who did not develop AKI-RRT during ICU admission. Pairing was done by APACHE-II. An analysis of unconditional logistic regression adjusted for age, sex, APACHE-II and water balance (in evaluating the type of fluid). We analysed the variables of 430 patients: 215 cases and 215 controls. An increase of 10% of the possibility of developing AKI-RRT per 500ml of positive water balance was evident (OR: 1.09 [95% CI: 1.05 to 1.14]; P<.001). The study of mean values of chloride load administered did not show differences between the group of cases and controls (299.35±254.91 vs. 301.67±234.63; P=.92). The water balance in the first 24h of ICU admission relates to the development of IRA-TRR, regardless of chloraemia. Copyright © 2017 Sociedad Española de Anestesiología, Reanimación y Terapéutica del Dolor. Publicado por Elsevier España, S.L.U. All rights reserved.
Improved Regression Analysis of Temperature-Dependent Strain-Gage Balance Calibration Data
Ulbrich, N.
2015-01-01
An improved approach is discussed that may be used to directly include first and second order temperature effects in the load prediction algorithm of a wind tunnel strain-gage balance. The improved approach was designed for the Iterative Method that fits strain-gage outputs as a function of calibration loads and uses a load iteration scheme during the wind tunnel test to predict loads from measured gage outputs. The improved approach assumes that the strain-gage balance is at a constant uniform temperature when it is calibrated and used. First, the method introduces a new independent variable for the regression analysis of the balance calibration data. The new variable is designed as the difference between the uniform temperature of the balance and a global reference temperature. This reference temperature should be the primary calibration temperature of the balance so that, if needed, a tare load iteration can be performed. Then, two temperature{dependent terms are included in the regression models of the gage outputs. They are the temperature difference itself and the square of the temperature difference. Simulated temperature{dependent data obtained from Triumph Aerospace's 2013 calibration of NASA's ARC-30K five component semi{span balance is used to illustrate the application of the improved approach.
Energy management based on AM/FM/GIS for phase balancing application on distribution systems
International Nuclear Information System (INIS)
Kuo, C.-C.; Chao, Y.-T.
2010-01-01
Unbalanced feeder systems may deteriorate of power quality, and increase investment and operating costs for distribution systems. The phase swapping method recommends re-phasing circuits of laterals and transformers for making the current and voltage balanced and also reducing feeder loss and voltage drop. In this paper, an application program, based on the automated mapping/facilities management/ geographic information system (AM/FM/GIS) is developed which contains a function of automatically computing Z-bus, load flow and phase balancing of feeders with phase swapping by using easily selecting of feeder on a graphic user interface application. Therefore, the relative data need not be keyed in manually. The presented phase balancing algorithm are based on database and related data structures developed on the AM/FM/GIS and Visual Basic software, which can be integrated into the Tai-Power distribution automation system. Then, the phase balancing algorithm is designed to handle the load patterns and the load of transformers that connect specific feeders when evaluating phase swaps that will result in reduced daily circuit losses over all load points. The proposed application not only can effectively reduce the circuit loss and improves phase balancing, but also enhances power quality efficiently under easily using environment.
Energy Technology Data Exchange (ETDEWEB)
Tom, Nathan M [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Yu, Yi-Hsiang [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Wright, Alan D [National Renewable Energy Laboratory (NREL), Golden, CO (United States)
2017-06-08
In this work, the net power delivered to the grid from a nonideal power take-off (PTO) is introduced followed by a review of the pseudo-spectral control theory. A power-to-load ratio, used to evaluate the pseudo-spectral controller performance, is discussed, and the results obtained from optimizing a multiterm objective function are compared against results obtained from maximizing the net output power to the grid. Simulation results are then presented for four different oscillating wave energy converter geometries to highlight the potential of combing both geometry and PTO control to maximize power while minimizing loads.
Geometric Algorithms for Private-Cache Chip Multiprocessors
DEFF Research Database (Denmark)
Ajwani, Deepak; Sitchinava, Nodari; Zeh, Norbert
2010-01-01
-D convex hulls. These results are obtained by analyzing adaptations of either the PEM merge sort algorithm or PRAM algorithms. For the second group of problems—orthogonal line segment intersection reporting, batched range reporting, and related problems—more effort is required. What distinguishes......We study techniques for obtaining efficient algorithms for geometric problems on private-cache chip multiprocessors. We show how to obtain optimal algorithms for interval stabbing counting, 1-D range counting, weighted 2-D dominance counting, and for computing 3-D maxima, 2-D lower envelopes, and 2...... these problems from the ones in the previous group is the variable output size, which requires I/O-efficient load balancing strategies based on the contribution of the individual input elements to the output size. To obtain nearly optimal algorithms for these problems, we introduce a parallel distribution...
Scalable Atomistic Simulation Algorithms for Materials Research
Directory of Open Access Journals (Sweden)
Aiichiro Nakano
2002-01-01
Full Text Available A suite of scalable atomistic simulation programs has been developed for materials research based on space-time multiresolution algorithms. Design and analysis of parallel algorithms are presented for molecular dynamics (MD simulations and quantum-mechanical (QM calculations based on the density functional theory. Performance tests have been carried out on 1,088-processor Cray T3E and 1,280-processor IBM SP3 computers. The linear-scaling algorithms have enabled 6.44-billion-atom MD and 111,000-atom QM calculations on 1,024 SP3 processors with parallel efficiency well over 90%. production-quality programs also feature wavelet-based computational-space decomposition for adaptive load balancing, spacefilling-curve-based adaptive data compression with user-defined error bound for scalable I/O, and octree-based fast visibility culling for immersive and interactive visualization of massive simulation data.
Energy Technology Data Exchange (ETDEWEB)
2008-06-15
Wind power is expected to growth rapidly in Sweden. The existing certificate system gives economic incentives for development of 17 TWh from renewable energy sources until 2016, compared to the 2002 level. The Swedish Energy Agency estimates that 9 TWh wind power will be built by 2020, given the present certificate system. However, a new planning goal of 30 TWh wind energy by 2020 has been proposed by the Agency. It is very important for Svenska Kraftnaet to follow the development in order to take the right actions to adapt the national grid to the increased share of wind power. The total increased need for balancing power is estimated to be: 1 400-1 800 MW for 10 TWh added wind power, and 4 300-5 300 MW for 30 TWh. About 15% of the increased balancing need must be assigned to automatically frequency regulating generation. The rest can be made up of sources that can be regulated on a minute- or hour-scale. The planned wind power risks to replace generation with regulating capacity, and it is important to continuously analyze if and how this happens, and which the consequences will be for the balancing capacity. The socio-economic effects for the national grid include increased investment cost and increased costs foe balancing and regulating. Massive expansion in North Sweden is the most costly alternative, with a capitalized cost estimated to 25 000 MSEK (about 4 000 MUSD) at an expansion of 30 TWh wind power. This can be compared to the estimated investment cost for the wind power expansion of 150 000 MSEK
... often, it could be a sign of a balance problem. Balance problems can make you feel unsteady. You may ... related injuries, such as a hip fracture. Some balance problems are due to problems in the inner ...
Optimal Residential Load Scheduling Under Utility and Rooftop Photovoltaic Units
Directory of Open Access Journals (Sweden)
Ghulam Hafeez
2018-03-01
Full Text Available With the rapid advancement in technology, electrical energy consumption is increasing rapidly. Especially, in the residential sector, more than 80% of electrical energy is being consumed because of consumer negligence. This brings the challenging task of maintaining the balance between the demand and supply of electric power. In this paper, we focus on the problem of load balancing via load scheduling under utility and rooftop photovoltaic (PV units to reduce electricity cost and peak to average ratio (PAR in demand-side management. For this purpose, we adopted genetic algorithm (GA, binary particle swarm optimization (BPSO, wind-driven optimization (WDO, and our proposed genetic WDO (GWDO algorithm, which is a hybrid of GA and WDO, to schedule the household load. For energy cost estimation, combined real-time pricing (RTP and inclined block rate (IBR were used. The proposed algorithm shifts load from peak consumption hours to off-peak hours based on combined pricing scheme and generation from rooftop PV units. Simulation results validate our proposed GWDO algorithm in terms of electricity cost and PAR reduction while considering all three scenarios which we have considered in this work: (1 load scheduling without renewable energy sources (RESs and energy storage system (ESS, (2 load scheduling with RESs, and (3 load scheduling with RESs and ESS. Furthermore, our proposed scheme reduced electricity cost and PAR by 22.5% and 29.1% in scenario 1, 47.7% and 30% in scenario 2, and 49.2% and 35.4% in scenario 3, respectively, as compared to unscheduled electricity consumption.
International Nuclear Information System (INIS)
Woodruff, S.B.
1992-01-01
The Transient Reactor Analysis Code (TRAC), which features a two- fluid treatment of thermal-hydraulics, is designed to model transients in water reactors and related facilities. One of the major computational costs associated with TRAC and similar codes is calculating constitutive coefficients. Although the formulations for these coefficients are local the costs are flow-regime- or data-dependent; i.e., the computations needed for a given spatial node often vary widely as a function of time. Consequently, poor load balancing will degrade efficiency on either vector or data parallel architectures when the data are organized according to spatial location. Unfortunately, a general automatic solution to the load-balancing problem associated with data-dependent computations is not yet available for massively parallel architectures. This document discusses why developers algorithms, such as a neural net representation, that do not exhibit algorithms, such as a neural net representation, that do not exhibit load-balancing problems
Optimized Virtual Machine Placement with Traffic-Aware Balancing in Data Center Networks
Directory of Open Access Journals (Sweden)
Tao Chen
2016-01-01
Full Text Available Virtualization has been an efficient method to fully utilize computing resources such as servers. The way of placing virtual machines (VMs among a large pool of servers greatly affects the performance of data center networks (DCNs. As network resources have become a main bottleneck of the performance of DCNs, we concentrate on VM placement with Traffic-Aware Balancing to evenly utilize the links in DCNs. In this paper, we first proposed a Virtual Machine Placement Problem with Traffic-Aware Balancing (VMPPTB and then proved it to be NP-hard and designed a Longest Processing Time Based Placement algorithm (LPTBP algorithm to solve it. To take advantage of the communication locality, we proposed Locality-Aware Virtual Machine Placement Problem with Traffic-Aware Balancing (LVMPPTB, which is a multiobjective optimization problem of simultaneously minimizing the maximum number of VM partitions of requests and minimizing the maximum bandwidth occupancy on uplinks of Top of Rack (ToR switches. We also proved it to be NP-hard and designed a heuristic algorithm (Least-Load First Based Placement algorithm, LLBP algorithm to solve it. Through extensive simulations, the proposed heuristic algorithm is proven to significantly balance the bandwidth occupancy on uplinks of ToR switches, while keeping the number of VM partitions of each request small enough.
Energy Aware Clustering Algorithms for Wireless Sensor Networks
Rakhshan, Noushin; Rafsanjani, Marjan Kuchaki; Liu, Chenglian
2011-09-01
The sensor nodes deployed in wireless sensor networks (WSNs) are extremely power constrained, so maximizing the lifetime of the entire networks is mainly considered in the design. In wireless sensor networks, hierarchical network structures have the advantage of providing scalable and energy efficient solutions. In this paper, we investigate different clustering algorithms for WSNs and also compare these clustering algorithms based on metrics such as clustering distribution, cluster's load balancing, Cluster Head's (CH) selection strategy, CH's role rotation, node mobility, clusters overlapping, intra-cluster communications, reliability, security and location awareness.
... fully trust your sense of balance. Loss of balance also raises the risk of falls. This is a serious and even life-threatening ... 65. Balance disorders are serious because of the risk of falls. But occasionally balance problems may warn of another health condition, such ...
Srinivasan, R. S.; Simanonok, K. E.; Charles, J. B.
1994-01-01
Fluid loading (FL) before Shuttle reentry is a countermeasure currently in use by NASA to improve the orthostatic tolerance of astronauts during reentry and postflight. The fluid load consists of water and salt tablets equivalent to 32 oz (946 ml) of isotonic saline. However, the effectiveness of this countermeasure has been observed to decrease with the duration of spaceflight. The countermeasure's effectiveness may be improved by enhancing fluid retention using analogs of vasopressin such as lypressin (LVP) and desmopressin (dDAVP). In a computer simulation study reported previously, we attempted to assess the improvement in fluid retention obtained by the use of LVP administered before FL. The present study is concerned with the use of dDAVP. In a recent 24-hour, 6 degree head-down tilt (HDT) study involving seven men, dDAVP was found to improve orthostatic tolerance as assessed by both lower body negative pressure (LBNP) and stand tests. The treatment restored Luft's cumulative stress index (cumulative product of magnitude and duration of LBNP) to nearly pre-bedrest level. The heart rate was lower and stroke volume was marginally higher at the same LBNP levels with administration of dDAVP compared to placebo. Lower heart rates were also observed with dDAVP during stand test, despite the lower level of cardiovascular stress. These improvements were seen with only a small but significant increase in plasma volume of approximately 3 percent. This paper presents a computer simulation analysis of some of the results of this HDT study.
LSPC is the Loading Simulation Program in C++, a watershed modeling system that includes streamlined Hydrologic Simulation Program Fortran (HSPF) algorithms for simulating hydrology, sediment, and general water quality
U.S. Environmental Protection Agency — LSPC is the Loading Simulation Program in C++, a watershed modeling system that includes streamlined Hydrologic Simulation Program Fortran (HSPF) algorithms for...
Artificial Immune Algorithm for Subtask Industrial Robot Scheduling in Cloud Manufacturing
Suma, T.; Murugesan, R.
2018-04-01
The current generation of manufacturing industry requires an intelligent scheduling model to achieve an effective utilization of distributed manufacturing resources, which motivated us to work on an Artificial Immune Algorithm for subtask robot scheduling in cloud manufacturing. This scheduling model enables a collaborative work between the industrial robots in different manufacturing centers. This paper discussed two optimizing objectives which includes minimizing the cost and load balance of industrial robots through scheduling. To solve these scheduling problems, we used the algorithm based on Artificial Immune system. The parameters are simulated with MATLAB and the results compared with the existing algorithms. The result shows better performance than existing.
A Novel Parallel Algorithm for Edit Distance Computation
Directory of Open Access Journals (Sweden)
Muhammad Murtaza Yousaf
2018-01-01
Full Text Available The edit distance between two sequences is the minimum number of weighted transformation-operations that are required to transform one string into the other. The weighted transformation-operations are insert, remove, and substitute. Dynamic programming solution to find edit distance exists but it becomes computationally intensive when the lengths of strings become very large. This work presents a novel parallel algorithm to solve edit distance problem of string matching. The algorithm is based on resolving dependencies in the dynamic programming solution of the problem and it is able to compute each row of edit distance table in parallel. In this way, it becomes possible to compute the complete table in min(m,n iterations for strings of size m and n whereas state-of-the-art parallel algorithm solves the problem in max(m,n iterations. The proposed algorithm also increases the amount of parallelism in each of its iteration. The algorithm is also capable of exploiting spatial locality while its implementation. Additionally, the algorithm works in a load balanced way that further improves its performance. The algorithm is implemented for multicore systems having shared memory. Implementation of the algorithm in OpenMP shows linear speedup and better execution time as compared to state-of-the-art parallel approach. Efficiency of the algorithm is also proven better in comparison to its competitor.
Liu, Jinxing
2011-11-11
General summaries on the load-unload and force-release methods indicate that the two methods are efficient for different-charactered quasi-static failures; therefore, it is important to choose the right one for different applications. Then we take, as an example, the case where the release of the ruptured element\\'s internal force is infinitely slower than the relaxation of the lattice system and analyze why the force-release method works better than the load-unload method in this particular case. Different trial deformation fields are used by them to track the next equilibrium state. Force-release method ensures that the deformation throughout the whole failure process coincides exactly with the controlled-displacement boundary conditions and we utilize the \\'left modulus\\' concept to prove that this method satisfies the energetic evolution in the force-displacement diagram; both of which are not satisfied by the load-unload method. To illustrate that the force-release method is not just another form of the load-unload method, a tensile test on a specifically designed system is analyzed to further compare the above two methods, showing that their predicted sequences of elemental failures can be different. In closing, we simulate the uniaxial tensile test on a beam lattice system by the load-unload and force-release methods and exploit the details of the resulting fracture processes. © The Author(s), 2011.
Directory of Open Access Journals (Sweden)
Y.N. Vijay Kumar
2016-05-01
Full Text Available Now a day, non-uniform increase of demand on a power system turns the research toward the dynamic analysis. In this paper, to perform dynamic analysis and to solve economic load dispatch problem using optimal power flow (OPF, four realistic load levels are considered. Further, the effectiveness of the objective has been enhanced in the presence of interline power flow controller (IPFC. An optimal location identification methodology for IPFC based on line stability index (LSI is also presented. The effect of ramp-rate limits on generations and the effect of dynamic loads on generation fuel cost and transmission losses are also analyzed on standard IEEE-30 bus and real time 23 bus test systems with supporting validations, numerical and graphical results.
Power Load Prediction Based on Fractal Theory
Jian-Kai, Liang; Cattani, Carlo; Wan-Qing, Song
2015-01-01
The basic theories of load forecasting on the power system are summarized. Fractal theory, which is a new algorithm applied to load forecasting, is introduced. Based on the fractal dimension and fractal interpolation function theories, the correlation algorithms are applied to the model of short-term load forecasting. According to the process of load forecasting, the steps of every process are designed, including load data preprocessing, similar day selecting, short-term load forecasting, and...
Liu, Jinxing; El Sayed, Tamer S.
2011-01-01
General summaries on the load-unload and force-release methods indicate that the two methods are efficient for different-charactered quasi-static failures; therefore, it is important to choose the right one for different applications. Then we take
Application of epidemic algorithms for smart grids control
International Nuclear Information System (INIS)
Krkoleva, Aleksandra
2012-01-01
Smart Grids are a new concept for electricity networks development, aiming to provide economically efficient and sustainable power system by integrating effectively the actions and needs of the network users. The thesis addresses the Smart Grids concept, with emphasis on the control strategies developed on the basis of epidemic algorithms, more specifically, gossip algorithms. The thesis is developed around three Smart grid aspects: the changed role of consumers in terms of taking part in providing services within Smart Grids; the possibilities to implement decentralized control strategies based on distributed algorithms; and information exchange and benefits emerging from implementation of information and communication technologies. More specifically, the thesis presents a novel approach for providing ancillary services by implementing gossip algorithms. In a decentralized manner, by exchange of information between the consumers and by making decisions on local level, based on the received information and local parameters, the group achieves its global objective, i. e. providing ancillary services. The thesis presents an overview of the Smart Grids control strategies with emphasises on new strategies developed for the most promising Smart Grids concepts, as Micro grids and Virtual power plants. The thesis also presents the characteristics of epidemic algorithms and possibilities for their implementation in Smart Grids. Based on the research on epidemic algorithms, two applications have been developed. These applications are the main outcome of the research. The first application enables consumers, represented by their commercial aggregators, to participate in load reduction and consequently, to participate in balancing market or reduce the balancing costs of the group. In this context, the gossip algorithms are used for aggregator's message dissemination for load reduction and households and small commercial and industrial consumers to participate in maintaining
A versatile computer package for mechanism analysis, part 2: Dynamics and balance
Davies, T.
The algorithms required for the shaking force components, the shaking moment about the crankshaft axis, and the input torque and bearing load components are discussed using the textile machine as a focus for the discussion. The example is also used to provide illustrations of the output for options on the hodograph of the shaking force vector. This provides estimates of the optimum contrarotating masses and their locations for a generalized primary Lanchester balancer. The suitability of generalized Lanchester balancers particularly for textile machinery, and the overall strategy used during the development of the package are outlined.
Directory of Open Access Journals (Sweden)
Marcelo Seido Nagano
2012-10-01
Full Text Available This work aimed to apply genetic algorithms (GA and particle swarm optimization (PSO in cash balance management using Miller-Orr model, which consists in a stochastic model that does not define a single ideal point for cash balance, but an oscillation range between a lower bound, an ideal balance and an upper bound. Thus, this paper proposes the application of GA and PSO to minimize the Total Cost of cash maintenance, obtaining the parameter of the lower bound of the Miller-Orr model, using for this the assumptions presented in literature. Computational experiments were applied in the development and validation of the models. The results indicated that both the GA and PSO are applicable in determining the cash level from the lower limit, with best results of PSO model, which had not yet been applied in this type of problem.O presente trabalho tem por objetivo a aplicação de algoritmos genéticos (AG e particle swarm optimization (PSO no gerenciamento do saldo de caixa, a partir do modelo Miller-Orr, que consiste em um modelo estocástico que não define um único ponto ideal para o saldo de caixa, mas uma faixa de oscilação entre um limite inferior, um saldo ideal e um limite superior. Assim, este trabalho propõe a aplicação de AG e PSO, para minimizar o Custo Total de manutenção do saldo de caixa, obtendo o parâmetro de limite inferior do modelo Miller-Orr, utilizando para isso premissas apresentadas na literatura. São aplicados experimentos computacionais no desenvolvimento e validação dos modelos. Os resultados indicam que tanto AG quanto PSO são aplicáveis na determinação do nível de caixa a partir do limite inferior, com melhores resultados do modelo PSO, que até então não havia sido aplicado neste tipo de problema.
International Nuclear Information System (INIS)
Koponen, P.
1998-01-01
Electricity cannot be stored in large quantities. That is why the electricity supply and consumption are always almost equal in large power supply systems. If this balance were disturbed beyond stability, the system or a part of it would collapse until a new stable equilibrium is reached. The balance between supply and consumption is mainly maintained by controlling the power production, but also the electricity consumption or, in other words, the load is controlled. Controlling the load of the power supply system is important, if easily controllable power production capacity is limited. Temporary shortage of capacity causes high peaks in the energy price in the electricity market. Load control either reduces the electricity consumption during peak consumption and peak price or moves electricity consumption to some other time. The project Optimisation of Load Control is a part of the EDISON research program for distribution automation. The following areas were studied: Optimization of space heating and ventilation, when electricity price is time variable, load control model in power purchase optimization, optimization of direct load control sequences, interaction between load control optimization and power purchase optimization, literature on load control, optimization methods and field tests and response models of direct load control and the effects of the electricity market deregulation on load control. An overview of the main results is given in this chapter
Energy Technology Data Exchange (ETDEWEB)
Koponen, P [VTT Energy, Espoo (Finland)
1998-08-01
Electricity cannot be stored in large quantities. That is why the electricity supply and consumption are always almost equal in large power supply systems. If this balance were disturbed beyond stability, the system or a part of it would collapse until a new stable equilibrium is reached. The balance between supply and consumption is mainly maintained by controlling the power production, but also the electricity consumption or, in other words, the load is controlled. Controlling the load of the power supply system is important, if easily controllable power production capacity is limited. Temporary shortage of capacity causes high peaks in the energy price in the electricity market. Load control either reduces the electricity consumption during peak consumption and peak price or moves electricity consumption to some other time. The project Optimisation of Load Control is a part of the EDISON research program for distribution automation. The following areas were studied: Optimization of space heating and ventilation, when electricity price is time variable, load control model in power purchase optimization, optimization of direct load control sequences, interaction between load control optimization and power purchase optimization, literature on load control, optimization methods and field tests and response models of direct load control and the effects of the electricity market deregulation on load control. An overview of the main results is given in this chapter
DEFF Research Database (Denmark)
Walther-Hansen, Mads
2016-01-01
is not thoroughly understood. In this paper I treat balance as a metaphor that we use to reason about several different actions in music production, such as adjusting levels, editing the frequency spectrum or the spatiality of the recording. This study is based on an exploration of a linguistic corpus of sound......This paper explores the concept of balance in music production and examines the role of conceptual metaphors in reasoning about audio editing. Balance may be the most central concept in record production, however, the way we cognitively understand and respond meaningfully to a mix requiring balance...
Directory of Open Access Journals (Sweden)
Hussein A. Kazem
2013-01-01
Full Text Available This paper presents a method for determining optimal sizes of PV array, wind turbine, diesel generator, and storage battery installed in a building integrated system. The objective of the proposed optimization is to design the system that can supply a building load demand at minimum cost and maximum availability. The mathematical models for the system components as well as meteorological variables such as solar energy, temperature, and wind speed are employed for this purpose. Moreover, the results showed that the optimum sizing ratios (the daily energy generated by the source to the daily energy demand for the PV array, wind turbine, diesel generator, and battery for a system located in Sohar, Oman, are 0.737, 0.46, 0.22, and 0.17, respectively. A case study represented by a system consisting of 30 kWp PV array (36%, 18 kWp wind farm (55%, and 5 kVA diesel generator (9% is presented. This system is supposed to power a 200 kWh/day load demand. It is found that the generated energy share of the PV array, wind farm, and diesel generator is 36%, 55%, and 9%, respectively, while the cost of energy is 0.17 USD/kWh.
PARALLEL ADAPTIVE MULTILEVEL SAMPLING ALGORITHMS FOR THE BAYESIAN ANALYSIS OF MATHEMATICAL MODELS
Prudencio, Ernesto; Cheung, Sai Hung
2012-01-01
In recent years, Bayesian model updating techniques based on measured data have been applied to many engineering and applied science problems. At the same time, parallel computational platforms are becoming increasingly more powerful and are being used more frequently by the engineering and scientific communities. Bayesian techniques usually require the evaluation of multi-dimensional integrals related to the posterior probability density function (PDF) of uncertain model parameters. The fact that such integrals cannot be computed analytically motivates the research of stochastic simulation methods for sampling posterior PDFs. One such algorithm is the adaptive multilevel stochastic simulation algorithm (AMSSA). In this paper we discuss the parallelization of AMSSA, formulating the necessary load balancing step as a binary integer programming problem. We present a variety of results showing the effectiveness of load balancing on the overall performance of AMSSA in a parallel computational environment.
Part of being an Active, More Powerful You means finding balance in your daily life: taking on the Must-dos and finding time for some Should Dos and Want-to-Dos. Sometimes, emotions and commitments can come into play and upset the balance.
Brus, D.J.
2015-01-01
In balanced sampling a linear relation between the soil property of interest and one or more covariates with known means is exploited in selecting the sampling locations. Recent developments make this sampling design attractive for statistical soil surveys. This paper introduces balanced sampling
Workflow Scheduling Using Hybrid GA-PSO Algorithm in Cloud Computing
Directory of Open Access Journals (Sweden)
Ahmad M. Manasrah
2018-01-01
Full Text Available Cloud computing environment provides several on-demand services and resource sharing for clients. Business processes are managed using the workflow technology over the cloud, which represents one of the challenges in using the resources in an efficient manner due to the dependencies between the tasks. In this paper, a Hybrid GA-PSO algorithm is proposed to allocate tasks to the resources efficiently. The Hybrid GA-PSO algorithm aims to reduce the makespan and the cost and balance the load of the dependent tasks over the heterogonous resources in cloud computing environments. The experiment results show that the GA-PSO algorithm decreases the total execution time of the workflow tasks, in comparison with GA, PSO, HSGA, WSGA, and MTCT algorithms. Furthermore, it reduces the execution cost. In addition, it improves the load balancing of the workflow application over the available resources. Finally, the obtained results also proved that the proposed algorithm converges to optimal solutions faster and with higher quality compared to other algorithms.
Optimal loading and protection of multi-state systems considering performance sharing mechanism
International Nuclear Information System (INIS)
Xiao, Hui; Shi, Daimin; Ding, Yi; Peng, Rui
2016-01-01
Engineering systems are designed to carry the load. The performance of the system largely depends on how much load it carries. On the other hand, the failure rate of the system is strongly affected by its load. Besides internal failures, such as fatigue and aging process, systems may also fail due to external impacts such as nature disasters and terrorism. In this paper, we integrate the effect of loading and protection of external impacts on multi-state systems with performance sharing mechanism. The objective of this research is to determine how to balance the load and protection on system elements. An availability evaluation algorithm of the proposed system is suggested and the corresponding optimization problem is solved utilizing genetic algorithms. - Highlights: • Performance sharing of multi-state systems is considered. • The effect of load on system elements is analyzed. • Joint optimization model of element loading and protection is formulated. • Genetic Algorithms are adapted to solve the reliability optimization problem.
Query Load Balancing For Visible Object Extraction
DEFF Research Database (Denmark)
Bukauskas, Linas; Bøhlen, Michael Hanspeter
2004-01-01
Interactive visual data explorations impose rigid real-time requirements on the extraction of visible objects. Often these requirements are met by deploying powerful hardware that maintains the entire data set in huge main memory structures. In this paper we propose an approach that retrieves...... the visible data on demand and is based on a tight integration of the database and visualization systems. We propose to incrementally adjust the observer path by adding and dropping path points. The result is an optimal path that minimizes the interaction with the database system and retrieves all visible...
Cell Load Balancing in Heterogeneous Scenarios
DEFF Research Database (Denmark)
Eduardo, Simao; Rodrigues, Antonio; Mihovska, Albena D.
2013-01-01
. It jointly performs congestion control and inter-cell interference avoidance by means of a utility describing the cell's channel. Centralized and uncoordinated schemes are studied. The first is defined as an integer linear program, while the second builds on the best channel utility developed for the first...
A comparative experiment in distributed load balancing
Randles, Martin; Odat, Enas M.; Lamb, David J.; Osama, Abu Rahmeh; Taleb-Bendiab, Azzelarabe
2009-01-01
The anticipated uptake of Cloud computing, built on the well-established research fields of web services, networks, utility computing, distributed computing and virtualisation, will bring many advantages in cost, flexibility and availability
Power load balancing in cellular networks
2010-01-01
In one aspect, a system is provided. In one embodiment, the system includes a plurality of wireless base stations that are located in a contiguous spatial coverage region of a cellular communication system. Each wireless base station that is configured to generate a coverage pilot beam to enable
Directory of Open Access Journals (Sweden)
S. N. Syed Nasir
2018-01-01
Full Text Available This research is focusing on optimal placement and sizing of multiple variable passive filter (VPF to mitigate harmonic distortion due to charging station (CS at 449 bus distribution network. There are 132 units of CS which are scheduled based on user behaviour within 24 hours, with the interval of 15 minutes. By considering the varying of CS patterns and harmonic impact, Modified Lightning Search Algorithm (MLSA is used to find 22 units of VPF coordination, so that less harmonics will be injected from 415 V bus to the medium voltage network and power loss is also reduced. Power system harmonic flow, VPF, CS, battery, and the analysis will be modelled in MATLAB/m-file platform. High Performance Computing (HPC is used to make simulation faster. Pareto-Fuzzy technique is used to obtain sizing of VPF from all nondominated solutions. From the result, the optimal placements and sizes of VPF are able to reduce the maximum THD for voltage and current and also the total apparent losses up to 39.14%, 52.5%, and 2.96%, respectively. Therefore, it can be concluded that the MLSA is suitable method to mitigate harmonic and it is beneficial in minimizing the impact of aggressive CS installation at distribution network.
DEFF Research Database (Denmark)
Mahnke, Martina; Uprichard, Emma
2014-01-01
Imagine sailing across the ocean. The sun is shining, vastness all around you. And suddenly [BOOM] you’ve hit an invisible wall. Welcome to the Truman Show! Ever since Eli Pariser published his thoughts on a potential filter bubble, this movie scenario seems to have become reality, just with slight...... changes: it’s not the ocean, it’s the internet we’re talking about, and it’s not a TV show producer, but algorithms that constitute a sort of invisible wall. Building on this assumption, most research is trying to ‘tame the algorithmic tiger’. While this is a valuable and often inspiring approach, we...
Algorithms in combinatorial design theory
Colbourn, CJ
1985-01-01
The scope of the volume includes all algorithmic and computational aspects of research on combinatorial designs. Algorithmic aspects include generation, isomorphism and analysis techniques - both heuristic methods used in practice, and the computational complexity of these operations. The scope within design theory includes all aspects of block designs, Latin squares and their variants, pairwise balanced designs and projective planes and related geometries.
Directory of Open Access Journals (Sweden)
Kaup Magdalena
2016-12-01
Full Text Available This paper presents the methodology of strength verification during load out of the heavy cargo, in this case Arkutun Dagi SE-Topside platform. General methodology of making calculation models and load algorithms has been presented. Paper shows results of verification of global shear forces and bending moments using self-developed algorithms to modify centre of gravity, fill tanks and hydrostatically balance a 3D finite element model with commercial hydrostatic code. The NAPA and ANSYS codes were used to calculate hydrostatic pressures and to apply to 3D-FE models and to carry out strength calculation of barge construction.
Analysis of the type II robotic mixed-model assembly line balancing problem
Çil, Zeynel Abidin; Mete, Süleyman; Ağpak, Kürşad
2017-06-01
In recent years, there has been an increasing trend towards using robots in production systems. Robots are used in different areas such as packaging, transportation, loading/unloading and especially assembly lines. One important step in taking advantage of robots on the assembly line is considering them while balancing the line. On the other hand, market conditions have increased the importance of mixed-model assembly lines. Therefore, in this article, the robotic mixed-model assembly line balancing problem is studied. The aim of this study is to develop a new efficient heuristic algorithm based on beam search in order to minimize the sum of cycle times over all models. In addition, mathematical models of the problem are presented for comparison. The proposed heuristic is tested on benchmark problems and compared with the optimal solutions. The results show that the algorithm is very competitive and is a promising tool for further research.
Duval, R. W.; Bahrami, M.
1985-01-01
The Rotor Systems Research Aircraft uses load cells to isolate the rotor/transmission systm from the fuselage. A mathematical model relating applied rotor loads and inertial loads of the rotor/transmission system to the load cell response is required to allow the load cells to be used to estimate rotor loads from flight data. Such a model is derived analytically by applying a force and moment balance to the isolated rotor/transmission system. The model is tested by comparing its estimated values of applied rotor loads with measured values obtained from a ground based shake test. Discrepancies in the comparison are used to isolate sources of unmodeled external loads. Once the structure of the mathematical model has been validated by comparison with experimental data, the parameters must be identified. Since the parameters may vary with flight condition it is desirable to identify the parameters directly from the flight data. A Maximum Likelihood identification algorithm is derived for this purpose and tested using a computer simulation of load cell data. The identification is found to converge within 10 samples. The rapid convergence facilitates tracking of time varying parameters of the load cell model in flight.
Choudhary, Alok Nidhi; Leung, Mun K.; Huang, Thomas S.; Patel, Janak H.
1989-01-01
Several techniques to perform static and dynamic load balancing techniques for vision systems are presented. These techniques are novel in the sense that they capture the computational requirements of a task by examining the data when it is produced. Furthermore, they can be applied to many vision systems because many algorithms in different systems are either the same, or have similar computational characteristics. These techniques are evaluated by applying them on a parallel implementation of the algorithms in a motion estimation system on a hypercube multiprocessor system. The motion estimation system consists of the following steps: (1) extraction of features; (2) stereo match of images in one time instant; (3) time match of images from different time instants; (4) stereo match to compute final unambiguous points; and (5) computation of motion parameters. It is shown that the performance gains when these data decomposition and load balancing techniques are used are significant and the overhead of using these techniques is minimal.
De Götzen , Amalia; Mion , Luca; Tache , Olivier
2007-01-01
International audience; We call sound algorithms the categories of algorithms that deal with digital sound signal. Sound algorithms appeared in the very infancy of computer. Sound algorithms present strong specificities that are the consequence of two dual considerations: the properties of the digital sound signal itself and its uses, and the properties of auditory perception.
Wang, Lui; Bayer, Steven E.
1991-01-01
Genetic algorithms are mathematical, highly parallel, adaptive search procedures (i.e., problem solving methods) based loosely on the processes of natural genetics and Darwinian survival of the fittest. Basic genetic algorithms concepts are introduced, genetic algorithm applications are introduced, and results are presented from a project to develop a software tool that will enable the widespread use of genetic algorithm technology.
O'Dell, Robin S.
2012-01-01
There are two primary interpretations of the mean: as a leveler of data (Uccellini 1996, pp. 113-114) and as a balance point of a data set. Typically, both interpretations of the mean are ignored in elementary school and middle school curricula. They are replaced with a rote emphasis on calculation using the standard algorithm. When students are…
Workload Balancing on Heterogeneous Systems: A Case Study of Sparse Grid Interpolation
Muraraşu, Alin; Weidendorfer, Josef; Bode, Arndt
2012-01-01
load balancing is essential. This paper proposes static and dynamic solutions for load balancing in the context of an application for visualizing high-dimensional simulation data. The application relies on the sparse grid technique for data compression
... vertigo. If you have additional problems with motor control, such as weakness, slowness, tremor, or rigidity, you can lose your ability to recover properly from imbalance. This raises the risk of falling and injury. What are some types of balance disorders? There are more than a dozen different ...
Mills, Allan
2014-01-01
Theory predicts that an egg-shaped body should rest in stable equilibrium when on its side, balance vertically in metastable equilibrium on its broad end and be completely unstable on its narrow end. A homogeneous solid egg made from wood, clay or plastic behaves in this way, but a real egg will not stand on either end. It is shown that this…
Parallel Computing Strategies for Irregular Algorithms
Biswas, Rupak; Oliker, Leonid; Shan, Hongzhang; Biegel, Bryan (Technical Monitor)
2002-01-01
Parallel computing promises several orders of magnitude increase in our ability to solve realistic computationally-intensive problems, but relies on their efficient mapping and execution on large-scale multiprocessor architectures. Unfortunately, many important applications are irregular and dynamic in nature, making their effective parallel implementation a daunting task. Moreover, with the proliferation of parallel architectures and programming paradigms, the typical scientist is faced with a plethora of questions that must be answered in order to obtain an acceptable parallel implementation of the solution algorithm. In this paper, we consider three representative irregular applications: unstructured remeshing, sparse matrix computations, and N-body problems, and parallelize them using various popular programming paradigms on a wide spectrum of computer platforms ranging from state-of-the-art supercomputers to PC clusters. We present the underlying problems, the solution algorithms, and the parallel implementation strategies. Smart load-balancing, partitioning, and ordering techniques are used to enhance parallel performance. Overall results demonstrate the complexity of efficiently parallelizing irregular algorithms.
Fatigue evaluation algorithms: Review
Energy Technology Data Exchange (ETDEWEB)
Passipoularidis, V.A.; Broendsted, P.
2009-11-15
A progressive damage fatigue simulator for variable amplitude loads named FADAS is discussed in this work. FADAS (Fatigue Damage Simulator) performs ply by ply stress analysis using classical lamination theory and implements adequate stiffness discount tactics based on the failure criterion of Puck, to model the degradation caused by failure events in ply level. Residual strength is incorporated as fatigue damage accumulation metric. Once the typical fatigue and static properties of the constitutive ply are determined,the performance of an arbitrary lay-up under uniaxial and/or multiaxial load time series can be simulated. The predictions are validated against fatigue life data both from repeated block tests at a single stress ratio as well as against spectral fatigue using the WISPER, WISPERX and NEW WISPER load sequences on a Glass/Epoxy multidirectional laminate typical of a wind turbine rotor blade construction. Two versions of the algorithm, the one using single-step and the other using incremental application of each load cycle (in case of ply failure) are implemented and compared. Simulation results confirm the ability of the algorithm to take into account load sequence effects. In general, FADAS performs well in predicting life under both spectral and block loading fatigue. (author)
A survey of parallel multigrid algorithms
Chan, Tony F.; Tuminaro, Ray S.
1987-01-01
A typical multigrid algorithm applied to well-behaved linear-elliptic partial-differential equations (PDEs) is described. Criteria for designing and evaluating parallel algorithms are presented. Before evaluating the performance of some parallel multigrid algorithms, consideration is given to some theoretical complexity results for solving PDEs in parallel and for executing the multigrid algorithm. The effect of mapping and load imbalance on the partial efficiency of the algorithm is studied.
Joux, Antoine
2009-01-01
Illustrating the power of algorithms, Algorithmic Cryptanalysis describes algorithmic methods with cryptographically relevant examples. Focusing on both private- and public-key cryptographic algorithms, it presents each algorithm either as a textual description, in pseudo-code, or in a C code program.Divided into three parts, the book begins with a short introduction to cryptography and a background chapter on elementary number theory and algebra. It then moves on to algorithms, with each chapter in this section dedicated to a single topic and often illustrated with simple cryptographic applic
Fluid structure coupling algorithm
International Nuclear Information System (INIS)
McMaster, W.H.; Gong, E.Y.; Landram, C.S.; Quinones, D.F.
1980-01-01
A fluid-structure-interaction algorithm has been developed and incorporated into the two-dimensional code PELE-IC. This code combines an Eulerian incompressible fluid algorithm with a Lagrangian finite element shell algorithm and incorporates the treatment of complex free surfaces. The fluid structure and coupling algorithms have been verified by the calculation of solved problems from the literature and from air and steam blowdown experiments. The code has been used to calculate loads and structural response from air blowdown and the oscillatory condensation of steam bubbles in water suppression pools typical of boiling water reactors. The techniques developed have been extended to three dimensions and implemented in the computer code PELE-3D
A new distributed systems scheduling algorithm: a swarm intelligence approach
Haghi Kashani, Mostafa; Sarvizadeh, Raheleh; Jameii, Mahdi
2011-12-01
The scheduling problem in distributed systems is known as an NP-complete problem, and methods based on heuristic or metaheuristic search have been proposed to obtain optimal and suboptimal solutions. The task scheduling is a key factor for distributed systems to gain better performance. In this paper, an efficient method based on memetic algorithm is developed to solve the problem of distributed systems scheduling. With regard to load balancing efficiently, Artificial Bee Colony (ABC) has been applied as local search in the proposed memetic algorithm. The proposed method has been compared to existing memetic-Based approach in which Learning Automata method has been used as local search. The results demonstrated that the proposed method outperform the above mentioned method in terms of communication cost.
Parallel SN algorithms in shared- and distributed-memory environments
International Nuclear Information System (INIS)
Haghighat, Alireza; Hunter, Melissa A.; Mattis, Ronald E.
1995-01-01
Different 2-D spatial domain partitioning Sn transport theory algorithms have been developed on the basis of the Block-Jacobi iterative scheme. These algorithms have been incorporated into TWOTRAN-II, and tested on a shared-memory CRAY Y-MP C90 and a distributed-memory IBM SP1. For a series of fixed source r-z geometry homogeneous problems, parallel efficiencies in a range of 50-90% are achieved on the C90 with 6 processors, and lower values (20-60%) are obtained on the SP1. It is demonstrated that better performance is attainable if one addresses issues such as convergence rate, load-balancing, and granularity for both architectures, as well as message passing (network bandwidth and latency) for SP1. (author). 17 refs, 4 figs
Balanced truncation for linear switched systems
DEFF Research Database (Denmark)
Petreczky, Mihaly; Wisniewski, Rafal; Leth, John-Josef
2013-01-01
In this paper, we present a theoretical analysis of the model reduction algorithm for linear switched systems from Shaker and Wisniewski (2011, 2009) and . This algorithm is a reminiscence of the balanced truncation method for linear parameter varying systems (Wood et al., 1996) [3]. Specifically...
Directory of Open Access Journals (Sweden)
Álvaro Jaramillo-Duque
2018-02-01
Full Text Available In this paper, a model and solution approach for minimizing internal power losses in Transformers Connected in Parallel (TCP with tap-changers is proposed. The model is based on power chargeability balance and seeks to keep the load voltage within an admissible range. For achieving this, tap positions are adjusted in such a way that all TCP are set in similar/same power chargeability. The main contribution of this paper is the inclusion of several construction features (rated voltage, rated power, voltage ratio, short-circuit impedance and tap steps in the minimization of power losses in TCP that are not included in previous works. A Genetic Algorithm (GA is used for solving the proposed model that is a system of nonlinear equations with discrete decision variables. The GA scans different sets for tap positions with the aim of balancing the power supplied by each transformer to the load. For this purpose, a fitness function is used for minimizing two conditions: The first condition consists on the mismatching between power chargeability for each transformer and a desired chargeability; and the second condition is the mismatching between the nominal load voltage and the load voltage obtained by changing the tap positions. The proposed method is generalized for any given number of TCP and was implemented for three TCP, demonstrating that the power losses are minimized and the load voltage remains within an admissible range.
Hougardy, Stefan
2016-01-01
Algorithms play an increasingly important role in nearly all fields of mathematics. This book allows readers to develop basic mathematical abilities, in particular those concerning the design and analysis of algorithms as well as their implementation. It presents not only fundamental algorithms like the sieve of Eratosthenes, the Euclidean algorithm, sorting algorithms, algorithms on graphs, and Gaussian elimination, but also discusses elementary data structures, basic graph theory, and numerical questions. In addition, it provides an introduction to programming and demonstrates in detail how to implement algorithms in C++. This textbook is suitable for students who are new to the subject and covers a basic mathematical lecture course, complementing traditional courses on analysis and linear algebra. Both authors have given this "Algorithmic Mathematics" course at the University of Bonn several times in recent years.
International Nuclear Information System (INIS)
Alsumait, J.S.; Qasem, M.; Sykulski, J.K.; Al-Othman, A.K.
2010-01-01
In this paper, an improved algorithm based on Pattern Search method (PS) to solve the Dynamic Economic Dispatch is proposed. The algorithm maintains the essential unit ramp rate constraint, along with all other necessary constraints, not only for the time horizon of operation (24 h), but it preserves these constraints through the transaction period to the next time horizon (next day) in order to avoid the discontinuity of the power system operation. The Dynamic Economic and Emission Dispatch problem (DEED) is also considered. The load balance constraints, operating limits, valve-point loading and network losses are included in the models of both DED and DEED. The numerical results clarify the significance of the improved algorithm and verify its performance.
Tel, G.
We define the notion of total algorithms for networks of processes. A total algorithm enforces that a "decision" is taken by a subset of the processes, and that participation of all processes is required to reach this decision. Total algorithms are an important building block in the design of
DEFF Research Database (Denmark)
Nygaard, Lene; Rossen, Camilla Blach; Buus, Niels
2015-01-01
This study explored how eight pregnant women diagnosed with depression managed the decision whether or not to take antidepressants during pregnancy. In total, 11 interviews were conducted and analysed by means of constructivist grounded theory. The major category constructed was Balancing risk......, with two minor categories: Assessing depression and antidepressants and Evaluating the impact of significant others. The participants tried to make the safest decision, taking all aspects of their life into consideration. They described successful decision-making in the context of managing social norms...
Renewable Distributed Generation Models in Three-Phase Load Flow Analysis for Smart Grid
Directory of Open Access Journals (Sweden)
K. M. Nor
2013-11-01
Full Text Available The paper presents renewable distributed generationÂ (RDG models as three-phase resource in load flow computation and analyzes their effect when they are connected in composite networks. The RDG models that have been considered comprise of photovoltaic (PV and wind turbine generation (WTG. The voltage-controlled node and complex power injection node are used in the models. These improvement models are suitable for smart grid power system analysis. The combination of IEEE transmission and distribution data used to test and analyze the algorithm in solving balanced/unbalanced active systems. The combination of IEEE transmission data and IEEE test feeder are used to test the the algorithm for balanced and unbalanced multi-phase distribution system problem. The simulation results show that by increased number and size of RDG units have improved voltage profile and reduced system losses.
Load management through agent based coordination of flexible electricity consumers
DEFF Research Database (Denmark)
Clausen, Anders; Demazeau, Yves; Jørgensen, Bo Nørregaard
2015-01-01
Demand Response (DR) offers a cost-effective and carbonfriendly way of performing load balancing. DR describes a change in the electricity consumption of flexible consumers in response to the supply situation. In DR, flexible consumers may perform their own load balancing through load management...
A combination of clinical balance measures and FRAX? to improve identification of high-risk fallers
Najafi, David A.; Dahlberg, Leif E.; Hansson, Eva Ekvall
2016-01-01
Background The FRAX? algorithm quantifies a patient?s 10-year probability of a hip or major osteoporotic fracture without taking an individual?s balance into account. Balance measures assess the functional ability of an individual and the FRAX? algorithm is a model that integrates the individual patients clinical risk factors [not balance] and bone mineral density. Thus, clinical balance measures capture aspects that the FRAX? algorithm does not, and vice versa. It is therefore possible that ...
Ocean Tide Loading Computation
Agnew, Duncan Carr
2005-01-01
September 15,2003 through May 15,2005 This grant funds the maintenance, updating, and distribution of programs for computing ocean tide loading, to enable the corrections for such loading to be more widely applied in space- geodetic and gravity measurements. These programs, developed under funding from the CDP and DOSE programs, incorporate the most recent global tidal models developed from Topex/Poscidon data, and also local tide models for regions around North America; the design of the algorithm and software makes it straightforward to combine local and global models.
KAM Tori Construction Algorithms
Wiesel, W.
In this paper we evaluate and compare two algorithms for the calculation of KAM tori in Hamiltonian systems. The direct fitting of a torus Fourier series to a numerically integrated trajectory is the first method, while an accelerated finite Fourier transform is the second method. The finite Fourier transform, with Hanning window functions, is by far superior in both computational loading and numerical accuracy. Some thoughts on applications of KAM tori are offered.
Directory of Open Access Journals (Sweden)
Maryam Shokouhi
2017-06-01
Full Text Available Distribution networks are designed as a ring and operated as a radial form. Therefore, the reconfiguration is a simple and cost-effective way to use existing facilities without the need for any new equipment in distribution networks to achieve various objectives such as: power loss reduction, feeder overload reduction, load balancing, voltage profile improvement, reducing the number of switching considering constraints that ultimately result in the power loss reduction. In this paper, a new method based on the Ant Lion algorithm (a modern meta-heuristic algorithm is provided for the reconfiguration of distribution networks. Considering the extension of the distribution networks and complexity of their communications networks, and the various parameters, using smart techniques is inevitable. The proposed approach is tested on the IEEE 33 & 69-bus radial standard distribution networks. The Evaluation of results in MATLAB software shows the effectiveness of the Ant Lion algorithm in the distribution network reconfiguration.
Kinetic-Monte-Carlo-Based Parallel Evolution Simulation Algorithm of Dust Particles
Directory of Open Access Journals (Sweden)
Xiaomei Hu
2014-01-01
Full Text Available The evolution simulation of dust particles provides an important way to analyze the impact of dust on the environment. KMC-based parallel algorithm is proposed to simulate the evolution of dust particles. In the parallel evolution simulation algorithm of dust particles, data distribution way and communication optimizing strategy are raised to balance the load of every process and reduce the communication expense among processes. The experimental results show that the simulation of diffusion, sediment, and resuspension of dust particles in virtual campus is realized and the simulation time is shortened by parallel algorithm, which makes up for the shortage of serial computing and makes the simulation of large-scale virtual environment possible.
A Novel Algorithm of Quantum Random Walk in Server Traffic Control and Task Scheduling
Directory of Open Access Journals (Sweden)
Dong Yumin
2014-01-01
Full Text Available A quantum random walk optimization model and algorithm in network cluster server traffic control and task scheduling is proposed. In order to solve the problem of server load balancing, we research and discuss the distribution theory of energy field in quantum mechanics and apply it to data clustering. We introduce the method of random walk and illuminate what the quantum random walk is. Here, we mainly research the standard model of one-dimensional quantum random walk. For the data clustering problem of high dimensional space, we can decompose one m-dimensional quantum random walk into m one-dimensional quantum random walk. In the end of the paper, we compare the quantum random walk optimization method with GA (genetic algorithm, ACO (ant colony optimization, and SAA (simulated annealing algorithm. In the same time, we prove its validity and rationality by the experiment of analog and simulation.
Partial storage optimization and load control strategy of cloud data centers.
Al Nuaimi, Klaithem; Mohamed, Nader; Al Nuaimi, Mariam; Al-Jaroodi, Jameela
2015-01-01
We present a novel approach to solve the cloud storage issues and provide a fast load balancing algorithm. Our approach is based on partitioning and concurrent dual direction download of the files from multiple cloud nodes. Partitions of the files are saved on the cloud rather than the full files, which provide a good optimization to the cloud storage usage. Only partial replication is used in this algorithm to ensure the reliability and availability of the data. Our focus is to improve the performance and optimize the storage usage by providing the DaaS on the cloud. This algorithm solves the problem of having to fully replicate large data sets, which uses up a lot of precious space on the cloud nodes. Reducing the space needed will help in reducing the cost of providing such space. Moreover, performance is also increased since multiple cloud servers will collaborate to provide the data to the cloud clients in a faster manner.
Partial Storage Optimization and Load Control Strategy of Cloud Data Centers
2015-01-01
We present a novel approach to solve the cloud storage issues and provide a fast load balancing algorithm. Our approach is based on partitioning and concurrent dual direction download of the files from multiple cloud nodes. Partitions of the files are saved on the cloud rather than the full files, which provide a good optimization to the cloud storage usage. Only partial replication is used in this algorithm to ensure the reliability and availability of the data. Our focus is to improve the performance and optimize the storage usage by providing the DaaS on the cloud. This algorithm solves the problem of having to fully replicate large data sets, which uses up a lot of precious space on the cloud nodes. Reducing the space needed will help in reducing the cost of providing such space. Moreover, performance is also increased since multiple cloud servers will collaborate to provide the data to the cloud clients in a faster manner. PMID:25973444
Balancing supply and demand resources
International Nuclear Information System (INIS)
Sinha, J.; Saleeby, R.G.
1990-01-01
This article deals with using demand-side management (DSM) resources as an effective means of balancing supply and demand as a part of least-cost planning. The authors present a more sophisticated application of the load forecast adjustment method that reduces the number of DSM programs that need to be evaluated and provides blocks large enough to eliminate resolution problems in production costing models
Directory of Open Access Journals (Sweden)
Houda Jouini
2010-01-01
Full Text Available As a perspective to ensure the power system stability and to avoid the vulnerability leading to the blackouts, several preventive and curative means are adopted. In order to avoid the voltage collapse, load shedding schemes represent a suitable action to maintain the power system service quality and to control its vulnerability. In this paper, we try to propose an intelligent load shedding strategy as a new approach based on fuzzy controllers. This strategy was founded on the calculation of generated power sensitivity degree related to those injected at different network buses. During the fault phase, fuzzy controller algorithms generate monitor vectors ensuring a precalculated load shedding ratio in the purpose to reestablish the power balance and conduct the network to a new steady state.
International Nuclear Information System (INIS)
Horton, S.G.
1984-01-01
The author presents a system planning perspective on how Ontario Hydro is viewing the future, and where nuclear power fits into that future. Before the 1980s Ontario experienced a steady seven percent per year growth in power demand. Shifting patterns of energy demand have made planning much more difficult. In the early 80s growth in demand fell short of predictions. It is hard to tell what level of demand to plan for in the future. With respect to any energy option, a utility planner or board of directors would want to know when it will be delivered, what it will cost when it is delivered, what it will cost to operate, how long it will last as an economic energy producer, and how all of these factors will be affected by future changes. Ontario Hydro's studies show that nuclear power continues to be the preferred option for large blocks of base load capacity. By 1996 Ontario Hydro will have saved about 10 billion 1983 dollars by using nuclear power. The utility continues to study both sides of the supply-demand equation, looking at conservation as an alternative to constructing new generating facilities and attempting to become aware of shifts in demand trends as soon as they happen
International Nuclear Information System (INIS)
Mak, H.
1995-01-01
Slides used in a presentation at The Power of Change Conference in Vancouver, BC in April 1995 about the changing needs for load forecasting were presented. Technological innovations and population increase were said to be the prime driving forces behind the changing needs in load forecasting. Structural changes, market place changes, electricity supply planning changes, and changes in planning objectives were other factors discussed. It was concluded that load forecasting was a form of information gathering, that provided important market intelligence
Energy Technology Data Exchange (ETDEWEB)
O' Brien, M. J.; Brantley, P. S.
2015-01-20
In order to run Monte Carlo particle transport calculations on new supercomputers with hundreds of thousands or millions of processors, care must be taken to implement scalable algorithms. This means that the algorithms must continue to perform well as the processor count increases. In this paper, we examine the scalability of:(1) globally resolving the particle locations on the correct processor, (2) deciding that particle streaming communication has finished, and (3) efficiently coupling neighbor domains together with different replication levels. We have run domain decomposed Monte Carlo particle transport on up to 2^{21} = 2,097,152 MPI processes on the IBM BG/Q Sequoia supercomputer and observed scalable results that agree with our theoretical predictions. These calculations were carefully constructed to have the same amount of work on every processor, i.e. the calculation is already load balanced. We also examine load imbalanced calculations where each domain’s replication level is proportional to its particle workload. In this case we show how to efficiently couple together adjacent domains to maintain within workgroup load balance and minimize memory usage.
Automatic load sharing in inverter modules
Nagano, S.
1979-01-01
Active feedback loads transistor equally with little power loss. Circuit is suitable for balancing modular inverters in spacecraft, computer power supplies, solar-electric power generators, and electric vehicles. Current-balancing circuit senses differences between collector current for power transistor and average value of load currents for all power transistors. Principle is effective not only in fixed duty-cycle inverters but also in converters operating at variable duty cycles.
An Algorithmic Diversity Diet?
DEFF Research Database (Denmark)
Sørensen, Jannick Kirk; Schmidt, Jan-Hinrik
2016-01-01
With the growing influence of personalized algorithmic recommender systems on the exposure of media content to users, the relevance of discussing the diversity of recommendations increases, particularly as far as public service media (PSM) is concerned. An imagined implementation of a diversity...... diet system however triggers not only the classic discussion of the reach – distinctiveness balance for PSM, but also shows that ‘diversity’ is understood very differently in algorithmic recommender system communities than it is editorially and politically in the context of PSM. The design...... of a diversity diet system generates questions not just about editorial power, personal freedom and techno-paternalism, but also about the embedded politics of recommender systems as well as the human skills affiliated with PSM editorial work and the nature of PSM content....
Day-ahead residential load forecasting with artificial neural network using smart meter data
Asare-Bediako, B.; Kling, W.L.; Ribeiro, P.F.
2013-01-01
Load forecasting is an important operational procedure for the electric industry particularly in a liberalized, deregulated environment. It enables the prediction of utilization of assets, provides input for load/supply balancing and supports optimal energy utilization. Current residential load
Multimodal Estimation of Distribution Algorithms.
Yang, Qiang; Chen, Wei-Neng; Li, Yun; Chen, C L Philip; Xu, Xiang-Min; Zhang, Jun
2016-02-15
Taking the advantage of estimation of distribution algorithms (EDAs) in preserving high diversity, this paper proposes a multimodal EDA. Integrated with clustering strategies for crowding and speciation, two versions of this algorithm are developed, which operate at the niche level. Then these two algorithms are equipped with three distinctive techniques: 1) a dynamic cluster sizing strategy; 2) an alternative utilization of Gaussian and Cauchy distributions to generate offspring; and 3) an adaptive local search. The dynamic cluster sizing affords a potential balance between exploration and exploitation and reduces the sensitivity to the cluster size in the niching methods. Taking advantages of Gaussian and Cauchy distributions, we generate the offspring at the niche level through alternatively using these two distributions. Such utilization can also potentially offer a balance between exploration and exploitation. Further, solution accuracy is enhanced through a new local search scheme probabilistically conducted around seeds of niches with probabilities determined self-adaptively according to fitness values of these seeds. Extensive experiments conducted on 20 benchmark multimodal problems confirm that both algorithms can achieve competitive performance compared with several state-of-the-art multimodal algorithms, which is supported by nonparametric tests. Especially, the proposed algorithms are very promising for complex problems with many local optima.
Algorithms for parallel flow solvers on message passing architectures
Vanderwijngaart, Rob F.
1995-01-01
The purpose of this project has been to identify and test suitable technologies for implementation of fluid flow solvers -- possibly coupled with structures and heat equation solvers -- on MIMD parallel computers. In the course of this investigation much attention has been paid to efficient domain decomposition strategies for ADI-type algorithms. Multi-partitioning derives its efficiency from the assignment of several blocks of grid points to each processor in the parallel computer. A coarse-grain parallelism is obtained, and a near-perfect load balance results. In uni-partitioning every processor receives responsibility for exactly one block of grid points instead of several. This necessitates fine-grain pipelined program execution in order to obtain a reasonable load balance. Although fine-grain parallelism is less desirable on many systems, especially high-latency networks of workstations, uni-partition methods are still in wide use in production codes for flow problems. Consequently, it remains important to achieve good efficiency with this technique that has essentially been superseded by multi-partitioning for parallel ADI-type algorithms. Another reason for the concentration on improving the performance of pipeline methods is their applicability in other types of flow solver kernels with stronger implied data dependence. Analytical expressions can be derived for the size of the dynamic load imbalance incurred in traditional pipelines. From these it can be determined what is the optimal first-processor retardation that leads to the shortest total completion time for the pipeline process. Theoretical predictions of pipeline performance with and without optimization match experimental observations on the iPSC/860 very well. Analysis of pipeline performance also highlights the effect of uncareful grid partitioning in flow solvers that employ pipeline algorithms. If grid blocks at boundaries are not at least as large in the wall-normal direction as those
Energy conservation in Newmark based time integration algorithms
DEFF Research Database (Denmark)
Krenk, Steen
2006-01-01
Energy balance equations are established for the Newmark time integration algorithm, and for the derived algorithms with algorithmic damping introduced via averaging, the so-called a-methods. The energy balance equations form a sequence applicable to: Newmark integration of the undamped equations...... of motion, an extended form including structural damping, and finally the generalized form including structural as well as algorithmic damping. In all three cases the expression for energy, appearing in the balance equation, is the mechanical energy plus some additional terms generated by the discretization...
International Nuclear Information System (INIS)
Sinitsyn, Nikolai A.; Kundu, Soumya; Backhaus, Scott
2013-01-01
Highlights: ► Algorithms to produce useful load response from a heterogeneous group of TCLs. ► Generation of sharp power pulses without initiating any unwanted oscillation. ► Open-loop methods, not requiring any detailed system modeling. ► One-way, utility-to-consumer, communication. ► Potential use in secondary frequency regulation, generation-load balancing, etc. - Abstract: We explore methods to use thermostatically controlled loads (TCLs), such as water heaters and air conditioners, to provide ancillary services by assisting in balancing generation and load. We show that by adding simple imbedded instructions and a small amount of memory to temperature controllers of TCLs, it is possible to design open-loop control algorithms capable of creating short-term pulses of demand response without unwanted power oscillations associated with temporary synchronization of the TCL dynamics. By moving a small amount of intelligence to each of the end point TCL devices, we are able to leverage our knowledge of the time dynamics of TCLs to shape the demand response pulses for different power system applications. A significant benefit of our open-loop method is the reduction from two-way to one-way broadcast communication which also eliminates many basic consumer privacy issues. In this work, we focus on developing the algorithms to generate a set of fundamental pulse shapes that can subsequently be used to create demand response with arbitrary profiles. Demand response control methods, such as the one developed here, open the door to fast, nonperturbative control of large aggregations of TCLs
Model-based Assessment for Balancing Privacy Requirements and Operational Capabilities
Energy Technology Data Exchange (ETDEWEB)
Knirsch, Fabian [Salzburg Univ. (Austria); Engel, Dominik [Salzburg Univ. (Austria); Frincu, Marc [Univ. of Southern California, Los Angeles, CA (United States); Prasanna, Viktor [Univ. of Southern California, Los Angeles, CA (United States)
2015-02-17
The smart grid changes the way energy is produced and distributed. In addition both, energy and information is exchanged bidirectionally among participating parties. Therefore heterogeneous systems have to cooperate effectively in order to achieve a common high-level use case, such as smart metering for billing or demand response for load curtailment. Furthermore, a substantial amount of personal data is often needed for achieving that goal. Capturing and processing personal data in the smart grid increases customer concerns about privacy and in addition, certain statutory and operational requirements regarding privacy aware data processing and storage have to be met. An increase of privacy constraints, however, often limits the operational capabilities of the system. In this paper, we present an approach that automates the process of finding an optimal balance between privacy requirements and operational requirements in a smart grid use case and application scenario. This is achieved by formally describing use cases in an abstract model and by finding an algorithm that determines the optimum balance by forward mapping privacy and operational impacts. For this optimal balancing algorithm both, a numeric approximation and – if feasible – an analytic assessment are presented and investigated. The system is evaluated by applying the tool to a real-world use case from the University of Southern California (USC) microgrid.
An Efficient Distributed Algorithm for Constructing Spanning Trees in Wireless Sensor Networks
Directory of Open Access Journals (Sweden)
Rosana Lachowski
2015-01-01
Full Text Available Monitoring and data collection are the two main functions in wireless sensor networks (WSNs. Collected data are generally transmitted via multihop communication to a special node, called the sink. While in a typical WSN, nodes have a sink node as the final destination for the data traffic, in an ad hoc network, nodes need to communicate with each other. For this reason, routing protocols for ad hoc networks are inefficient for WSNs. Trees, on the other hand, are classic routing structures explicitly or implicitly used in WSNs. In this work, we implement and evaluate distributed algorithms for constructing routing trees in WSNs described in the literature. After identifying the drawbacks and advantages of these algorithms, we propose a new algorithm for constructing spanning trees in WSNs. The performance of the proposed algorithm and the quality of the constructed tree were evaluated in different network scenarios. The results showed that the proposed algorithm is a more efficient solution. Furthermore, the algorithm provides multiple routes to the sensor nodes to be used as mechanisms for fault tolerance and load balancing.
Load flow analysis using decoupled fuzzy load flow under critical ...
African Journals Online (AJOL)
user
3.1 Maximum range selection of input and output variables: ..... Wong K. P., Li A., and Law M.Y., “ Advanced Constrained Genetic Algorithm Load Flow Method”, IEE Proc. ... Dr. Parimal Acharjee passed B.E.E. from North Bengal University ...
Home Appliance Load Scheduling with SEMIAH
DEFF Research Database (Denmark)
Jacobsen, Rune Hylsberg; Ghasem Azar, Armin; Zhang, Qi
2015-01-01
The European research project SEMIAH aims at designing a scalable infrastructure for residential demand response. This paper presents the progress towards a centralized load scheduling algorithm for controlling home appliances taking power grid constraints and satisfaction of consumers into account....
Boussard, Daniel
1987-01-01
We begin by giving a description of the radio-frequency generator-cavity-beam coupled system in terms of basic quantities. Taking beam loading and cavity detuning into account, expressions for the cavity impedance as seen by the generator and as seen by the beam are derived. Subsequently methods of beam-loading compensation by cavity detuning, radio-frequency feedback and feedforward are described. Examples of digital radio-frequency phase and amplitude control for the special case of superco...
International Nuclear Information System (INIS)
Creutz, M.
1987-11-01
A large variety of Monte Carlo algorithms are being used for lattice gauge simulations. For purely bosonic theories, present approaches are generally adequate; nevertheless, overrelaxation techniques promise savings by a factor of about three in computer time. For fermionic fields the situation is more difficult and less clear. Algorithms which involve an extrapolation to a vanishing step size are all quite closely related. Methods which do not require such an approximation tend to require computer time which grows as the square of the volume of the system. Recent developments combining global accept/reject stages with Langevin or microcanonical updatings promise to reduce this growth to V/sup 4/3/
Hu, T C
2002-01-01
Newly enlarged, updated second edition of a valuable text presents algorithms for shortest paths, maximum flows, dynamic programming and backtracking. Also discusses binary trees, heuristic and near optimums, matrix multiplication, and NP-complete problems. 153 black-and-white illus. 23 tables.Newly enlarged, updated second edition of a valuable, widely used text presents algorithms for shortest paths, maximum flows, dynamic programming and backtracking. Also discussed are binary trees, heuristic and near optimums, matrix multiplication, and NP-complete problems. New to this edition: Chapter 9
A Dynamic and Heuristic Phase Balancing Method for LV Feeders
Directory of Open Access Journals (Sweden)
Samad Taghipour Boroujeni
2016-01-01
Full Text Available Due to the single-phase loads and their stochastic behavior, the current in the distribution feeders is not balanced. In addition, the single-phase loads are located in different positions along the LV feeders. So the amount of the unbalanced load and its location affect the feeder losses. An unbalanced load causes the feeder losses and the voltage drop. Because of time-varying behavior of the single-phase loads, phase balancing is a dynamic and combinatorial problem. In this research, a heuristic and dynamic solution for the phase balancing of the LV feeders is proposed. In this method, it is supposed that the loads’ tie could be connected to all phases through a three-phase switch. The aim of the proposed method is to make the feeder conditions as balanced as possible. The amount and the location of single-phase loads are considered in the proposed phase balancing method. Since the proposed method needs no communication interface or no remote controller, it is inexpensive, simple, practical, and robust. Applying this method provides a distributed and dynamic phase balancing control. In addition, the feasibility of reducing the used switches is investigated. The ability of the proposed method in the phase balancing of the LV feeders is approved by carrying out some simulations.
Directory of Open Access Journals (Sweden)
Anna Bourmistrova
2011-02-01
Full Text Available The autodriver algorithm is an intelligent method to eliminate the need of steering by a driver on a well-defined road. The proposed method performs best on a four-wheel steering (4WS vehicle, though it is also applicable to two-wheel-steering (TWS vehicles. The algorithm is based on coinciding the actual vehicle center of rotation and road center of curvature, by adjusting the kinematic center of rotation. The road center of curvature is assumed prior information for a given road, while the dynamic center of rotation is the output of dynamic equations of motion of the vehicle using steering angle and velocity measurements as inputs. We use kinematic condition of steering to set the steering angles in such a way that the kinematic center of rotation of the vehicle sits at a desired point. At low speeds the ideal and actual paths of the vehicle are very close. With increase of forward speed the road and tire characteristics, along with the motion dynamics of the vehicle cause the vehicle to turn about time-varying points. By adjusting the steering angles, our algorithm controls the dynamic turning center of the vehicle so that it coincides with the road curvature center, hence keeping the vehicle on a given road autonomously. The position and orientation errors are used as feedback signals in a closed loop control to adjust the steering angles. The application of the presented autodriver algorithm demonstrates reliable performance under different driving conditions.
Directory of Open Access Journals (Sweden)
Trachuk A.R.
2017-06-01
Full Text Available This paper deals with issues of petroleum consumption in Ukraine. The dynamics of consumption of petroleum is analysed and proposed guidelines for the efficient production, consumption and import of petroleum in Ukraine. Constructed and developed predictive models of petroleum consumption in Ukraine through the use of modern software and using the group method of data handling, which allowed building adequate predictive models of petroleum consumption in the system of Ukraine’s energy balance. Researched and forecasted scenarios of petroleum consumption in the Ukraine. The problem of efficient use of energy resources is critical for sustainable economic development against the backdrop of energy saving national economy depends on energy imports, on the one hand, and rising prices for these resources. The basic foundation of the formation energy system of Ukraine is to build forecasting scenarios for different types of energy and different criteria for effective use of energy resources. Solving this problem is not only with ensuring energy security, but also with the level of development of regions of Ukraine and ensuring quality of life. Prediction of petroleum consumption in Ukraine today is an extremely important issue of strategic importance since conducted through analysis and building predictive models will be possible to develop guidelines for the efficient production and consumption of petroleum across Ukraine as a whole.
Validation of a robotic balance system for investigations in the control of human standing balance.
Luu, Billy L; Huryn, Thomas P; Van der Loos, H F Machiel; Croft, Elizabeth A; Blouin, Jean-Sébastien
2011-08-01
Previous studies have shown that human body sway during standing approximates the mechanics of an inverted pendulum pivoted at the ankle joints. In this study, a robotic balance system incorporating a Stewart platform base was developed to provide a new technique to investigate the neural mechanisms involved in standing balance. The robotic system, programmed with the mechanics of an inverted pendulum, controlled the motion of the body in response to a change in applied ankle torque. The ability of the robotic system to replicate the load properties of standing was validated by comparing the load stiffness generated when subjects balanced their own body to the robot's mechanical load programmed with a low (concentrated-mass model) or high (distributed-mass model) inertia. The results show that static load stiffness was not significantly (p > 0.05) different for standing and the robotic system. Dynamic load stiffness for the robotic system increased with the frequency of sway, as predicted by the mechanics of an inverted pendulum, with the higher inertia being accurately matched to the load properties of the human body. This robotic balance system accurately replicated the physical model of standing and represents a useful tool to simulate the dynamics of a standing person. © 2011 IEEE
Computer Applications in Balancing Chemical Equations.
Kumar, David D.
2001-01-01
Discusses computer-based approaches to balancing chemical equations. Surveys 13 methods, 6 based on matrix, 2 interactive programs, 1 stand-alone system, 1 developed in algorithm in Basic, 1 based on design engineering, 1 written in HyperCard, and 1 prepared for the World Wide Web. (Contains 17 references.) (Author/YDS)
Spatial electric load forecasting
Willis, H Lee
2002-01-01
Containing 12 new chapters, this second edition contains offers increased-coverage of weather correction and normalization of forecasts, anticipation of redevelopment, determining the validity of announced developments, and minimizing risk from over- or under-planning. It provides specific examples and detailed explanations of key points to consider for both standard and unusual utility forecasting situations, information on new algorithms and concepts in forecasting, a review of forecasting pitfalls and mistakes, case studies depicting challenging forecast environments, and load models illustrating various types of demand.
基于负载平衡配置的新型双螺杆压缩机的设计%Design of a New Twin-screw Compressor Based on Load Balanced Configuration
Institute of Scientific and Technical Information of China (English)
王小明; 杨志; 熊国良; 赵育基; 汤小明; 雷林
2012-01-01
The suction and the exhaust are arranged on both sides of traditional twin-screw compressors. When it works, the medium is compressed in axial. Shaft supports of the twin-screw are under pressure and tension on both sides because of the one-way force. Traditional twin-screw compressor's structure arrangement and design are conformed to general method of mechanical design; technical characteristics, like structure size and service life, also follow general rules of machinery. The principle, structure of a new kind of double suction balanced twin-screw compressor were introduced. Force analysis shows that this compressor can reach a balance in the axial force. The stress status of core component is improved. The structure size is minished and the work noise is reduced. The goals of saving raw materials, lowering manufacturing cost, prolonging service life are achieved.%传统的双螺杆压缩机是按一端吸气另一端排气方式布置,压缩机工作时工作介质沿双螺杆轴向被压缩而增压,双螺杆轴向是单向受力,轴支撑一端受压另一端受拉,其结构布置与设计遵循机械设计的一般方法,其结构尺寸与使用寿命等技术特征同样遵循动力机械的一般规律.介绍一种全新的双吸平衡式双螺杆压缩机的工作原理和结构特点.通过受力分析可知:该双吸平衡式双螺杆压缩机轴向受力平衡,核心部件受力状况得到改善,结构尺寸减小,工作噪声降低,达到节约原材料、降低制造成本、提高使用寿命、增加无故障运行时间的目的.
Prediction Based Energy Balancing Forwarding in Cellular Networks
Directory of Open Access Journals (Sweden)
Yang Jian-Jun
2017-01-01
Full Text Available In the recent cellular network technologies, relay stations extend cell coverage and enhance signal strength for mobile users. However, busy traffic makes the relay stations in hot area run out of energy quickly. Energy is a very important factor in the forwarding of cellular network since mobile users(cell phones in hot cells often suffer from low throughput due to energy lack problems. In many situations, the energy lack problems take place because the energy loading is not balanced. In this paper, we present a prediction based forwarding algorithm to let a mobile node dynamically select the next relay station with highest potential energy capacity to resume communication. Key to this strategy is that a relay station only maintains three past status, and then it is able to predict the potential energy capacity. Then, the node selects the next hop with potential maximal energy. Moreover, a location based algorithm is developed to let the mobile node figure out the target region in order to avoid flooding. Simulations demonstrate that our approach significantly increase the aggregate throughput and decrease the delay in cellular network environment.
Inducer Hydrodynamic Load Measurement Devices
Skelley, Stephen E.; Zoladz, Thomas F.
2002-01-01
Marshall Space Flight Center (MSFC) has demonstrated two measurement devices for sensing and resolving the hydrodynamic loads on fluid machinery. The first - a derivative of the six component wind tunnel balance - senses the forces and moments on the rotating device through a weakened shaft section instrumented with a series of strain gauges. This "rotating balance" was designed to directly measure the steady and unsteady hydrodynamic loads on an inducer, thereby defining both the amplitude and frequency content associated with operating in various cavitation modes. The second device - a high frequency response pressure transducer surface mounted on a rotating component - was merely an extension of existing technology for application in water. MSFC has recently completed experimental evaluations of both the rotating balance and surface-mount transducers in a water test loop. The measurement bandwidth of the rotating balance was severely limited by the relative flexibility of the device itself, resulting in an unexpectedly low structural bending mode and invalidating the higher frequency response data. Despite these limitations, measurements confirmed that the integrated loads on the four-bladed inducer respond to both cavitation intensity and cavitation phenomena. Likewise, the surface-mount pressure transducers were subjected to a range of temperatures and flow conditions in a non-rotating environment to record bias shifts and transfer functions between the transducers and a reference device. The pressure transducer static performance was within manufacturer's specifications and dynamic response accurately followed that of the reference.
Gamp, Alexander
2013-01-01
We begin by giving a description of the radio-frequency generator-cavity-beam coupled system in terms of basic quantities. Taking beam loading and cavity detuning into account, expressions for the cavity impedance as seen by the generator and as seen by the beam are derived. Subsequently methods of beam-loading compensation by cavity detuning, radio-frequency feedback and feedforward are described. Examples of digital radio-frequency phase and amplitude control for the special case of superconducting cavities are also given. Finally, a dedicated phase loop for damping synchrotron oscillations is discussed.
International Nuclear Information System (INIS)
Gamp, Alexander
2013-01-01
We begin by giving a description of the radio-frequency generator-cavity-beam coupled system in terms of basic quantities. Taking beam loading and cavity detuning into account, expressions for the cavity impedance as seen by the generator and as seen by the beam are derived. Subsequently methods of beam-loading compensation by cavity detuning, radio-frequency feedback and feedforward are described. Examples of digital radio-frequency phase and amplitude control for the special case of superconducting cavities are also given. Finally, a dedicated phase loop for damping synchrotron oscillations is discussed. (author)
Weight/balance portable test equipment
International Nuclear Information System (INIS)
Whitlock, R.W.
1994-01-01
This document shows the general layout, and gives a part description for the weight/balance test equipment. This equipment will aid in the regulation of the leachate loading of tanker trucks. The report contains four drawings with part specifications. The leachate originates from lined trenches
Fluid-structure-coupling algorithm
International Nuclear Information System (INIS)
McMaster, W.H.; Gong, E.Y.; Landram, C.S.; Quinones, D.F.
1980-01-01
A fluid-structure-interaction algorithm has been developed and incorporated into the two dimensional code PELE-IC. This code combines an Eulerian incompressible fluid algorithm with a Lagrangian finite element shell algorithm and incorporates the treatment of complex free surfaces. The fluid structure, and coupling algorithms have been verified by the calculation of solved problems from the literature and from air and steam blowdown experiments. The code has been used to calculate loads and structural response from air blowdown and the oscillatory condensation of steam bubbles in water suppression pools typical of boiling water reactors. The techniques developed here have been extended to three dimensions and implemented in the computer code PELE-3D
Loading relativistic Maxwell distributions in particle simulations
International Nuclear Information System (INIS)
Zenitani, Seiji
2015-01-01
Numerical algorithms to load relativistic Maxwell distributions in particle-in-cell (PIC) and Monte-Carlo simulations are presented. For stationary relativistic Maxwellian, the inverse transform method and the Sobol algorithm are reviewed. To boost particles to obtain relativistic shifted-Maxwellian, two rejection methods are proposed in a physically transparent manner. Their acceptance efficiencies are ≈50% for generic cases and 100% for symmetric distributions. They can be combined with arbitrary base algorithms
Loading relativistic Maxwell distributions in particle simulations
Energy Technology Data Exchange (ETDEWEB)
Zenitani, Seiji, E-mail: seiji.zenitani@nao.ac.jp [National Astronomical Observatory of Japan, 2-21-1 Osawa, Mitaka, Tokyo 181-8588 (Japan)
2015-04-15
Numerical algorithms to load relativistic Maxwell distributions in particle-in-cell (PIC) and Monte-Carlo simulations are presented. For stationary relativistic Maxwellian, the inverse transform method and the Sobol algorithm are reviewed. To boost particles to obtain relativistic shifted-Maxwellian, two rejection methods are proposed in a physically transparent manner. Their acceptance efficiencies are ≈50% for generic cases and 100% for symmetric distributions. They can be combined with arbitrary base algorithms.
DEFF Research Database (Denmark)
Markham, Annette
This paper takes an actor network theory approach to explore some of the ways that algorithms co-construct identity and relational meaning in contemporary use of social media. Based on intensive interviews with participants as well as activity logging and data tracking, the author presents a richly...... layered set of accounts to help build our understanding of how individuals relate to their devices, search systems, and social network sites. This work extends critical analyses of the power of algorithms in implicating the social self by offering narrative accounts from multiple perspectives. It also...... contributes an innovative method for blending actor network theory with symbolic interaction to grapple with the complexity of everyday sensemaking practices within networked global information flows....
A Hybrid Fuzzy Multi-hop Unequal Clustering Algorithm for Dense Wireless Sensor Networks
Directory of Open Access Journals (Sweden)
Shawkat K. Guirguis
2017-01-01
Full Text Available Clustering is carried out to explore and solve power dissipation problem in wireless sensor network (WSN. Hierarchical network architecture, based on clustering, can reduce energy consumption, balance traffic load, improve scalability, and prolong network lifetime. However, clustering faces two main challenges: hotspot problem and searching for effective techniques to perform clustering. This paper introduces a fuzzy unequal clustering technique for heterogeneous dense WSNs to determine both final cluster heads and their radii. Proposed fuzzy system blends three effective parameters together which are: the distance to the base station, the density of the cluster, and the deviation of the noders residual energy from the average network energy. Our objectives are achieving gain for network lifetime, energy distribution, and energy consumption. To evaluate the proposed algorithm, WSN clustering based routing algorithms are analyzed, simulated, and compared with obtained results. These protocols are LEACH, SEP, HEED, EEUC, and MOFCA.
The balanced academic curriculum problem revisited
DEFF Research Database (Denmark)
Chiarandini, Marco; Di Gaspero, Luca; Gualandi, Stefano
2012-01-01
The Balanced Academic Curriculum Problem (BACP) consists in assigning courses to teaching terms satisfying prerequisites and balancing the credit course load within each term. The BACP is part of the CSPLib with three benchmark instances, but its formulation is simpler than the problem solved...... in practice by universities. In this article, we introduce a generalized version of the problem that takes different curricula and professor preferences into account, and we provide a set of real-life problem instances arisen at University of Udine. Since the existing formulation based on a min-max objective...... function does not balance effectively the credit load for the new instances, we also propose alternative objective functions. Whereas all the CSPLib instances are efficiently solved with Integer Linear Programming (ILP) state-of-the-art solvers, our new set of real-life instances turns out to be much more...
Van den Ende, D.; Almeida, P.M.R.; Dingemans, T.J.; Van der Zwaag, S.
2007-01-01
The invention relates to a load sensor comprising a polymer matrix and a piezo-ceramic material such as PZT, em not bedded in the polymer matrix, which together form a compos not ite, wherein the polymer matrix is a liquid crystalline resin, and wherein the piezo-ceramic material is a PZT powder
Csernus, Marilyn
Carbohydrate loading is a frequently used technique to improve performance by altering an athlete's diet. The objective is to increase glycogen stored in muscles for use in prolonged strenuous exercise. For two to three days, the athlete consumes a diet that is low in carbohydrates and high in fat and protein while continuing to exercise and…
Energy Technology Data Exchange (ETDEWEB)
Makarov, Yuri V.; Huang, Zhenyu; Etingov, Pavel V.; Ma, Jian; Guttromson, Ross T.; Subbarao, Krishnappa; Chakrabarti, Bhujanga B.
2010-01-01
unique features make this work a significant step forward toward the objective of incorporating of wind, solar, load, and other uncertainties into power system operations. Currently, uncertainties associated with wind and load forecasts, as well as uncertainties associated with random generator outages and unexpected disconnection of supply lines, are not taken into account in power grid operation. Thus, operators have little means to weigh the likelihood and magnitude of upcoming events of power imbalance. In this project, funded by the U.S. Department of Energy (DOE), a framework has been developed for incorporating uncertainties associated with wind and load forecast errors, unpredicted ramps, and forced generation disconnections into the energy management system (EMS) as well as generation dispatch and commitment applications. A new approach to evaluate the uncertainty ranges for the required generation performance envelope including balancing capacity, ramping capability, and ramp duration has been proposed. The approach includes three stages: forecast and actual data acquisition, statistical analysis of retrospective information, and prediction of future grid balancing requirements for specified time horizons and confidence levels. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on a histogram analysis, incorporating all sources of uncertainties of both continuous (wind and load forecast errors) and discrete (forced generator outages and start-up failures) nature. A new method called the “flying brick” technique has been developed to evaluate the look-ahead required generation performance envelope for the worst case scenario within a user-specified confidence level. A self-validation algorithm has been developed to validate the accuracy of the confidence intervals.
Parallel-vector algorithms for particle simulations on shared-memory multiprocessors
International Nuclear Information System (INIS)
Nishiura, Daisuke; Sakaguchi, Hide
2011-01-01
Over the last few decades, the computational demands of massive particle-based simulations for both scientific and industrial purposes have been continuously increasing. Hence, considerable efforts are being made to develop parallel computing techniques on various platforms. In such simulations, particles freely move within a given space, and so on a distributed-memory system, load balancing, i.e., assigning an equal number of particles to each processor, is not guaranteed. However, shared-memory systems achieve better load balancing for particle models, but suffer from the intrinsic drawback of memory access competition, particularly during (1) paring of contact candidates from among neighboring particles and (2) force summation for each particle. Here, novel algorithms are proposed to overcome these two problems. For the first problem, the key is a pre-conditioning process during which particle labels are sorted by a cell label in the domain to which the particles belong. Then, a list of contact candidates is constructed by pairing the sorted particle labels. For the latter problem, a table comprising the list indexes of the contact candidate pairs is created and used to sum the contact forces acting on each particle for all contacts according to Newton's third law. With just these methods, memory access competition is avoided without additional redundant procedures. The parallel efficiency and compatibility of these two algorithms were evaluated in discrete element method (DEM) simulations on four types of shared-memory parallel computers: a multicore multiprocessor computer, scalar supercomputer, vector supercomputer, and graphics processing unit. The computational efficiency of a DEM code was found to be drastically improved with our algorithms on all but the scalar supercomputer. Thus, the developed parallel algorithms are useful on shared-memory parallel computers with sufficient memory bandwidth.
An adaptive clustering algorithm for image matching based on corner feature
Wang, Zhe; Dong, Min; Mu, Xiaomin; Wang, Song
2018-04-01
The traditional image matching algorithm always can not balance the real-time and accuracy better, to solve the problem, an adaptive clustering algorithm for image matching based on corner feature is proposed in this paper. The method is based on the similarity of the matching pairs of vector pairs, and the adaptive clustering is performed on the matching point pairs. Harris corner detection is carried out first, the feature points of the reference image and the perceived image are extracted, and the feature points of the two images are first matched by Normalized Cross Correlation (NCC) function. Then, using the improved algorithm proposed in this paper, the matching results are clustered to reduce the ineffective operation and improve the matching speed and robustness. Finally, the Random Sample Consensus (RANSAC) algorithm is used to match the matching points after clustering. The experimental results show that the proposed algorithm can effectively eliminate the most wrong matching points while the correct matching points are retained, and improve the accuracy of RANSAC matching, reduce the computation load of whole matching process at the same time.
Energy Technology Data Exchange (ETDEWEB)
Lober, R.R.; Tautges, T.J.; Vaughan, C.T.
1997-03-01
Paving is an automated mesh generation algorithm which produces all-quadrilateral elements. It can additionally generate these elements in varying sizes such that the resulting mesh adapts to a function distribution, such as an error function. While powerful, conventional paving is a very serial algorithm in its operation. Parallel paving is the extension of serial paving into parallel environments to perform the same meshing functions as conventional paving only on distributed, discretized models. This extension allows large, adaptive, parallel finite element simulations to take advantage of paving`s meshing capabilities for h-remap remeshing. A significantly modified version of the CUBIT mesh generation code has been developed to host the parallel paving algorithm and demonstrate its capabilities on both two dimensional and three dimensional surface geometries and compare the resulting parallel produced meshes to conventionally paved meshes for mesh quality and algorithm performance. Sandia`s {open_quotes}tiling{close_quotes} dynamic load balancing code has also been extended to work with the paving algorithm to retain parallel efficiency as subdomains undergo iterative mesh refinement.
A multi-pattern hash-binary hybrid algorithm for URL matching in the HTTP protocol.
Directory of Open Access Journals (Sweden)
Ping Zeng
Full Text Available In this paper, based on our previous multi-pattern uniform resource locator (URL binary-matching algorithm called HEM, we propose an improved multi-pattern matching algorithm called MH that is based on hash tables and binary tables. The MH algorithm can be applied to the fields of network security, data analysis, load balancing, cloud robotic communications, and so on-all of which require string matching from a fixed starting position. Our approach effectively solves the performance problems of the classical multi-pattern matching algorithms. This paper explores ways to improve string matching performance under the HTTP protocol by using a hash method combined with a binary method that transforms the symbol-space matching problem into a digital-space numerical-size comparison and hashing problem. The MH approach has a fast matching speed, requires little memory, performs better than both the classical algorithms and HEM for matching fields in an HTTP stream, and it has great promise for use in real-world applications.
Robertazzi, Thomas G.; Skiena, Steven; Wang, Kai
2017-08-08
Provided are an apparatus and method for load-balancing of a three-phase electric power distribution system having a multi-phase feeder, including obtaining topology information of the feeder identifying supply points for customer loads and feeder sections between the supply points, obtaining customer information that includes peak customer load at each of the points between each of the feeder sections, performing a phase balancing analysis, and recommending phase assignment at the customer load supply points.
Hysteresis Control for Shunt Active Power Filter under Unbalanced Three-Phase Load Conditions
Directory of Open Access Journals (Sweden)
Z. Chelli
2015-01-01
Full Text Available This paper focuses on a four-wire shunt active power filter (APF control scheme proposed to improve the performance of the APF. This filter is used to compensate harmonic distortion in three-phase four-wire systems. Several harmonic suppression techniques have been widely proposed and applied to minimize harmonic effects. The proposed control scheme can compensate harmonics and reactive power of the nonlinear loads simultaneously. This approach is compared to the conventional shunt APF reference compensation strategy. The developed algorithm is validated by simulation tests using MATLAB Simulink. The obtained results have demonstrated the effectiveness of the proposed scheme and confirmed the theoretical developments for balanced and unbalanced nonlinear loads.