Stackelberg Network Pricing Games
Briest, Patrick; Krysta, Piotr
2008-01-01
We study a multi-player one-round game termed Stackelberg Network Pricing Game, in which a leader can set prices for a subset of $m$ priceable edges in a graph. The other edges have a fixed cost. Based on the leader's decision one or more followers optimize a polynomial-time solvable combinatorial minimization problem and choose a minimum cost solution satisfying their requirements based on the fixed costs and the leader's prices. The leader receives as revenue the total amount of prices paid by the followers for priceable edges in their solutions, and the problem is to find revenue maximizing prices. Our model extends several known pricing problems, including single-minded and unit-demand pricing, as well as Stackelberg pricing for certain follower problems like shortest path or minimum spanning tree. Our first main result is a tight analysis of a single-price algorithm for the single follower game, which provides a $(1+\\epsilon) \\log m$-approximation for any $\\epsilon >0$. This can be extended to provide a ...
Huang, Jianwei
2013-01-01
Today's wireless communications and networking practices are tightly coupled with economic considerations, to the extent that it is almost impossible to make a sound technology choice without understanding the corresponding economic implications. This book aims at providing a foundational introduction on how microeconomics, and pricing theory in particular, can help us to understand and build better wireless networks. The book can be used as lecture notes for a course in the field of network economics, or a reference book for wireless engineers and applied economists to understand how pricing
Future aircraft networks and schedules
Shu, Yan
2011-07-01
Because of the importance of air transportation scheduling, the emergence of small aircraft and the vision of future fuel-efficient aircraft, this thesis has focused on the study of aircraft scheduling and network design involving multiple types of aircraft and flight services. It develops models and solution algorithms for the schedule design problem and analyzes the computational results. First, based on the current development of small aircraft and on-demand flight services, this thesis expands a business model for integrating on-demand flight services with the traditional scheduled flight services. This thesis proposes a three-step approach to the design of aircraft schedules and networks from scratch under the model. In the first step, both a frequency assignment model for scheduled flights that incorporates a passenger path choice model and a frequency assignment model for on-demand flights that incorporates a passenger mode choice model are created. In the second step, a rough fleet assignment model that determines a set of flight legs, each of which is assigned an aircraft type and a rough departure time is constructed. In the third step, a timetable model that determines an exact departure time for each flight leg is developed. Based on the models proposed in the three steps, this thesis creates schedule design instances that involve almost all the major airports and markets in the United States. The instances of the frequency assignment model created in this thesis are large-scale non-convex mixed-integer programming problems, and this dissertation develops an overall network structure and proposes iterative algorithms for solving these instances. The instances of both the rough fleet assignment model and the timetable model created in this thesis are large-scale mixed-integer programming problems, and this dissertation develops subproblem schemes for solving these instances. Based on these solution algorithms, this dissertation also presents
Optimal scheduling using priced timed automata
Behrmann, Gerd; Larsen, Kim Guldstrand; Rasmussen, Jacob Illum
2005-01-01
This contribution reports on the considerable effort made recently towards extending and applying well-established timed automata technology to optimal scheduling and planning problems. The effort of the authors in this direction has to a large extent been carried out as part of the European...... projects VHS [20] and AMETIST [16] and are available in the recently released UPPAAL CORA [12], a variant of the real-time verification tool UPPAAL [18, 5] specialized for cost-optimal reachability for the extended model of so-called priced timed automata....
Optimal scheduling using priced timed automata
Behrmann, Gerd; Larsen, Kim Guldstrand; Rasmussen, Jacob Illum
2005-01-01
This contribution reports on the considerable effort made recently towards extending and applying well-established timed automata technology to optimal scheduling and planning problems. The effort of the authors in this direction has to a large extent been carried out as part of the European proj...... projects VHS [20] and AMETIST [16] and are available in the recently released UPPAAL CORA [12], a variant of the real-time verification tool UPPAAL [18, 5] specialized for cost-optimal reachability for the extended model of so-called priced timed automata....
Trading Network Predicts Stock Price
Sun, Xiao-Qian; Shen, Hua-Wei; Cheng, Xue-Qi
2014-01-01
Stock price prediction is an important and challenging problem for studying financial markets. Existing studies are mainly based on the time series of stock price or the operation performance of listed company. In this paper, we propose to predict stock price based on investors' trading behavior. For each stock, we characterize the daily trading relationship among its investors using a trading network. We then classify the nodes of trading network into three roles according to their connectivity pattern. Strong Granger causality is found between stock price and trading relationship indices, i.e., the fraction of trading relationship among nodes with different roles. We further predict stock price by incorporating these trading relationship indices into a neural network based on time series of stock price. Experimental results on 51 stocks in two Chinese Stock Exchanges demonstrate the accuracy of stock price prediction is significantly improved by the inclusion of trading relationship indices.
Trading network predicts stock price.
Sun, Xiao-Qian; Shen, Hua-Wei; Cheng, Xue-Qi
2014-01-16
Stock price prediction is an important and challenging problem for studying financial markets. Existing studies are mainly based on the time series of stock price or the operation performance of listed company. In this paper, we propose to predict stock price based on investors' trading behavior. For each stock, we characterize the daily trading relationship among its investors using a trading network. We then classify the nodes of trading network into three roles according to their connectivity pattern. Strong Granger causality is found between stock price and trading relationship indices, i.e., the fraction of trading relationship among nodes with different roles. We further predict stock price by incorporating these trading relationship indices into a neural network based on time series of stock price. Experimental results on 51 stocks in two Chinese Stock Exchanges demonstrate the accuracy of stock price prediction is significantly improved by the inclusion of trading relationship indices.
Optimal pricing of capacitated networks
Grigoriev, Alexander; Loon, van Joyce; Sitters, René; Uetz, Marc
2009-01-01
We address the algorithmic complexity of a profit maximization problem in capacitated, undirected networks. We are asked to price a set of $m$ capacitated network links to serve a set of $n$ potential customers. Each customer is interested in purchasing a network connection that is specified by a si
Resource-Optimal Scheduling Using Priced Timed Automata
Larsen, Kim Guldstrand; Rasmussen, Jacob Illum; Subramani, K.
2004-01-01
In this paper, we show how the simple structure of the linear programs encountered during symbolic minimum-cost reachability analysis of priced timed automata can be exploited in order to substantially improve the performance of the current algorithm. The idea is rooted in duality of linear progr......-80 percent performance gain. As a main application area, we show how to solve energy-optimal task graph scheduling problems using the framework of priced timed automata....
Cooperation in Networks and Scheduling
van Velzen, S.
2005-01-01
This thesis deals with various models of cooperation in networks and scheduling. The main focus is how the benefits of this cooperation should be divided among the participating individuals. A major part of this analysis is concerned with stability of the cooperation. In addition, allocation rules a
Spatial price dynamics: From complex network perspective
Li, Y. L.; Bi, J. T.; Sun, H. J.
2008-10-01
The spatial price problem means that if the supply price plus the transportation cost is less than the demand price, there exists a trade. Thus, after an amount of exchange, the demand price will decrease. This process is continuous until an equilibrium state is obtained. However, how the trade network structure affects this process has received little attention. In this paper, we give a evolving model to describe the levels of spatial price on different complex network structures. The simulation results show that the network with shorter path length is sensitive to the variation of prices.
Fair Scheduling in Networks Through Packet Election
Jagabathula, Srikanth
2008-01-01
We consider the problem of designing a fair scheduling algorithm for discrete-time constrained queuing networks. Each queue has dedicated exogenous packet arrivals. There are constraints on which queues can be served simultaneously. This model effectively describes important special instances like network switches, interference in wireless networks, bandwidth sharing for congestion control and traffic scheduling in road roundabouts. Fair scheduling is required because it provides isolation to different traffic flows; isolation makes the system more robust and enables providing quality of service. Existing work on fairness for constrained networks concentrates on flow based fairness. As a main result, we describe a notion of packet based fairness by establishing an analogy with the ranked election problem: packets are voters, schedules are candidates and each packet ranks the schedules based on its priorities. We then obtain a scheduling algorithm that achieves the described notion of fairness by drawing upon ...
Network-Aware HEFT Scheduling for Grid
Muhammad Murtaza Yousaf
2014-01-01
Full Text Available We present a network-aware HEFT. The original HEFT does not take care of parallel network flows while designing its schedule for a computational environment where computing nodes are physically at distant locations. In the proposed mechanism, such data transfers are stretched to their realistic completion time. A HEFT schedule with stretched data transfers exhibits the realistic makespan of the schedule. It is shown how misleading a schedule can be if the impact of parallel data transfers that share a bottleneck is ignored. A network-aware HEFT can be used to yield a benefit for Grid applications.
Scheduling Network Traffic for Grid Purposes
Gamst, Mette
This thesis concerns scheduling of network traffic in grid context. Grid computing consists of a number of geographically distributed computers, which work together for solving large problems. The computers are connected through a network. When scheduling job execution in grid computing, data...
Maritime wideband communication networks video transmission scheduling
Yang, Tingting
2014-01-01
This Springer Brief covers emerging maritime wideband communication networks and how they facilitate applications such as maritime distress, urgency, safety and general communications. It provides valuable insight on the data transmission scheduling and protocol design for the maritime wideband network. This brief begins with an introduction to maritime wideband communication networks including the architecture, framework, operations and a comprehensive survey on current developments. The second part of the brief presents the resource allocation and scheduling for video packet transmission wit
NASA Deep Space Network Operations Scheduling
Enari, D. M.
The functioning of the Deep Space Network Operations Scheduling, Jet Propulsion Laboratory, CA is reviewed. The primary objectives of the Operations Scheduling are: to schedule the worldwide global allocation of ground communications, tracking facilities, and equipment; and to provide deep space telecommunications for command, tracking, telemetry, and control in support of flight mission operations and tests. Elements of the earth set are Deep Space Stations (DSS) which provide the telecommunications link between the earth and spacecraft; NASA Communications Network; Network Data Processing Area; Network Operations Control Area which provides operational direction to the DSS; Mission Control and Computing systems; and Mission Support areas which provide flight control of the spacecraft. Elements of the space set include mission priorities and requirements which determine the spacecraft queue for allocating network resources. Scheduling is discussed in terms of long-range (3 years), mid-range (8 weeks), and short-range (2 weeks).
Dynamic pricing by hopfield neural network
Lusajo M Minga; FENG Yu-qiang(冯玉强); LI Yi-jun(李一军); LU Yang(路杨); Kimutai Kimeli
2004-01-01
The increase in the number of shopbots users in e-commerce has triggered flexibility of sellers in their pricing strategies. Sellers see the importance of automated price setting which provides efficient services to a large number of buyers who are using shopbots. This paper studies the characteristic of decreasing energy with time in a continuous model of a Hopfield neural network that is the decreasing of errors in the network with respect to time. The characteristic shows that it is possible to use Hopfield neural network to get the main factor of dynamic pricing; the least variable cost, from production function principles. The least variable cost is obtained by reducing or increasing the input combination factors, and then making the comparison of the network output with the desired output, where the difference between the network output and desired output will be decreasing in the same manner as in the Hopfield neural network energy. Hopfield neural network will simplify the rapid change of prices in e-commerce during transaction that depends on the demand quantity for demand sensitive model of pricing.
Simplified Scheduling for Underwater Acoustic Networks
Wouter van Kleunen
2013-01-01
Full Text Available The acoustic propagation speed under water poses significant challenges to the design of underwater sensor networks and their medium access control protocols. Similar to the air, scheduling transmissions under water has significant impact on throughput, energy consumption, and reliability. In this paper we present an extended set of simplified scheduling constraints which allows easy scheduling of underwater acoustic communication. We also present two algorithms for scheduling communications, i.e. a centralized scheduling approach and a distributed scheduling approach. The centralized approach achieves the highest throughput while the distributed approach aims to minimize the computation and communication overhead. We further show how the centralized scheduling approach can be extended with transmission dependencies to reduce the end-to-end delay of packets. We evaluate the performance of the centralized and distributed scheduling approaches using simulation. The centralized approach outperforms the distributed approach in terms of throughput, however we also show the distributed approach has significant benefits in terms of communication and computational overhead required to setup the schedule. We propose a novel way of estimating the performance of scheduling approaches using the ratio of modulation time and propagation delay. We show the performance is largely dictated by this ratio, although the number of links to be scheduled also has a minor impact on the performance.
Greedy Maximal Scheduling in Wireless Networks
Li, Qiao
2010-01-01
In this paper we consider greedy scheduling algorithms in wireless networks, i.e., the schedules are computed by adding links greedily based on some priority vector. Two special cases are considered: 1) Longest Queue First (LQF) scheduling, where the priorities are computed using queue lengths, and 2) Static Priority (SP) scheduling, where the priorities are pre-assigned. We first propose a closed-form lower bound stability region for LQF scheduling, and discuss the tightness result in some scenarios. We then propose an lower bound stability region for SP scheduling with multiple priority vectors, as well as a heuristic priority assignment algorithm, which is related to the well-known Expectation-Maximization (EM) algorithm. The performance gain of the proposed heuristic algorithm is finally confirmed by simulations.
Integrated network design and scheduling problems :
Nurre, Sarah G.; Carlson, Jeffrey J.
2014-01-01
We consider the class of integrated network design and scheduling problems. These problems focus on selecting and scheduling operations that will change the characteristics of a network, while being speci cally concerned with the performance of the network over time. Motivating applications of INDS problems include infrastructure restoration after extreme events and building humanitarian distribution supply chains. While similar models have been proposed, no one has performed an extensive review of INDS problems from their complexity, network and scheduling characteristics, information, and solution methods. We examine INDS problems under a parallel identical machine scheduling environment where the performance of the network is evaluated by solving classic network optimization problems. We classify that all considered INDS problems as NP-Hard and propose a novel heuristic dispatching rule algorithm that selects and schedules sets of arcs based on their interactions in the network. We present computational analysis based on realistic data sets representing the infrastructures of coastal New Hanover County, North Carolina, lower Manhattan, New York, and a realistic arti cial community CLARC County. These tests demonstrate the importance of a dispatching rule to arrive at near-optimal solutions during real-time decision making activities. We extend INDS problems to incorporate release dates which represent the earliest an operation can be performed and exible release dates through the introduction of specialized machine(s) that can perform work to move the release date earlier in time. An online optimization setting is explored where the release date of a component is not known.
Integrated Job Scheduling and Network Routing
Gamst, Mette; Pisinger, David
2013-01-01
We consider an integrated job scheduling and network routing problem which appears in Grid Computing and production planning. The problem is to schedule a number of jobs at a finite set of machines, such that the overall profit of the executed jobs is maximized. Each job demands a number...... of resources which must be sent to the executing machine through a network with limited capacity. A job cannot start before all of its resources have arrived at the machine. The scheduling problem is formulated as a Mixed Integer Program (MIP) and proved to be NP-hard. An exact solution approach using Dantzig...... instances with 1,000 jobs and 1,000 machines covering 24 hours of scheduling activity on a Grid network. The algorithm is also compared to simulations of a real-life Grid, and results show that the solution quality significantly increases when solving the problem to optimality. The promising results...
Schedule Selection by Agents: from Price Plans to Tax Tables
Luttmer, Erzo F.P.; Zeckhauser, Richard J.
2008-01-01
Requiring agents with private information to select from a menu of incentive schedules can yield efficiency gains. It will do so if, and only if, agents will receive further private information after selecting the incentive schedule but before taking the action that determines where on the incentive schedule they end up. We argue that this information structure is relevant in many applications. We develop the theory underlying optimal menus of non-linear schedules and prove that there exists ...
Smart self-scheduling of Gencos with thermal and energy storage units under price uncertainty
Soroudi, Alireza
2013-01-01
This paper provides a self-scheduling tool for price taker Gencos. This methodology is based on Robust Optimization (RO) to deal with the uncertainties of market price values in the day-ahead electricity pool market. The Genco is assumed to be the entity who decides about the operating schedules of its thermal units and Compressed Air Energy Storage units. The benefits of Genco brought by smart grid technology and energy storage systems are investigated in this work. The applicability of the ...
2016-11-15
This major final rule addresses changes to the physician fee schedule and other Medicare Part B payment policies, such as changes to the Value Modifier, to ensure that our payment systems are updated to reflect changes in medical practice and the relative value of services, as well as changes in the statute. This final rule also includes changes related to the Medicare Shared Savings Program, requirements for Medicare Advantage Provider Networks, and provides for the release of certain pricing data from Medicare Advantage bids and of data from medical loss ratio reports submitted by Medicare health and drug plans. In addition, this final rule expands the Medicare Diabetes Prevention Program model.
Planning and Scheduling for Environmental Sensor Networks
Frank, J. D.
2005-12-01
Environmental Sensor Networks are a new way of monitoring the environment. They comprise autonomous sensor nodes in the environment that record real-time data, which is retrieved, analyzed, integrated with other data sets (e.g. satellite images, GIS, process models) and ultimately lead to scientific discoveries. Sensor networks must operate within time and resource constraints. Sensors have limited onboard memory, energy, computational power, communications windows and communications bandwidth. The value of data will depend on when, where and how it was collected, how detailed the data is, how long it takes to integrate the data, and how important the data was to the original scientific question. Planning and scheduling of sensor networks is necessary for effective, safe operations in the face of these constraints. For example, power bus limitations may preclude sensors from simultaneously collecting data and communicating without damaging the sensor; planners and schedulers can ensure these operations are ordered so that they do not happen simultaneously. Planning and scheduling can also ensure best use of the sensor network to maximize the value of collected science data. For example, if data is best recorded using a particular camera angle but it is costly in time and energy to achieve this, planners and schedulers can search for times when time and energy are available to achieve the optimal camera angle. Planning and scheduling can handle uncertainty in the problem specification; planners can be re-run when new information is made available, or can generate plans that include contingencies. For example, if bad weather may prevent the collection of data, a contingent plan can check lighting conditions and turn off data collection to save resources if lighting is not ideal. Both mobile and immobile sensors can benefit from planning and scheduling. For example, data collection on otherwise passive sensors can be halted to preserve limited power and memory
Packet scheduling for OFDMA based relay networks
无
2008-01-01
The combination of relay networks with orthogonal frequency division multiple access (OFDMA) has been proposed as a promising solution for the next generation wireless system. Considering different traffic classes and user quality of service (QoS), three efficient scheduling algorithms are introduced in such networks. The round-robin (RR) algorithm in relay networks serves as a performance benchmark. Numerical results show that the proposed algorithms achieve significant improvement on system throughput and decrease system packet loss rate, compared with the RR and absence of relaying system (traditional network). Furthermore, comparisons have been carried out among the three proposed algorithms.
Simplified scheduling for underwater acoustic networks
Kleunen, van Wouter; Meratnia, Nirvana; Havinga, Paul J.M.
2013-01-01
The acoustic propagation speed under water poses significant challenges to the design of underwater sensor networks and their medium access control protocols. Similar to the air, scheduling transmissions under water has significant impact on throughput, energy consumption, and reliability. In this p
Simplified scheduling for underwater acoustic networks
van Kleunen, W.A.P.; Meratnia, Nirvana; Havinga, Paul J.M.
The acoustic propagation speed under water poses significant challenges to the design of underwater sensor networks and their medium access control protocols. Similar to the air, scheduling transmissions under water has significant impact on throughput, energy consumption, and reliability. In this
Overcoming barriers to scheduling embedded generation to support distribution networks
Wright, A.J.; Formby, J.R.
2000-07-01
Current scheduling of embedded generation for distribution in the UK is limited and patchy. Some DNOs actively schedule while others do none. The literature on the subject is mainly about accommodating volatile wind output, and optimising island systems, for both cost of supply and network stability. The forthcoming NETA will lower prices, expose unpredictable generation to imbalance markets and could introduce punitive constraint payments on DNOs, but at the same time create a dynamic market for both power and ancillary services from embedded generators. Most renewable generators either run as base load (e.g. waste ) or according to the vagaries of the weather (e.g. wind, hydro), so offer little scope for scheduling other than 'off'. CHP plant is normally heat- led for industrial processes or building needs, but supplementary firing or thermal storage often allow considerable scope for scheduling. Micro-CHP with thermal storage could provide short-term scheduling, but tends to be running anyway during the evening peak. Standby generation appears to be ideal for scheduling, but in practice operators may be unwilling to run parallel with the network, and noise and pollution problems may preclude frequent operation. Statistical analysis can be applied to calculate the reliability of several generators compared to one; with a large number of generators such as micro-CHP reliability of a proportion of load is close to unity. The type of communication for generation used will depend on requirements for bandwidth, cost, reliability and whether it is bundled with other services. With high levels of deeply embedded, small-scale generation using induction machines, voltage control and black start capability will become important concerns on 11 kV and LV networks. This will require increased generation monitoring and remote control of switchgear. Examples of cost benefits from scheduling are given, including deferred reinforcement, increased exports on non
Dynamic Packet Scheduling in Wireless Networks
Kesselheim, Thomas
2012-01-01
We consider protocols that serve communication requests arising over time in a wireless network that is subject to interference. Unlike previous approaches, we take the geometry of the network and power control into account, both allowing to increase the network's performance significantly. We introduce a stochastic and an adversarial model to bound the packet injection. Although taken as the primary motivation, this approach is not only suitable for models based on the signal-to-interference-plus-noise ratio (SINR). It also covers virtually all other common interference models, for example the multiple-access channel, the radio-network model, the protocol model, and distance-2 matching. Packet-routing networks allowing each edge or each node to transmit or receive one packet at a time can be modeled as well. Starting from algorithms for the respective scheduling problem with static transmission requests, we build distributed stable protocols. This is more involved than in previous, similar approaches because...
Utility Optimal Scheduling in Processing Networks
Huang, Longbo
2010-01-01
We consider the problem of utility optimal scheduling in general \\emph{processing networks} with random arrivals and network conditions. These are generalizations of traditional data networks where commodities in one or more queues can be combined to produce new commodities that are delivered to other parts of the network. This can be used to model problems such as in-network data fusion, stream processing, and grid computing. Scheduling actions are complicated by the \\emph{underflow problem} that arises when some queues with required components go empty. In this paper, we develop the Perturbed Max-Weight algorithm (PMW) to achieve optimal utility. The idea of PMW is to perturb the weights used by the usual Max-Weight algorithm to ``push'' queue levels towards non-zero values (avoiding underflows). We show that when the perturbations are carefully chosen, PMW is able to achieve a utility that is within $O(1/V)$ of the optimal value for any $V\\geq1$, while ensuring an average network backlog of $O(V)$.
Economic impact of price forecasting inaccuracies on self-scheduling of generation companies
Mohammadi-Ivatloo, B.; Ehsan, M. [Center of Excellence in Power System Management and Control, Department of Electrical Engineering, Sharif University of Technology, Tehran (Iran, Islamic Republic of); Zareipour, H. [Power and Energy Systems Group, Department of Electrical and Computer Engineering, University of Calgary, Alberta (Canada); Amjady, N. [Department of Electrical Engineering, University of Semnan, Semnan (Iran, Islamic Republic of)
2011-02-15
This paper studies the economic impact of using inaccurate price forecasts on self-scheduling of generation companies (GenCos) in a competitive electricity market. Four alternative sets of price forecasts are used in this study which have different levels of accuracy. The economic impact of price forecast inaccuracies is calculated by comparing the economic benefits of the GenCos in two self-scheduling scenarios. In the first scenario, electricity market price forecasts are used to optimally schedule the GenCos' next day operation. In the second scenario, perfect price forecasts, i.e., actual market prices, are used for self-scheduling of the GenCos. Two indices are utilized to quantify the differences in the economic benefits of the GenCos under the two scenarios. Simulation results are provided and discussed for two typical and inherently different GenCos, i.e., a hydro-based producer and a thermal-based producer. (author)
Integrating job scheduling and constrained network routing
Gamst, Mette
2010-01-01
This paper examines the NP-hard problem of scheduling jobs on resources such that the overall profit of executed jobs is maximized. Job demand must be sent through a constrained network to the resource before execution can begin. The problem has application in grid computing, where a number...... of geographically distributed resources connected through an optical network work together for solving large problems. A number of heuristics are proposed along with an exact solution approach based on Dantzig-Wolfe decomposition. The latter has some performance difficulties while the heuristics solve all instances...
Scheduling Broadcasts in a Network of Timelines
Manzoor, Emaad A.
2015-05-12
Broadcasts and timelines are the primary mechanism of information exchange in online social platforms today. Services like Facebook, Twitter and Instagram have enabled ordinary people to reach large audiences spanning cultures and countries, while their massive popularity has created increasingly competitive marketplaces of attention. Timing broadcasts to capture the attention of such geographically diverse audiences has sparked interest from many startups and social marketing gurus. However, formal study is lacking on both the timing and frequency problems. In this thesis, we introduce, motivate and solve the broadcast scheduling problem of specifying the timing and frequency of publishing content to maximise the attention received. We validate and quantify three interacting behavioural phenomena to parametrise social platform users: information overload, bursty circadian rhythms and monotony aversion, which is defined here for the first time. Our analysis of the influence of monotony refutes the common assumption that posts on social network timelines are consumed piecemeal independently. Instead, we reveal that posts are consumed in chunks, which has important consequences for any future work considering human behaviour over social network timelines. Our quantification of monotony aversion is also novel, and has applications to problems in various domains such as recommender list diversification, user satiation and variety-seeking consumer behaviour. Having studied the underlying behavioural phenomena, we link schedules, timelines, attention and behaviour by formalising a timeline information exchange process. Our formulation gives rise to a natural objective function that quantifies the expected collective attention an arrangement of posts on a timeline will receive. We apply this formulation as a case-study on real-data from Twitter, where we estimate behavioural parameters, calculate the attention potential for different scheduling strategies and, using the
On using priced timed automata to achieve optimal scheduling
Rasmussen, Jacob Illum; Larsen, Kim Guldstrand; Subramani, K.
2006-01-01
This contribution reports on the considerable effort made recently towards extending and applying well-established timed automata technology to optimal scheduling and planning problems. The effort of the authors in this direction has to a large extent been carried out as part of the European proj...
A branch-and-price algorithm for the long-term home care scheduling problem
Gamst, Mette; Jensen, Thomas Sejr
2012-01-01
propose a branchand-price algorithm for the long-term home care scheduling problem. The pricing problem generates a one-day plan for an employee, and the master problem merges the plans with respect to regularity constraints. The method is capable of generating plans with up to 44 visits during one week.......In several countries, home care is provided for certain citizens living at home. The long-term home care scheduling problem is to generate work plans such that a high quality of service is maintained, the work hours of the employees are respected, and the overall cost is kept as low as possible. We...
Scheduling and Topology Design in Networks with Directional Antennas
2017-05-19
match the topology design and traffic patterns. Specifically, we find that commonly used, suboptimal schedules can lead to greatly reduced network...1/4 (b) Uniform schedule (i) 3/14 (ii) 3/14 (iii) 2/7 (iv) 2/7 (c) Optimal schedule for all-all unicast traffic Fig. 2: Example schedules for a line...same schedule is repeated through the duration of network use. Example schedules for a four-node network with a line topology are shown in Fig. 2. We
A Network Simulation Tool for Task Scheduling
Ondřej Votava
2012-01-01
Full Text Available Distributed computing may be looked at from many points of view. Task scheduling is the viewpoint, where a distributed application can be described as a Directed Acyclic Graph and every node of the graph is executed independently. There are, however, data dependencies and the nodes have to be executed in a specified order. Hence the parallelism of the execution is limited. The scheduling problem is difficult and therefore heuristics are used. However, many inaccuracies are caused by the model used for the system, in which the heuristics are being tested. In this paper we present a tool for simulating the execution of the distributed application on a “real” computer network, and try to tell how the executionis influenced compared to the model.
A subjective scheduler for subjective dedicated networks
Suherman; Fakhrizal, Said Reza; Al-Akaidi, Marwan
2017-09-01
Multiple access technique is one of important techniques within medium access layer in TCP/IP protocol stack. Each network technology implements the selected access method. Priority can be implemented in those methods to differentiate services. Some internet networks are dedicated for specific purpose. Education browsing or tutorial video accesses are preferred in a library hotspot, while entertainment and sport contents could be subjects of limitation. Current solution may use IP address filter or access list. This paper proposes subjective properties of users or applications are used for priority determination in multiple access techniques. The NS-2 simulator is employed to evaluate the method. A video surveillance network using WiMAX is chosen as the object. Subjective priority is implemented on WiMAX scheduler based on traffic properties. Three different traffic sources from monitoring video: palace, park, and market are evaluated. The proposed subjective scheduler prioritizes palace monitoring video that results better quality, xx dB than the later monitoring spots.
Wireless Network Coding with Local Network Views: Coded Layer Scheduling
Vahid, Alireza; Avestimehr, A Salman; Sabharwal, Ashutosh
2011-01-01
One of the fundamental challenges in the design of distributed wireless networks is the large dynamic range of network state. Since continuous tracking of global network state at all nodes is practically impossible, nodes can only acquire limited local views of the whole network to design their transmission strategies. In this paper, we study multi-layer wireless networks and assume that each node has only a limited knowledge, namely 1-local view, where each S-D pair has enough information to perform optimally when other pairs do not interfere, along with connectivity information for rest of the network. We investigate the information-theoretic limits of communication with such limited knowledge at the nodes. We develop a novel transmission strategy, namely Coded Layer Scheduling, that solely relies on 1-local view at the nodes and incorporates three different techniques: (1) per layer interference avoidance, (2) repetition coding to allow overhearing of the interference, and (3) network coding to allow inter...
Pricing and Referrals in Diffusion on Networks
Leduc, Matt V; Johari, Ramesh
2015-01-01
When a new product or technology is introduced, potential consumers can learn its quality by trying the product, at a risk, or by letting others try it and free-riding on the information that they generate. We propose a dynamic game to study the adoption of technologies of uncertain value, when agents are connected by a network and a monopolist seller chooses a policy to maximize profits. Consumers with low degree (few friends) have incentives to adopt early, while consumers with high degree have incentives to free ride. The seller can induce high degree consumers to adopt early by offering referral incentives - rewards to early adopters whose friends buy in the second period. Referral incentives thus lead to a `double-threshold strategy' by which low and high-degree agents adopt the product early while middle-degree agents wait. We show that referral incentives are optimal on certain networks while intertemporal price discrimination (i.e., a first-period price discount) is optimal on others.
Feedback Scheduling of Priority-Driven Control Networks
Xia, Feng; Tian, Yu-Chu
2008-01-01
With traditional open-loop scheduling of network resources, the quality-of-control (QoC) of networked control systems (NCSs) may degrade significantly in the presence of limited bandwidth and variable workload. The goal of this work is to maximize the overall QoC of NCSs through dynamically allocating available network bandwidth. Based on codesign of control and scheduling, an integrated feedback scheduler is developed to enable flexible QoC management in dynamic environments. It encompasses a cascaded feedback scheduling module for sampling period adjustment and a direct feedback scheduling module for priority modification. The inherent characteristics of priority-driven control networks make it feasible to implement the proposed feedback scheduler in real-world systems. Extensive simulations show that the proposed approach leads to significant QoC improvement over the traditional open-loop scheduling scheme under both underloaded and overloaded network conditions.
Utility Optimal Scheduling in Energy Harvesting Networks
Huang, Longbo
2010-01-01
In this paper, we show how to achieve close-to-optimal utility performance in energy harvesting networks with only finite capacity energy storage devices. In these networks, nodes are capable of harvesting energy from the environment. The amount of energy that can be harvested is time varying and evolves according to some probability law. We develop an \\emph{online} algorithm, called the Energy-limited Scheduling Algorithm (ESA), which jointly manages the energy and makes power allocation decisions for packet transmissions. ESA only has to keep track of the amount of energy left at the network nodes and \\emph{does not require any knowledge} of the harvestable energy process. We show that ESA achieves a utility that is within $O(\\epsilon)$ of the optimal, for any $\\epsilon>0$, while ensuring that the network congestion and the required capacity of the energy storage devices are \\emph{deterministically} upper bounded by bounds of size $O(1/\\epsilon)$. We then also develop the Modified-ESA algorithm (MESA) to ac...
Price of Fairness on Networked Auctions
Mariusz Kaleta
2014-01-01
as follows: no agent can be treated worse than any other in similar circumstances. Ensuring the fairness conditions makes only part of the social welfare available in the auction to be distributed on pure market rules. The rest of welfare must be distributed without market rules and constitutes the so-called price of fairness. We prove that there exists the minimum of price of fairness and that it is achieved when uniform unconstrained market price is used as the base price. The price of fairness takes into account costs of forced offers and compensations for lost profits. The final payments can be different than locational marginal pricing. That means that the widely applied locational marginal pricing mechanism does not in general minimize the price of fairness.
Grid Computing based on Game Optimization Theory for Networks Scheduling
Peng-fei Zhang
2014-05-01
Full Text Available The resource sharing mechanism is introduced into grid computing algorithm so as to solve complex computational tasks in heterogeneous network-computing problem. However, in the Grid environment, it is required for the available resource from network to reasonably schedule and coordinate, which can get a good workflow and an appropriate network performance and network response time. In order to improve the performance of resource allocation and task scheduling in grid computing method, a game model based on non-cooperation game is proposed. Setting the time and cost of user’s resource allocation can increase the performance of networks, and incentive resource of networks uses an optimization scheduling algorithm, which minimizes the time and cost of resource scheduling. Simulation experiment results show the feasibility and suitability of model. In addition, we can see from the experiment result that model-based genetic algorithm is the best resource scheduling algorithm
Real-Time Pricing-Based Scheduling Strategy in Smart Grids: A Hierarchical Game Approach
Jie Yang
2014-01-01
Full Text Available This paper proposes a scheduling strategy based on real-time pricing in smart grids. A hierarchical game is employed to analyze the decision-making process of generators and consumers. We prove the existence and uniqueness of Nash equilibrium and utilize a backward induction method to obtain the generation and consumption strategies. Then, we propose two dynamic algorithms for the generators and consumers to search for the equilibrium in a distributed fashion. Simulation results demonstrate that the proposed scheduling strategy can match supply with demand and shift load away from peak time.
Collaborative Scheduling between OSPPs and Gasholders in Steel Mill under Time-of-Use Power Price
Juxian Hao
2017-08-01
Full Text Available Byproduct gases generated during steel production process are the main fuels for on-site power plants (OSPPs in steel enterprises. Recently, with the implementation of time-of-use (TOU power price in China, increasing attention has been paid to the collaborative scheduling between OSPPs and gasholders. However, the load shifting potential of OSPPs has seldom been discussed in previous studies. In this paper, a mixed integer linear programming (MILP-based scheduling model is built to evaluate the load shifting potential and the corresponding economic benefits. A case study is conducted on two steel enterprises with different configurations of OSPPs, and the optimal operation strategy is also discussed.
Dynamic Pricing in Electronic Commerce Using Neural Network
Ghose, Tapu Kumar; Tran, Thomas T.
In this paper, we propose an approach where feed-forward neural network is used for dynamically calculating a competitive price of a product in order to maximize sellers’ revenue. In the approach we considered that along with product price other attributes such as product quality, delivery time, after sales service and seller’s reputation contribute in consumers purchase decision. We showed that once the sellers, by using their limited prior knowledge, set an initial price of a product our model adjusts the price automatically with the help of neural network so that sellers’ revenue is maximized.
Fair packet scheduling in Wireless Mesh Networks
Nawab, Faisal
2014-02-01
In this paper we study the interactions of TCP and IEEE 802.11 MAC in Wireless Mesh Networks (WMNs). We use a Markov chain to capture the behavior of TCP sessions, particularly the impact on network throughput due to the effect of queue utilization and packet relaying. A closed form solution is derived to numerically determine the throughput. Based on the developed model, we propose a distributed MAC protocol called Timestamp-ordered MAC (TMAC), aiming to alleviate the unfairness problem in WMNs. TMAC extends CSMA/CA by scheduling data packets based on their age. Prior to transmitting a data packet, a transmitter broadcasts a request control message appended with a timestamp to a selected list of neighbors. It can proceed with the transmission only if it receives a sufficient number of grant control messages from these neighbors. A grant message indicates that the associated data packet has the lowest timestamp of all the packets pending transmission at the local transmit queue. We demonstrate that a loose ordering of timestamps among neighboring nodes is sufficient for enforcing local fairness, subsequently leading to flow rate fairness in a multi-hop WMN. We show that TMAC can be implemented using the control frames in IEEE 802.11, and thus can be easily integrated in existing 802.11-based WMNs. Our simulation results show that TMAC achieves excellent resource allocation fairness while maintaining over 90% of maximum link capacity across a large number of topologies.
Minru Bai
2014-01-01
Full Text Available As a major energy-saving industry, power industry has implemented energy-saving generation dispatching. Apart from security and economy, low carbon will be the most important target in power dispatch mechanisms. In this paper, considering a power system with many thermal power generators which use different petrochemical fuels (such as coal, petroleum, and natural gas to produce electricity, respectively, we establish a self-scheduling model based on the forecasted locational marginal prices, particularly taking into account CO2 emission constraint, CO2 emission cost, and unit heat value of fuels. Then, we propose a distributionally robust self-scheduling optimization model under uncertainty in both the distribution form and moments of the locational marginal prices, where the knowledge of the prices is solely derived from historical data. We prove that the proposed robust self-scheduling model can be solved to any precision in polynomial time. These arguments are confirmed in a practical example on the IEEE 30 bus test system.
An improved scheduling algorithm for linear networks
Bader, Ahmed
2017-02-09
In accordance with the present disclosure, embodiments of an exemplary scheduling controller module or device implement an improved scheduling process such that the targeted reduction in schedule length can be achieve while incurring minimal energy penalty by allowing for a large rate (or duration) selection alphabet.
Integrated model for pricing, delivery time setting, and scheduling in make-to-order environments
Garmdare, Hamid Sattari; Lotfi, M. M.; Honarvar, Mahboobeh
2017-05-01
Usually, in make-to-order environments which work only in response to the customer's orders, manufacturers for maximizing the profits should offer the best price and delivery time for an order considering the existing capacity and the customer's sensitivity to both the factors. In this paper, an integrated approach for pricing, delivery time setting and scheduling of new arrival orders are proposed based on the existing capacity and accepted orders in system. In the problem, the acquired market demands dependent on the price and delivery time of both the manufacturer and its competitors. A mixed-integer non-linear programming model is presented for the problem. After converting to a pure non-linear model, it is validated through a case study. The efficiency of proposed model is confirmed by comparing it to both the literature and the current practice. Finally, sensitivity analysis for the key parameters is carried out.
Fetene, Gebeyehu Manie
electric cars. The last chapter deals with analysis of energy consumption rate and its determinants of electric cars under the hands of customers. A variety of techniques are used including analysis of field data, economics laboratory experiments and theoretical modeling with simulation. Chapter one...... and Pricing of Electric Vehicle Recharging’, proposes, and tests at laboratory, contracts about recharging BEVs combining the ultimatum game framework and the myopic loss aversion (MLA) behavioral hypothesis. The model represents the behavior of EV-owners trading-off between the amount of the discount on fee...... price as long-term contracts may curtail MLA behavior and help BEV owners to choose cost minimizing recharging time and, simultaneously, may help to reduce BEVs impact on the electricity grid system. The fourth chapter, ‘Using the Peer Effect in Scheduling and Pricing Electric Vehicles Recharging...
Robust Optimization-Based Generation Self-Scheduling under Uncertain Price
Xiao Luo
2011-01-01
Full Text Available This paper considers generation self-scheduling in electricity markets under uncertain price. Based on the robust optimization (denoted as RO methodology, a new self-scheduling model, which has a complicated max-min optimization structure, is set up. By using optimal dual theory, the proposed model is reformulated to an ordinary quadratic and quadratic cone programming problems in the cases of box and ellipsoidal uncertainty, respectively. IEEE 30-bus system is used to test the new model. Some comparisons with other methods are done, and the sensitivity with respect to the uncertain set is analyzed. Comparing with the existed uncertain self-scheduling approaches, the new method has twofold characteristics. First, it does not need a prediction of distribution of random variables and just requires an estimated value and the uncertain set of power price. Second, the counterpart of RO corresponding to the self-scheduling is a simple quadratic or quadratic cone programming. This indicates that the reformulated problem can be solved by many ordinary optimization algorithms.
Location-Price Competition in Airline Networks
H. Gao
2014-01-01
Full Text Available This paper addresses location-then-price competition in airline market as a two-stage game of n players on the graph. Passenger’s demand distribution is described by multinomial logit model. Equilibrium in price game is computed through best response dynamics. We solve location game using backward induction, knowing that airlines will choose prices from equilibrium for the second-stage game. Some numerical results for airline market under consideration are presented.
Traffic Scheduling in WDM Passive Optical Network with Delay Guarantee
无
2005-01-01
WDM passive optical network becomes more favorable as the required bandwidth increases, but currently few media access control algorithms adapted to WDM access network. This paper presented a new scheduling algorithm for bandwidth sharing in WDM passive optical networks, which provides per-flow delay guarantee and supports variable-length packets scheduling. Through theoretical analysis and simulation, the end-to-end delay bound and throughput fairness of the algorithm was demonstrated.
Spectrum and service pricing for 802.22 networks
Stefan, Andrei Lucian; Rota, Cyril; Pratas, Nuno
2011-01-01
of channels which have an impact on the demand, and thus on the spectrum pricing. The second part of the paper exemplifies how a Bertrand game model can solve the issue of service pricing for a Wireless Regional Area Network (WRAN) operator that is trying to deploy an 802.22 network in a region where...... a competitor already exists. In this work the service pricing was envisioned as a network preplanning step, one that would show the potential revenues for an operator by entering as inputs, among other, the competitor's coverage area and spectrum pricing. The case study has been conducted through CNPT1......, an ongoing cognitive radio network planning tool developed by the authors....
Cooperative Resource Pricing in Service Overlay Networks for Mobile Agents
Nakano, Tadashi; Okaie, Yutaka
The success of peer-to-peer overlay networks depends on cooperation among participating peers. In this paper, we investigate the degree of cooperation among individual peers required to induce globally favorable properties in an overlay network. Specifically, we consider a resource pricing problem in a market-oriented overlay network where participating peers sell own resources (e.g., CPU cycles) to earn energy which represents some money or rewards in the network. In the resource pricing model presented in this paper, each peer sets the price for own resource based on the degree of cooperation; non-cooperative peers attempt to maximize their own energy gains, while cooperative peers maximize the sum of own and neighbors' energy gains. Simulation results are presented to demonstrate that the network topology is an important factor influencing the minimum degree of cooperation required to increase the network-wide global energy gain.
Chain-type wireless sensor network node scheduling strategy
Guangzhu Chen; Qingchun Meng; Lei Zhang
2014-01-01
In order to reduce power consumption of sensor nodes and extend network survival time in the wireless sensor network (WSN), sensor nodes are scheduled in an active or dormant mode. A chain-type WSN is fundamental y different from other types of WSNs, in which the sensor nodes are deployed along elongated geographic areas and form a chain-type network topo-logy structure. This paper investigates the node scheduling prob-lem in the chain-type WSN. Firstly, a node dormant scheduling mode is analyzed theoretical y from geographic coverage, and then three neighboring nodes scheduling criteria are proposed. Sec-ondly, a hybrid coverage scheduling algorithm and dead areas are presented. Final y, node scheduling in mine tunnel WSN with uniform deployment (UD), non-uniform deployment (NUD) and op-timal distribution point spacing (ODS) is simulated. The results show that the node scheduling with UD and NUD, especial y NUD, can effectively extend the network survival time. Therefore, a strat-egy of adding a few mobile nodes which activate the network in dead areas is proposed, which can further extend the network survival time by balancing the energy consumption of nodes.
Price discrimination, entry, and switching costs in network competition
Trifunović Dejan
2016-01-01
Full Text Available This paper reviews theoretical models of network competition in telecommunications. We will discuss two alternative approaches. The first approach assumes Hoteling’s horizontal differentiation and the second approach is based on switching costs. We will first analyse spatial competition with linear prices and continue with price discrimination between on-net and off-net calls. Price discrimination can also be used to deter entry to the market. We will also deal with the regulator’s optimal choice of access price, which should be designed to induce entry of new firms. Furthermore, pricing of roaming services and the switching cost approach to network competition will be considered. Finally, we will illustrate the theoretical results with data from the Serbian mobile and fixed telephony market.
Joint opportunistic scheduling and network coding for bidirectional relay channel
Shaqfeh, Mohammad
2013-07-01
In this paper, we consider a two-way communication system in which two users communicate with each other through an intermediate relay over block-fading channels. We investigate the optimal opportunistic scheduling scheme in order to maximize the long-term average transmission rate in the system assuming symmetric information flow between the two users. Based on the channel state information, the scheduler decides that either one of the users transmits to the relay, or the relay transmits to a single user or broadcasts to both users a combined version of the two users\\' transmitted information by using linear network coding. We obtain the optimal scheduling scheme by using the Lagrangian dual problem. Furthermore, in order to characterize the gains of network coding and opportunistic scheduling, we compare the achievable rate of the system versus suboptimal schemes in which the gains of network coding and opportunistic scheduling are partially exploited. © 2013 IEEE.
Scheduling components for multigigabit network SoCs
Orphanoudakis, Theofanis; Kornaros, George; Papaefstathiou, Ioannis; Leligou, Helen-Catherine; Perissakis, Stylianos; Zervos, Nicholas
2003-04-01
To meet the demand for higher performance, flexibility, and economy in today's state-of-the-art networks, great emphasis is placed on unconventional hardware architectures of network processors. This paper analyzes the problem of processor internal resource and traffic management and proposes a programmable scheduler architecture implemented in a novel protocol processor that deals with the above problems in an integrated way. We briefly outline the architecture of the protocol processor and we support that the innovative scheduling scheme integrated in PRO3 is, in general, crucial for network Systems-on-Chip since it makes it feasible to use scheduler's architecture are discussed that lead to efficient integration of the component to different network processor architectures at a similar cost. Its beneficial features are easy hardware implementation, low memory bandwidth requirements and high flexibility so as to support multiple service disciplines in a programmable way, thousands of flows and even perform different scheduling tasks.
New packet scheduling algorithm in wireless CDMA data networks
Wang, Yu; Gao, Zhuo; Li, Shaoqian; Li, Lemin
2002-08-01
The future 3G/4G wireless communication systems will provide internet access for mobile users. Packet scheduling algorithms are essential for QoS of diversified data traffics and efficient utilization of radio spectrum.This paper firstly presents a new packet scheduling algorithm DSTTF under the assumption of continuous transmission rates and scheduling intervals for CDMA data networks . Then considering the constraints of discrete transmission rates and fixed scheduling intervals imposed by the practical system, P-DSTTF, a modified version of DSTTF, is brought forward. Both scheduling algorithms take into consideration of channel condition, packet size and traffic delay bounds. The extensive simulation results demonstrate that the proposed scheduling algorithms are superior to some typical ones in current research. In addition, both static and dynamic wireless channel model of multi-level link capacity are established. These channel models sketch better the characterizations of wireless channel than two state Markov model widely adopted by the current literature.
Rate adaptation in ad hoc networks based on pricing
Awuor, F
2011-09-01
Full Text Available to transmit at high power leading to abnormal interference in the network hence degrades network performance (i.e. low data rates, loss of connectivity among others). In this paper, the authors propose rate adaptation based on pricing (RAP) algorithm...
Pricing Resources in LTE Networks through Multiobjective Optimization
Yung-Liang Lai
2014-01-01
Full Text Available The LTE technology offers versatile mobile services that use different numbers of resources. This enables operators to provide subscribers or users with differential quality of service (QoS to boost their satisfaction. On one hand, LTE operators need to price the resources high for maximizing their profits. On the other hand, pricing also needs to consider user satisfaction with allocated resources and prices to avoid “user churn,” which means subscribers will unsubscribe services due to dissatisfaction with allocated resources or prices. In this paper, we study the pricing resources with profits and satisfaction optimization (PRPSO problem in the LTE networks, considering the operator profit and subscribers' satisfaction at the same time. The problem is modelled as nonlinear multiobjective optimization with two optimal objectives: (1 maximizing operator profit and (2 maximizing user satisfaction. We propose to solve the problem based on the framework of the NSGA-II. Simulations are conducted for evaluating the proposed solution.
Pricing resources in LTE networks through multiobjective optimization.
Lai, Yung-Liang; Jiang, Jehn-Ruey
2014-01-01
The LTE technology offers versatile mobile services that use different numbers of resources. This enables operators to provide subscribers or users with differential quality of service (QoS) to boost their satisfaction. On one hand, LTE operators need to price the resources high for maximizing their profits. On the other hand, pricing also needs to consider user satisfaction with allocated resources and prices to avoid "user churn," which means subscribers will unsubscribe services due to dissatisfaction with allocated resources or prices. In this paper, we study the pricing resources with profits and satisfaction optimization (PRPSO) problem in the LTE networks, considering the operator profit and subscribers' satisfaction at the same time. The problem is modelled as nonlinear multiobjective optimization with two optimal objectives: (1) maximizing operator profit and (2) maximizing user satisfaction. We propose to solve the problem based on the framework of the NSGA-II. Simulations are conducted for evaluating the proposed solution.
Contoyannis, Paul; Hurley, Jeremiah; Grootendorst, Paul; Jeon, Sung-Hee; Tamblyn, Robyn
2005-09-01
The price elasticity of demand for prescription drugs is a crucial parameter of interest in designing pharmaceutical benefit plans. Estimating the elasticity using micro-data, however, is challenging because insurance coverage that includes deductibles, co-insurance provisions and maximum expenditure limits create a non-linear price schedule, making price endogenous (a function of drug consumption). In this paper we exploit an exogenous change in cost-sharing within the Quebec (Canada) public Pharmacare program to estimate the price elasticity of expenditure for drugs using IV methods. This approach corrects for the endogeneity of price and incorporates the concept of a 'rational' consumer who factors into consumption decisions the price they expect to face at the margin given their expected needs. The IV method is adapted from an approach developed in the public finance literature used to estimate income responses to changes in tax schedules. The instrument is based on the price an individual would face under the new cost-sharing policy if their consumption remained at the pre-policy level. Our preferred specification leads to expenditure elasticities that are in the low range of previous estimates (between -0.12 and -0.16). Naïve OLS estimates are between 1 and 4 times these magnitudes.
Scheduling and Pricing for Expected Ramp Capability in Real-Time Power Markets
Ela, Erik; O' Malley, Mark
2016-05-01
Higher variable renewable generation penetrations are occurring throughout the world on different power systems. These resources increase the variability and uncertainty on the system which must be accommodated by an increase in the flexibility of the system resources in order to maintain reliability. Many scheduling strategies have been discussed and introduced to ensure that this flexibility is available at multiple timescales. To meet variability, that is, the expected changes in system conditions, two recent strategies have been introduced: time-coupled multi-period market clearing models and the incorporation of ramp capability constraints. To appropriately evaluate these methods, it is important to assess both efficiency and reliability. But it is also important to assess the incentive structure to ensure that resources asked to perform in different ways have the proper incentives to follow these directions, which is a step often ignored in simulation studies. We find that there are advantages and disadvantages to both approaches. We also find that look-ahead horizon length in multi-period market models can impact incentives. This paper proposes scheduling and pricing methods that ensure expected ramps are met reliably, efficiently, and with associated prices based on true marginal costs that incentivize resources to do as directed by the market. Case studies show improvements of the new method.
Dynamic pricing of network goods with boundedly rational consumers.
Radner, Roy; Radunskaya, Ami; Sundararajan, Arun
2014-01-07
We present a model of dynamic monopoly pricing for a good that displays network effects. In contrast with the standard notion of a rational-expectations equilibrium, we model consumers as boundedly rational and unable either to pay immediate attention to each price change or to make accurate forecasts of the adoption of the network good. Our analysis shows that the seller's optimal price trajectory has the following structure: The price is low when the user base is below a target level, is high when the user base is above the target, and is set to keep the user base stationary once the target level has been attained. We show that this pricing policy is robust to a number of extensions, which include the product's user base evolving over time and consumers basing their choices on a mixture of a myopic and a "stubborn" expectation of adoption. Our results differ significantly from those that would be predicted by a model based on rational-expectations equilibrium and are more consistent with the pricing of network goods observed in practice.
Space Surveillance Network Scheduling Under Uncertainty: Models and Benefits
Valicka, C.; Garcia, D.; Staid, A.; Watson, J.; Rintoul, M.; Hackebeil, G.; Ntaimo, L.
2016-09-01
Advances in space technologies continue to reduce the cost of placing satellites in orbit. With more entities operating space vehicles, the number of orbiting vehicles and debris has reached unprecedented levels and the number continues to grow. Sensor operators responsible for maintaining the space catalog and providing space situational awareness face an increasingly complex and demanding scheduling requirements. Despite these trends, a lack of advanced tools continues to prevent sensor planners and operators from fully utilizing space surveillance resources. One key challenge involves optimally selecting sensors from a network of varying capabilities for missions with differing requirements. Another open challenge, the primary focus of our work, is building robust schedules that effectively plan for uncertainties associated with weather, ad hoc collections, and other target uncertainties. Existing tools and techniques are not amenable to rigorous analysis of schedule optimality and do not adequately address the presented challenges. Building on prior research, we have developed stochastic mixed-integer linear optimization models to address uncertainty due to weather's effect on collection quality. By making use of the open source Pyomo optimization modeling software, we have posed and solved sensor network scheduling models addressing both forms of uncertainty. We present herein models that allow for concurrent scheduling of collections with the same sensor configuration and for proactively scheduling against uncertain ad hoc collections. The suitability of stochastic mixed-integer linear optimization for building sensor network schedules under different run-time constraints will be discussed.
Distributed Estimation, Coding, and Scheduling in Wireless Visual Sensor Networks
Yu, Chao
2013-01-01
In this thesis, we consider estimation, coding, and sensor scheduling for energy efficient operation of wireless visual sensor networks (VSN), which consist of battery-powered wireless sensors with sensing (imaging), computation, and communication capabilities. The competing requirements for applications of these wireless sensor networks (WSN)…
Distributed Estimation, Coding, and Scheduling in Wireless Visual Sensor Networks
Yu, Chao
2013-01-01
In this thesis, we consider estimation, coding, and sensor scheduling for energy efficient operation of wireless visual sensor networks (VSN), which consist of battery-powered wireless sensors with sensing (imaging), computation, and communication capabilities. The competing requirements for applications of these wireless sensor networks (WSN)…
Scheduling Advantages of Network Coded Storage in Point-to-Multipoint Networks
Ferner, Ulric J.; Sadeghi, Parastoo; Aboutorab, Neda; Medard, Muriel
2014-01-01
We consider scheduling strategies for point-to-multipoint (PMP) storage area networks (SANs) that use network coded storage (NCS). In particular, we present a simple SAN system model, two server scheduling algorithms for PMP networks, and analytical expressions for internal and external blocking probability. We point to select scheduling advantages in NCS systems under normal operating conditions, where content requests can be temporarily denied owing to finite system capacity from drive I/O ...
Toward an Autonomous Telescope Network: the TBT Scheduler
Racero, E.; Ibarra, A.; Ocaña, F.; de Lis, S. B.; Ponz, J. D.; Castillo, M.; Sánchez-Portal, M.
2015-09-01
Within the ESA SSA program, it is foreseen to deploy several robotic telescopes to provide surveillance and tracking services for hazardous objects. The TBT project will procure a validation platform for an autonomous optical observing system in a realistic scenario, consisting of two telescopes located in Spain and Australia, to collect representative test data for precursor SSA services. In this context, the planning and scheduling of the night consists of two software modules, the TBT Scheduler, that will allow the manual and autonomous planning of the night, and the control of the real-time response of the system, done by the RTS2 internal scheduler. The TBT Scheduler allocates tasks for both telescopes without human intervention. Every night it takes all the inputs needed and prepares the schedule following some predefined rules. The main purpose of the scheduler is the distribution of the time for follow-up of recently discovered targets and surveys. The TBT Scheduler considers the overall performance of the system, and combine follow-up with a priori survey strategies for both kind of objects. The strategy is defined according to the expected combined performance for both systems the upcoming night (weather, sky brightness, object accessibility and priority). Therefore, TBT Scheduler defines the global approach for the network and relies on the RTS2 internal scheduler for the final detailed distribution of tasks at each sensor.
A Heuristic Scheduling Scheme in Multiuser OFDMA Networks
Sun, Zheng; Wang, Ruochen; Niu, Kai
2008-01-01
Conventional heterogeneous-traffic scheduling schemes utilize zero-delay constraint for real-time services, which aims to minimize the average packet delay among real-time users. However, in light or moderate load networks this strategy is unnecessary and leads to low data throughput for non-real-time users. In this paper, we propose a heuristic scheduling scheme to solve this problem. The scheme measures and assigns scheduling priorities to both real-time and non-real-time users, and schedules the radio resources for the two user classes simultaneously. Simulation results show that the proposed scheme efficiently handles the heterogeneous-traffic scheduling with diverse QoS requirements and alleviates the unfairness between real-time and non-real-time services under various traffic loads.
Developing scheduling benchmark tests for the Space Network
Moe, Karen L.; Happell, Nadine; Brady, Sean
1993-01-01
A set of benchmark tests were developed to analyze and measure Space Network scheduling characteristics and to assess the potential benefits of a proposed flexible scheduling concept. This paper discusses the role of the benchmark tests in evaluating alternative flexible scheduling approaches and defines a set of performance measurements. The paper describes the rationale for the benchmark tests as well as the benchmark components, which include models of the Tracking and Data Relay Satellite (TDRS), mission spacecraft, their orbital data, and flexible requests for communication services. Parameters which vary in the tests address the degree of request flexibility, the request resource load, and the number of events to schedule. Test results are evaluated based on time to process and schedule quality. Preliminary results and lessons learned are addressed.
Price of anarchy in transportation networks: efficiency and optimality control.
Youn, Hyejin; Gastner, Michael T; Jeong, Hawoong
2008-09-19
Uncoordinated individuals in human society pursuing their personally optimal strategies do not always achieve the social optimum, the most beneficial state to the society as a whole. Instead, strategies form Nash equilibria which are often socially suboptimal. Society, therefore, has to pay a price of anarchy for the lack of coordination among its members. Here we assess this price of anarchy by analyzing the travel times in road networks of several major cities. Our simulation shows that uncoordinated drivers possibly waste a considerable amount of their travel time. Counterintuitively, simply blocking certain streets can partially improve the traffic conditions. We analyze various complex networks and discuss the possibility of similar paradoxes in physics.
Auction pricing of network access for North American railways
Harrod, Steven
2013-01-01
The question of pricing train paths for "open access" railway networks in North America is discussed. An auction process is suggested as necessary to maintain transparency in the contracting process. Multiple random samples of auction pricing for a single track railway line demonstrate that the i...... that the infrastructure entity will receive approximately 15.6% less than the true value of the contracted train paths. This loss of revenue threatens the objective of reducing government subsidy for the railway network. (C) 2012 Elsevier Ltd. All rights reserved....
The price of complexity in financial networks.
Battiston, Stefano; Caldarelli, Guido; May, Robert M; Roukny, Tarik; Stiglitz, Joseph E
2016-09-06
Financial institutions form multilayer networks by engaging in contracts with each other and by holding exposures to common assets. As a result, the default probability of one institution depends on the default probability of all of the other institutions in the network. Here, we show how small errors on the knowledge of the network of contracts can lead to large errors in the probability of systemic defaults. From the point of view of financial regulators, our findings show that the complexity of financial networks may decrease the ability to mitigate systemic risk, and thus it may increase the social cost of financial crises.
The price of complexity in financial networks
Battiston, Stefano; Caldarelli, Guido; May, Robert M.; Roukny, Tarik; Stiglitz, Joseph E.
2016-09-01
Financial institutions form multilayer networks by engaging in contracts with each other and by holding exposures to common assets. As a result, the default probability of one institution depends on the default probability of all of the other institutions in the network. Here, we show how small errors on the knowledge of the network of contracts can lead to large errors in the probability of systemic defaults. From the point of view of financial regulators, our findings show that the complexity of financial networks may decrease the ability to mitigate systemic risk, and thus it may increase the social cost of financial crises.
The price of complexity in financial networks
May, Robert M.; Roukny, Tarik; Stiglitz, Joseph E.
2016-01-01
Financial institutions form multilayer networks by engaging in contracts with each other and by holding exposures to common assets. As a result, the default probability of one institution depends on the default probability of all of the other institutions in the network. Here, we show how small errors on the knowledge of the network of contracts can lead to large errors in the probability of systemic defaults. From the point of view of financial regulators, our findings show that the complexity of financial networks may decrease the ability to mitigate systemic risk, and thus it may increase the social cost of financial crises. PMID:27555583
Forecasting Model for Crude Oil Price Using Artificial Neural Networks and Commodity Futures Prices
Kulkarni, Siddhivinayak
2009-01-01
This paper presents a model based on multilayer feedforward neural network to forecast crude oil spot price direction in the short-term, up to three days ahead. A great deal of attention was paid on finding the optimal ANN model structure. In addition, several methods of data pre-processing were tested. Our approach is to create a benchmark based on lagged value of pre-processed spot price, then add pre-processed futures prices for 1, 2, 3,and four months to maturity, one by one and also altogether. The results on the benchmark suggest that a dynamic model of 13 lags is the optimal to forecast spot price direction for the short-term. Further, the forecast accuracy of the direction of the market was 78%, 66%, and 53% for one, two, and three days in future conclusively. For all the experiments, that include futures data as an input, the results show that on the short-term, futures prices do hold new information on the spot price direction. The results obtained will generate comprehensive understanding of the cr...
Request-Driven Schedule Automation for the Deep Space Network
Johnston, Mark D.; Tran, Daniel; Arroyo, Belinda; Call, Jared; Mercado, Marisol
2010-01-01
The DSN Scheduling Engine (DSE) has been developed to increase the level of automated scheduling support available to users of NASA s Deep Space Network (DSN). We have adopted a request-driven approach to DSN scheduling, in contrast to the activity-oriented approach used up to now. Scheduling requests allow users to declaratively specify patterns and conditions on their DSN service allocations, including timing, resource requirements, gaps, overlaps, time linkages among services, repetition, priorities, and a wide range of additional factors and preferences. The DSE incorporates a model of the key constraints and preferences of the DSN scheduling domain, along with algorithms to expand scheduling requests into valid resource allocations, to resolve schedule conflicts, and to repair unsatisfied requests. We use time-bounded systematic search with constraint relaxation to return nearby solutions if exact ones cannot be found, where the relaxation options and order are under user control. To explore the usability aspects of our approach we have developed a graphical user interface incorporating some crucial features to make it easier to work with complex scheduling requests. Among these are: progressive revelation of relevant detail, immediate propagation and visual feedback from a user s decisions, and a meeting calendar metaphor for repeated patterns of requests. Even as a prototype, the DSE has been deployed and adopted as the initial step in building the operational DSN schedule, thus representing an important initial validation of our overall approach. The DSE is a core element of the DSN Service Scheduling Software (S(sup 3)), a web-based collaborative scheduling system now under development for deployment to all DSN users.
Scheduled Controller Design of Congestion Control Considering Network Resource Constraints
Naito, Hiroyuki; Azuma, Takehito; Fujita, Masayuki
In this paper, we consider a dynamical model of computer networks and derive a synthesis method for congestion control. First, we show a model of TCP/AQM (Transmission Control Protocol/Active Queue Management) as a dynamical model of computer networks. The dynamical model of TCP/AQM networks consists of models of TCP window size, queue length and AQM mechanisms. Second, we propose to describe the dynamical model of TCP/AQM networks as linear systems with self-scheduling parameters, which also depend on information delay. Here we focus on the constraints on the maximum queue length and TCP window-size, which are the network resources in TCP/AQM networks. We derive TCP/AQM networks as the LPV system (linear parameter varying system) with information delay and self-scheduling parameter. We design a memoryless state feedback controller of the LPV system based on a gain-scheduling method. Finally, the effectiveness of the proposed method is evaluated by using MATLAB and the well-known ns-2 (Network Simulator Ver.2) simulator.
On bid-price controls for network revenue management
Bariş Ata
2015-12-01
Full Text Available We consider a network revenue management problem and advance its dual formulation. The dual formulation reveals that the (optimal shadow price of capacity forms a nonnegative martingale. This result is proved under minimal assumptions on network topology and stochastic nature of demand, allowing an arbitrary statistical dependence structure across time and products. Next, we consider a quadratic perturbation of the network revenue management problem and show that a simple (perturbed bid-price control is optimal for the perturbed problem; and it is ε-optimal for the original network revenue management problem. Finally, we consider a predictable version of this control, where the bid prices used in the current period are last updated in the previous period, and provide an upper bound on its optimality gap in terms of the (quadratic variation of demand. Using this upper bound we show that there exists a near-optimal such control in the usual case when periods are small compared to the planning horizon provided that either demand or the incremental information arriving during each period is small. We establish the martingale property of the (near optimal bid prices in both settings. The martingale property can have important implications in practice as it may offer a tool for monitoring the revenue management systems.
Second-best Pricing for Imperfect Substitutes in Urban Networks
Rouwendal, J.; Verhoef, Erik
2003-01-01
This paper considers second-best pricing as it arises through incomplete coverage of full networks. The main principles are first reviewed by considering the classic two-route problem and some extensions that have been studied more recently. In most of these studies the competing routes are assumed
Network Asymmetries and Access Pricing in Cellular Telecommunications
V. Kocsis
2005-01-01
textabstractNetwork shares and retail prices are not symmetric in the telecommunications market with multiple bottlenecks which give rise to new questions of access fee regulation. In this paper we consider a model with two types of asymmetry arising from different entry timing, i.e. a larger reputa
Network Asymmetries and Access Pricing in Cellular Telecommunications
V. Kocsis
2005-01-01
textabstractNetwork shares and retail prices are not symmetric in the telecommunications market with multiple bottlenecks which give rise to new questions of access fee regulation. In this paper we consider a model with two types of asymmetry arising from different entry timing, i.e. a larger reputa
Charge scheduling of an energy storage system under time-of-use pricing and a demand charge.
Yoon, Yourim; Kim, Yong-Hyuk
2014-01-01
A real-coded genetic algorithm is used to schedule the charging of an energy storage system (ESS), operated in tandem with renewable power by an electricity consumer who is subject to time-of-use pricing and a demand charge. Simulations based on load and generation profiles of typical residential customers show that an ESS scheduled by our algorithm can reduce electricity costs by approximately 17%, compared to a system without an ESS and by 8% compared to a scheduling algorithm based on net power.
Modeling of price and profit in coupled-ring networks
Tangmongkollert, Kittiwat; Suwanna, Sujin
2016-06-01
We study the behaviors of magnetization, price, and profit profiles in ring networks in the presence of the external magnetic field. The Ising model is used to determine the state of each node, which is mapped to the buy-or-sell state in a financial market, where +1 is identified as the buying state, and -1 as the selling state. Price and profit mechanisms are modeled based on the assumption that price should increase if demand is larger than supply, and it should decrease otherwise. We find that the magnetization can be induced between two rings via coupling links, where the induced magnetization strength depends on the number of the coupling links. Consequently, the price behaves linearly with time, where its rate of change depends on the magnetization. The profit grows like a quadratic polynomial with coefficients dependent on the magnetization. If two rings have opposite direction of net spins, the price flows in the direction of the majority spins, and the network with the minority spins gets a loss in profit.
Particle swarm optimization based space debris surveillance network scheduling
Jiang, Hai; Liu, Jing; Cheng, Hao-Wen; Zhang, Yao
2017-02-01
The increasing number of space debris has created an orbital debris environment that poses increasing impact risks to existing space systems and human space flights. For the safety of in-orbit spacecrafts, we should optimally schedule surveillance tasks for the existing facilities to allocate resources in a manner that most significantly improves the ability to predict and detect events involving affected spacecrafts. This paper analyzes two criteria that mainly affect the performance of a scheduling scheme and introduces an artificial intelligence algorithm into the scheduling of tasks of the space debris surveillance network. A new scheduling algorithm based on the particle swarm optimization algorithm is proposed, which can be implemented in two different ways: individual optimization and joint optimization. Numerical experiments with multiple facilities and objects are conducted based on the proposed algorithm, and simulation results have demonstrated the effectiveness of the proposed algorithm.
Mixed Criticality Scheduling for Industrial Wireless Sensor Networks
Jin, Xi; Xia, Changqing; Xu, Huiting; Wang, Jintao; Zeng, Peng
2016-01-01
Wireless sensor networks (WSNs) have been widely used in industrial systems. Their real-time performance and reliability are fundamental to industrial production. Many works have studied the two aspects, but only focus on single criticality WSNs. Mixed criticality requirements exist in many advanced applications in which different data flows have different levels of importance (or criticality). In this paper, first, we propose a scheduling algorithm, which guarantees the real-time performance and reliability requirements of data flows with different levels of criticality. The algorithm supports centralized optimization and adaptive adjustment. It is able to improve both the scheduling performance and flexibility. Then, we provide the schedulability test through rigorous theoretical analysis. We conduct extensive simulations, and the results demonstrate that the proposed scheduling algorithm and analysis significantly outperform existing ones. PMID:27589741
2010-07-08
... Notice of Proposed Information Collection: Retail Price Schedule, DS-2020 Parts 1-4, DS-2020I, DS-2021, DS-1996, 1405-XXXX ACTION: Notice of request for public comments. SUMMARY: The Department of State is... Allowances (A/OPR/ALS). Form Number: DS-2020, DS-2020I, DS-2021, DS-1996. Respondents: Respondents are...
Optimal Sensor Networks Scheduling in Identification of Distributed Parameter Systems
Patan, Maciej
2012-01-01
Sensor networks have recently come into prominence because they hold the potential to revolutionize a wide spectrum of both civilian and military applications. An ingenious characteristic of sensor networks is the distributed nature of data acquisition. Therefore they seem to be ideally prepared for the task of monitoring processes with spatio-temporal dynamics which constitute one of most general and important classes of systems in modelling of the real-world phenomena. It is clear that careful deployment and activation of sensor nodes are critical for collecting the most valuable information from the observed environment. Optimal Sensor Network Scheduling in Identification of Distributed Parameter Systems discusses the characteristic features of the sensor scheduling problem, analyzes classical and recent approaches, and proposes a wide range of original solutions, especially dedicated for networks with mobile and scanning nodes. Both researchers and practitioners will find the case studies, the proposed al...
Pricing Strategies for Viral Marketing on Social Networks
Arthur, David
2009-01-01
We study the use of viral marketing strategies on social networks that seek to maximize revenue from the sale of a single product. We propose a model in which the decision of a buyer to buy the product is influenced by friends that own the product and the price at which the product is offered. The influence model we analyze is quite general, naturally extending both the Linear Threshold model and the Independent Cascade model, while also incorporating price information. We consider sales proceeding in a cascading manner through the network, i.e. a buyer is offered the product via recommendations from its neighbors who own the product. In this setting, the seller influences events by offering a cashback to recommenders and by setting prices (via coupons or discounts) for each buyer in the social network. This choice of prices for the buyers is termed as the seller\\'s strategy. Finding a seller strategy which maximizes the expected revenue in this setting turns out to be NP-hard. However, we propose a seller strategy that generates revenue guaranteed to be within a constant factor of the optimal strategy in a wide variety of models. The strategy is based on an influence-and-exploit idea, and it consists of finding the right trade-off at each time step between: generating revenue from the current user versus offering the product for free and using the influence generated from this sale later in the process. © 2009 Springer-Verlag Berlin Heidelberg.
Price of anarchy on heterogeneous traffic-flow networks
Rose, A.; O'Dea, R.; Hopcraft, K. I.
2016-09-01
The efficiency of routing traffic through a network, comprising nodes connected by links whose cost of traversal is either fixed or varies in proportion to volume of usage, can be measured by the "price of anarchy." This is the ratio of the cost incurred by agents who act to minimize their individual expenditure to the optimal cost borne by the entire system. As the total traffic load and the network variability—parameterized by the proportion of variable-cost links in the network—changes, the behaviors that the system presents can be understood with the introduction of a network of simpler structure. This is constructed from classes of nonoverlapping paths connecting source to destination nodes that are characterized by the number of variable-cost edges they contain. It is shown that localized peaks in the price of anarchy occur at critical traffic volumes at which it becomes beneficial to exploit ostensibly more expensive paths as the network becomes more congested. Simulation results verifying these findings are presented for the variation of the price of anarchy with the network's size, aspect ratio, variability, and traffic load.
MAC scheduling in large-scale underwater acoustic networks
Kleunen, van Wouter; Meratnia, Nirvana; Havinga, Paul J.M.
2011-01-01
The acoustic propagation speed under water poses significant challenges to the design of underwater sensor networks and their medium access control protocols. Scheduling allows reducing the effects of long propagation delay of the acoustic signal and has significant impacts on throughput, energy con
Performance analysis of adaptive scheduling in integrated services UMTS networks
Litjens, Remco; Berg, van den Hans
2002-01-01
For an integrated services UMTS network serving speech and data calls, we propose, evaluate and compare different scheduling schemes, which dynamically adapt the shared data transport channel rates to the varying speech traffic load. within each cell, the assigned data transfer resources are distrib
Multimodal processes scheduling in mesh-like network environment
Bocewicz Grzegorz
2015-06-01
Full Text Available Multimodal processes planning and scheduling play a pivotal role in many different domains including city networks, multimodal transportation systems, computer and telecommunication networks and so on. Multimodal process can be seen as a process partially processed by locally executed cyclic processes. In that context the concept of a Mesh-like Multimodal Transportation Network (MMTN in which several isomorphic subnetworks interact each other via distinguished subsets of common shared intermodal transport interchange facilities (such as a railway station, bus station or bus/tram stop as to provide a variety of demand-responsive passenger transportation services is examined. Consider a mesh-like layout of a passengers transport network equipped with different lines including buses, trams, metro, trains etc. where passenger flows are treated as multimodal processes. The goal is to provide a declarative model enabling to state a constraint satisfaction problem aimed at multimodal transportation processes scheduling encompassing passenger flow itineraries. Then, the main objective is to provide conditions guaranteeing solvability of particular transport lines scheduling, i.e. guaranteeing the right match-up of local cyclic acting bus, tram, metro and train schedules to a given passengers flow itineraries.
Interval algebra: an effective means of scheduling surveillance radar networks
Focke, RW
2015-05-01
Full Text Available Interval Algebra provides an effective means to schedule surveillance radar networks, as it is a temporal ordering constraint language. Thus it provides a solution to a part of resource management, which is included in the revised Data Fusion...
A Light-Weight Statically Scheduled Network-on-Chip
Sørensen, Rasmus Bo; Schoeberl, Martin; Sparsø, Jens
2012-01-01
This paper investigates how a light-weight, statically scheduled network-on-chip (NoC) for real-time systems can be designed and implemented. The NoC provides communication channels between all cores with equal bandwidth and latency. The design is FPGA-friendly and consumes a minimum of resources...
A Data Scheduling and Management Infrastructure for the TEAM Network
Andelman, S.; Baru, C.; Chandra, S.; Fegraus, E.; Lin, K.; Unwin, R.
2009-04-01
currently partnering with the San Diego Super Computer Center to build the data management infrastructure. Data collected from the three core protocols as well as others are currently made available through the TEAM Network portal, which provides the content management framework, the data scheduling and management framework, an administrative framework to implement and manage TEAM sites, collaborative tools and a number of tools and applications utilizing Google Map and Google Earth products. A critical element of the TEAM Network data management infrastructure is to make the data publicly available in as close to real-time as possible (the TEAM Network Data Use Policy: http://www.teamnetwork.org/en/data/policy). This requires two essential tasks to be accomplished, 1) A data collection schedule has to be planned, proposed and approved for a given TEAM site. This is a challenging process since TEAM sites are geographically distributed across the tropics and hence have different seasons where they schedule field sampling for the different TEAM protocols. Capturing this information and ensuring that TEAM sites follow the outlined legal contract is key to the data collection process and 2) A stream-lined and efficient information management system to ensure data collected from the field meet the minimum data standards (i.e. are of the highest scientific quality) and are securely transferred, archived, processed and be rapidly made publicaly available, as a finished consumable product via the TEAM Network portal. The TEAM Network is achieving these goals by implementing an end-to-end framework consisting of the Sampling Scheduler application and the Data Management Framework. Sampling Scheduler The Sampling Scheduler is a project management, calendar based portal application that will allow scientists at a TEAM site to schedule field sampling for each of the TEAM protocols implemented at that site. The sampling scheduler addresses the specific requirements established in the
O. V. Russkov
2015-01-01
Full Text Available The article considers a hot issue to forecast electric power demand amounts and prices for the entities of wholesale electricity market (WEM, which are in capacity of a large user with production technology requirements prevailing over hourly energy planning ones. An electric power demand of such entities is on irregular schedule. The article analyses mathematical models, currently applied to forecast demand amounts and prices. It describes limits of time-series models and fundamental ones in case of hourly forecasting an irregular demand schedule of the electricity market entity. The features of electricity trading at WEM are carefully analysed. Factors that influence on irregularity of demand schedule of the metallurgical plant are shown. The article proposes method for the qualitative forecast of market price ratios as a tool to reduce a dependence on the accuracy of forecasting an irregular schedule of demand. It describes the differences between the offered method and the similar ones considered in research studies and scholarly works. The correlation between price ratios and relaxation in the requirements for the forecast accuracy of the electric power consumption is analysed. The efficiency function of forecast method is derived. The article puts an increased focus on description of the mathematical model based on the method of qualitative forecast. It shows main model parameters and restrictions the electricity market imposes on them. The model prototype is described as a programme module. Methods to assess an effectiveness of the proposed forecast model are examined. The positive test results of the model using JSC «Volzhsky Pipe Plant» data are given. A conclusion is drawn concerning the possibility to decrease dependence on the forecast accuracy of irregular schedule of entity’s demand at WEM. The effective trading tool has been found for the entities of irregular demand schedule at WEM. The tool application allows minimizing cost
Application for Single Price Auction Model (SPA) in AC Network
Wachi, Tsunehisa; Fukutome, Suguru; Chen, Luonan; Makino, Yoshinori; Koshimizu, Gentarou
This paper aims to develop a single price auction model with AC transmission network, based on the principle of maximizing social surplus of electricity market. Specifically, we first formulate the auction market as a nonlinear optimization problem, which has almost the same form as the conventional optimal power flow problem, and then propose an algorithm to derive both market clearing price and trade volume of each player even for the case of market-splitting. As indicated in the paper, the proposed approach can be used not only for the price evaluation of auction or bidding market but also for analysis of bidding strategy, congestion effect and other constraints or factors. Several numerical examples are used to demonstrate effectiveness of our method.
Schedule-based sequential localization in asynchronous wireless networks
Zachariah, Dave; De Angelis, Alessio; Dwivedi, Satyam; Händel, Peter
2014-12-01
In this paper, we consider the schedule-based network localization concept, which does not require synchronization among nodes and does not involve communication overhead. The concept makes use of a common transmission sequence, which enables each node to perform self-localization and to localize the entire network, based on noisy propagation-time measurements. We formulate the schedule-based localization problem as an estimation problem in a Bayesian framework. This provides robustness with respect to uncertainty in such system parameters as anchor locations and timing devices. Moreover, we derive a sequential approximate maximum a posteriori (AMAP) estimator. The estimator is fully decentralized and copes with varying noise levels. By studying the fundamental constraints given by the considered measurement model, we provide a system design methodology which enables a scalable solution. Finally, we evaluate the performance of the proposed AMAP estimator by numerical simulations emulating an impulse-radio ultra-wideband (IR-UWB) wireless network.
GCF: Green Conflict Free TDMA Scheduling for Wireless Sensor Network
Pawar, Pranav M.; Nielsen, Rasmus Hjorth; Prasad, Neeli R.
2012-01-01
The last few years have seen the promising growth in the application of wireless sensor networks (WSNs). The contribution of this paper is on a cluster-based time division multiple access (TDMA) scheduling algorithm to improve the performance of WSN applications in terms of energy efficiency, delay......- and intra-cluster communication. The algorithm is applied to a multi-hop cluster and uses a conflict graph to find the conflict free schedule. It helps to reduce the number of conflicts. Compared to state-of-the-art solutions, the algorithm shows better energy efficiency, average delay, scalability...
Energy Efficient Cluster Based Scheduling Scheme for Wireless Sensor Networks.
Janani, E Srie Vidhya; Kumar, P Ganesh
2015-01-01
The energy utilization of sensor nodes in large scale wireless sensor network points out the crucial need for scalable and energy efficient clustering protocols. Since sensor nodes usually operate on batteries, the maximum utility of network is greatly dependent on ideal usage of energy leftover in these sensor nodes. In this paper, we propose an Energy Efficient Cluster Based Scheduling Scheme for wireless sensor networks that balances the sensor network lifetime and energy efficiency. In the first phase of our proposed scheme, cluster topology is discovered and cluster head is chosen based on remaining energy level. The cluster head monitors the network energy threshold value to identify the energy drain rate of all its cluster members. In the second phase, scheduling algorithm is presented to allocate time slots to cluster member data packets. Here congestion occurrence is totally avoided. In the third phase, energy consumption model is proposed to maintain maximum residual energy level across the network. Moreover, we also propose a new packet format which is given to all cluster member nodes. The simulation results prove that the proposed scheme greatly contributes to maximum network lifetime, high energy, reduced overhead, and maximum delivery ratio.
Heuristic based data scheduling algorithm for OFDMA wireless network
无
2008-01-01
A system model based on joint layer mechanism is formulated for optimal data scheduling over fixed point-to-point links in OFDMA ad-hoc wireless networks.A distributed scheduling algorithm (DSA) for system model optimization is proposed that combines the randomly chosen subcarrier according to the channel condition of local subcarriers with link power control to limit interference caused by the reuse of subcarrier among links.For the global fairness improvement of algorithms,a global power control scheduling algorithm (GPCSA) based on the proposed DSA is presented and dynamically allocates global power according to difference between average carrier-noise-ratio of selected local links and system link protection ratio.Simulation results demonstrate that the proposed algorithms achieve better efficiency and fairness compared with other existing algorithms.
Link Scheduling in Multi-Transmit-Receive Wireless Networks
Dai, Hong-Ning; Fu, Liqun
2011-01-01
This paper investigates the problem of link scheduling to meet traffic demands with minimum airtime in a multi-transmit-receive (MTR) wireless network. MTR networks are a new class of networks, in which each node can simultaneously transmit to a number of other nodes, or simultaneously receive from a number of other nodes. The MTR capability can be enabled by the use of multiple directional antennas or multiple channels. Potentially, MTR can boost the network capacity significantly. However, link scheduling that makes full use of the MTR capability must be in place before this can happen. We show that optimal link scheduling can be formulated as a linear program (LP). However, the problem is NP-hard because we need to find all the maximal independent sets in a graph first. We propose two computationally efficient algorithms, called Heavy-Weight-First (HWF) and Max-Degree-First (MDF) to solve this problem. Simulation results show that both HWF and MDF can achieve superior performance in terms of runtime and op...
A NOVEL QOS SCHEDULING FOR WIRELESS BROADBAND NETWORKS
D. David Neels Pon Kumar
2010-09-01
Full Text Available During the last few years, users all over the world have become more and more familiar to the availability of broadband access. When users want broadband Internet service, they are generally restricted to a DSL (Digital Subscribers Line, or cable-modem-based connection. Proponents are advocating worldwide interoperability for microwave access (WiMAX, a technology based on an evolving standard for point-to multipoint wireless networking. Scheduling algorithms that support Quality of Service (QoS differentiation and guarantees for wireless data networks are crucial to the deployment of broadband wireless networks. The performance affecting parameters like fairness, bandwidth allocation, throughput, latency are studied and found out that none of the conventional algorithms perform effectively for both fairness and bandwidth allocation simultaneously. Hence it is absolutely essential for an efficient scheduling algorithm with a better trade off for these two parameters. So we are proposing a novel Scheduling Algorithm using Fuzzy logic and Artificial neural networks that addresses these aspects simultaneously. The initial results show that a fair amount of fairness is attained while keeping the priority intact. Results also show that maximum channel utilization is achieved with a negligible increment in processing time.
Constrained Task Assignment and Scheduling On Networks of Arbitrary Topology
Jackson, Justin Patrick
This dissertation develops a framework to address centralized and distributed constrained task assignment and task scheduling problems. This framework is used to prove properties of these problems that can be exploited, develop effective solution algorithms, and to prove important properties such as correctness, completeness and optimality. The centralized task assignment and task scheduling problem treated here is expressed as a vehicle routing problem with the goal of optimizing mission time subject to mission constraints on task precedence and agent capability. The algorithm developed to solve this problem is able to coordinate vehicle (agent) timing for task completion. This class of problems is NP-hard and analytical guarantees on solution quality are often unavailable. This dissertation develops a technique for determining solution quality that can be used on a large class of problems and does not rely on traditional analytical guarantees. For distributed problems several agents must communicate to collectively solve a distributed task assignment and task scheduling problem. The distributed task assignment and task scheduling algorithms developed here allow for the optimization of constrained military missions in situations where the communication network may be incomplete and only locally known. Two problems are developed. The distributed task assignment problem incorporates communication constraints that must be satisfied; this is the Communication-Constrained Distributed Assignment Problem. A novel distributed assignment algorithm, the Stochastic Bidding Algorithm, solves this problem. The algorithm is correct, probabilistically complete, and has linear average-case time complexity. The distributed task scheduling problem addressed here is to minimize mission time subject to arbitrary predicate mission constraints; this is the Minimum-time Arbitrarily-constrained Distributed Scheduling Problem. The Optimal Distributed Non-sequential Backtracking Algorithm
Pricing strategies for viral marketing on Social Networks
Arthur, David; Sharma, Aneesh; Xu, Ying
2009-01-01
We study the use of viral marketing strategies on social networks to maximize revenue from the sale of a single product. We propose a model in which the decision of a buyer to buy the product is influenced by friends that own the product and the price at which the product is offered. The influence model we analyze is quite general, naturally extending both the Linear Threshold model and the Independent Cascade model, while also incorporating price information. We consider sales proceeding in a cascading manner through the network, i.e. a buyer is offered the product via recommendations from its neighbors who own the product. In this setting, the seller influences events by offering a cashback to recommenders and by setting prices (via coupons or discounts) for each buyer in the social network. Finding a seller strategy which maximizes the expected revenue in this setting turns out to be NP-hard. However, we propose a seller strategy that generates revenue guaranteed to be within a constant factor of the optim...
Distributed Algorithms for Scheduling on Line and Tree Networks
Chakaravarthy, Venkatesan T; Sabharwal, Yogish
2012-01-01
We have a set of processors (or agents) and a set of graph networks defined over some vertex set. Each processor can access a subset of the graph networks. Each processor has a demand specified as a pair of vertices $$, along with a profit; the processor wishes to send data between $u$ and $v$. Towards that goal, the processor needs to select a graph network accessible to it and a path connecting $u$ and $v$ within the selected network. The processor requires exclusive access to the chosen path, in order to route the data. Thus, the processors are competing for routes/channels. A feasible solution selects a subset of demands and schedules each selected demand on a graph network accessible to the processor owning the demand; the solution also specifies the paths to use for this purpose. The requirement is that for any two demands scheduled on the same graph network, their chosen paths must be edge disjoint. The goal is to output a solution having the maximum aggregate profit. Prior work has addressed the above...
An Adaptive Power Efficient Packet Scheduling Algorithm for Wimax Networks
Prasad, R Murali
2010-01-01
Admission control schemes and scheduling algorithms are designed to offer QoS services in 802.16/802.16e networks and a number of studies have investigated these issues. But the channel condition and priority of traffic classes are very rarely considered in the existing scheduling algorithms. Although a number of energy saving mechanisms have been proposed for the IEEE 802.16e, to minimize the power consumption of IEEE 802.16e mobile stations with multiple real-time connections has not yet been investigated. Moreover, they mainly consider non real- time connections in IEEE 802.16e networks. In this paper, we propose to design an adaptive power efficient packet scheduling algorithm that provides a minimum fair allocation of the channel bandwidth for each packet flow and additionally minimizes the power consumption. In the adaptive scheduling algorithm, packets are transmitted as per allotted slots from different priority of traffic classes adaptively, depending on the channel condition. Suppose if the buffer s...
Calculating the Price of Anarchy for Network Formation Games
Lichter, Shaun; Friesz, Terry
2011-01-01
There has been recent interest in showing that real networks, designed via optimization, may possess topological properties similar to those investigated by the Network Science community. This suggests that the Network Science community's view that topological properties such as scale-freeness are not the result of some immutable physical laws, but in fact intentional optimization. Recently, it was shown that stable graphs with an arbitrary degree sequence may result from a stability point of a collaborative game. In this paper, we present an integer program (IP) whose solutions yield graphs with a degree sequence, that is closest to a given degree sequence in the Manhattan metric. Stable graphs to the graph formation game and solutions to the IP in this paper, may be non-unique. We relate graphical solutions of the given IP to stable collaboration networks via the price of anarchy which we can calculate exactly as the result of another integer program.
A Scheduling Algorithm Based on Communication Delay for Wireless Network Control System
Jun Wang
2012-09-01
Full Text Available In this study, a scheduling algorithm based on communication delay is proposed. This scheduling algorithm can tolerate delay of periodic communication tasks in wireless network control system. It resolves real-time problem of periodic communication tasks in wireless network control system and partly reduces overtime phenomenon of periodic communication tasks caused by delay in wireless network. At the same time, the nonlinear programming model is built for solving scheduling timetable based on the proposed scheduling algorithm. Finally, the performance of the proposed scheduling algorithm is evaluated by an application example. The statistics results show that it is more effective than traditional scheduling algorithms in wireless network control system.
A Novel Message Scheduling Framework for Delay Tolerant Networks Routing
Elwhishi, Ahmed
2013-05-01
Multicopy routing strategies have been considered the most applicable approaches to achieve message delivery in Delay Tolerant Networks (DTNs). Epidemic routing and two-hop forwarding routing are two well-reported approaches for delay tolerant networks routing which allow multiple message replicas to be launched in order to increase message delivery ratio and/or reduce message delivery delay. This advantage, nonetheless, is at the expense of additional buffer space and bandwidth overhead. Thus, to achieve efficient utilization of network resources, it is important to come up with an effective message scheduling strategy to determine which messages should be forwarded and which should be dropped in case of buffer is full. This paper investigates a new message scheduling framework for epidemic and two-hop forwarding routing in DTNs, such that the forwarding/dropping decision can be made at a node during each contact for either optimal message delivery ratio or message delivery delay. Extensive simulation results show that the proposed message scheduling framework can achieve better performance than its counterparts.
ECS: efficient communication scheduling for underwater sensor networks.
Hong, Lu; Hong, Feng; Guo, Zhongwen; Li, Zhengbao
2011-01-01
TDMA protocols have attracted a lot of attention for underwater acoustic sensor networks (UWSNs), because of the unique characteristics of acoustic signal propagation such as great energy consumption in transmission, long propagation delay and long communication range. Previous TDMA protocols all allocated transmission time to nodes based on discrete time slots. This paper proposes an efficient continuous time scheduling TDMA protocol (ECS) for UWSNs, including the continuous time based and sender oriented conflict analysis model, the transmission moment allocation algorithm and the distributed topology maintenance algorithm. Simulation results confirm that ECS improves network throughput by 20% on average, compared to existing MAC protocols.
ECS: Efficient Communication Scheduling for Underwater Sensor Networks
Lu Hong
2011-03-01
Full Text Available TDMA protocols have attracted a lot of attention for underwater acoustic sensor networks (UWSNs, because of the unique characteristics of acoustic signal propagation such as great energy consumption in transmission, long propagation delay and long communication range. Previous TDMA protocols all allocated transmission time to nodes based on discrete time slots. This paper proposes an efficient continuous time scheduling TDMA protocol (ECS for UWSNs, including the continuous time based and sender oriented conflict analysis model, the transmission moment allocation algorithm and the distributed topology maintenance algorithm. Simulation results confirm that ECS improves network throughput by 20% on average, compared to existing MAC protocols.
Zhang, Tian; Chen, Wei; Han, Zhu; Cao, Zhigang
2013-01-01
In the paper, we consider delay-optimal charging scheduling of the electric vehicles (EVs) at a charging station with multiple charge points. The charging station is equipped with renewable energy generation devices and can also buy energy from power grid. The uncertainty of the EV arrival, the intermittence of the renewable energy, and the variation of the grid power price are taken into account and described as independent Markov processes. Meanwhile, the charging energy for each EV is rand...
Stock price change rate prediction by utilizing social network activities.
Deng, Shangkun; Mitsubuchi, Takashi; Sakurai, Akito
2014-01-01
Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL) and genetic algorithm (GA). MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques.
Stock Price Change Rate Prediction by Utilizing Social Network Activities
Mitsubuchi, Takashi; Sakurai, Akito
2014-01-01
Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS) before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL) and genetic algorithm (GA). MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques. PMID:24790586
Stock Price Change Rate Prediction by Utilizing Social Network Activities
Shangkun Deng
2014-01-01
Full Text Available Predicting stock price change rates for providing valuable information to investors is a challenging task. Individual participants may express their opinions in social network service (SNS before or after their transactions in the market; we hypothesize that stock price change rate is better predicted by a function of social network service activities and technical indicators than by a function of just stock market activities. The hypothesis is tested by accuracy of predictions as well as performance of simulated trading because success or failure of prediction is better measured by profits or losses the investors gain or suffer. In this paper, we propose a hybrid model that combines multiple kernel learning (MKL and genetic algorithm (GA. MKL is adopted to optimize the stock price change rate prediction models that are expressed in a multiple kernel linear function of different types of features extracted from different sources. GA is used to optimize the trading rules used in the simulated trading by fusing the return predictions and values of three well-known overbought and oversold technical indicators. Accumulated return and Sharpe ratio were used to test the goodness of performance of the simulated trading. Experimental results show that our proposed model performed better than other models including ones using state of the art techniques.
Dynamic Intelligent Feedback Scheduling in Networked Control Systems
Hui-ying Chen
2013-01-01
Full Text Available For the networked control system with limited bandwidth and flexible workload, a dynamic intelligent feedback scheduling strategy is proposed. Firstly, a monitor is used to acquire the current available network bandwidth. Then, the new available bandwidth in the next interval is predicted by using LS_SVM approach. At the same time, the dynamic performance indices of all control loops are obtained with a two-dimensional fuzzy logic modulator. Finally, the predicted network bandwidth is dynamically allocated by the bandwidth manager and the priority allocator in terms of the loops' dynamic performance indices. Simulation results show that the sampling periods and priorities of control loops are adjusted timely according to the network workload condition and the dynamic performance of control loops, which make the system running in the optimal state all the time.
Improving Dense Network Performance through Centralized Scheduling and Interference Coordination
Lopez, Victor Fernandez; Pedersen, Klaus I.; Alvarez, Beatriz Soret
2017-01-01
. Interference management at the receiver is achieved through the use of a Network-Assisted Interference Cancellation and Suppression (NAICS) receiver. In order to further boost the 5th percentile user data rates, the transmission rank at the interferers is selectively reduced by a centralized rank coordination......Dense network deployments comprising small cells pose a series of important challenges when it comes to achieving an efficient resource use and curbing inter-cell interference in the downlink. This article examines different techniques to treat these problems in a dynamic way, from the network...... and the receiver sides. As a network coordination scheme, we apply a centralized joint cell association and scheduling mechanism based on dynamic cell switching, by which users are not always served by the strongest perceived cell. The method simultaneously resultsin more balanced loads and increased performance...
Improved Space Surveillance Network (SSN) Scheduling using Artificial Intelligence Techniques
Stottler, D.
There are close to 20,000 cataloged manmade objects in space, the large majority of which are not active, functioning satellites. These are tracked by phased array and mechanical radars and ground and space-based optical telescopes, collectively known as the Space Surveillance Network (SSN). A better SSN schedule of observations could, using exactly the same legacy sensor resources, improve space catalog accuracy through more complementary tracking, provide better responsiveness to real-time changes, better track small debris in low earth orbit (LEO) through efficient use of applicable sensors, efficiently track deep space (DS) frequent revisit objects, handle increased numbers of objects and new types of sensors, and take advantage of future improved communication and control to globally optimize the SSN schedule. We have developed a scheduling algorithm that takes as input the space catalog and the associated covariance matrices and produces a globally optimized schedule for each sensor site as to what objects to observe and when. This algorithm is able to schedule more observations with the same sensor resources and have those observations be more complementary, in terms of the precision with which each orbit metric is known, to produce a satellite observation schedule that, when executed, minimizes the covariances across the entire space object catalog. If used operationally, the results would be significantly increased accuracy of the space catalog with fewer lost objects with the same set of sensor resources. This approach inherently can also trade-off fewer high priority tasks against more lower-priority tasks, when there is benefit in doing so. Currently the project has completed a prototyping and feasibility study, using open source data on the SSN's sensors, that showed significant reduction in orbit metric covariances. The algorithm techniques and results will be discussed along with future directions for the research.
Design of Hierarchical Ring Networks Using Branch-and-Price
Thomadsen, Tommy; Stidsen, Thomas K.
2004-01-01
We consider the problem of designing hierarchical two layer ring networks. The top layer consists of a federal-ring which establishes connection between a number of node disjoint metro-rings in a bottom layer. The objective is to minimize the costs of links in the network, taking both the fixed...... link establishment costs and the link capacity costs into account. The hierarchical two layer ring network design problem is solved in two stages: First the bottom layer, i.e. the metro-rings are designed, implicitly taking into account the capacity cost of the federal-ring. Then the federal......-ring is designed connecting the metro-rings, minimizing fixed link establishment costs of the federal-ring. A branch-and-price algorithm is presented for the design of the bottom layer and it is suggested that existing methods are used for the design of the federal-ring. Computational results are given...
MULTITASK SCHEDULING IN NETWORKED CONTROL SYSTEMS WITH APPLICATION TO LARGE SCALE VEHICLE CONTROL
YANG Liman; LI Yunhua
2007-01-01
Aiming at scheduling problems of networked control system (NCS) used to fulfill motion synthesis and cooperation control of the distributed multi-mechatronic systems, the differences of network scheduling and task scheduling are compared, and the mathematic description of task scheduling is presented. A performance index function of task scheduling of NCS according to task balance and traffic load matching principles is defined. According to this index, a static scheduling method is designed and implemented to controlling task set simulation of the DCY100 transportation vehicle. The simulation results are applied successfully to practical engineering in this case so as to validate the effectiveness of the proposed performance index and scheduling algorithm.
Optimal Workflow Scheduling in Critical Infrastructure Systems with Neural Networks
S. Vukmirović
2012-04-01
Full Text Available Critical infrastructure systems (CISs, such as power grids, transportation systems, communication networks and water systems are the backbone of a country’s national security and industrial prosperity. These CISs execute large numbers of workflows with very high resource requirements that can span through different systems and last for a long time. The proper functioning and synchronization of these workflows is essential since humanity’s well-being is connected to it. Because of this, the challenge of ensuring availability and reliability of these services in the face of a broad range of operating conditions is very complicated. This paper proposes an architecture which dynamically executes a scheduling algorithm using feedback about the current status of CIS nodes. Different artificial neural networks (ANNs were created in order to solve the scheduling problem. Their performances were compared and as the main result of this paper, an optimal ANN architecture for workflow scheduling in CISs is proposed. A case study is shown for a meter data management system with measurements from a power distribution management system in Serbia. Performance tests show that significant improvement of the overall execution time can be achieved by ANNs.
Opportunistic Scheduling in Heterogeneous Networks: Distributed Algorithms and System Capacity
Kampeas, Dor-Joseph; Gurewitz, Omer
2012-01-01
In this work, we design and analyze novel distributed scheduling algorithms for multi-user MIMO systems. In particular, we consider algorithms which do not require sending channel state information to a central processing unit, nor do they require communication between the users themselves, yet, we prove their performance closely approximates that of a centrally-controlled system, which is able to schedule the strongest user in each time-slot. Possible application include, but are not limited to, modern 4G networks such as 3GPP LTE, or random access protocols. The analysis is based on a novel application of the Point-Process approximation, enabling the examination of non-homogeneous cases, such as non-identically distributed users, or handling various QoS considerations, which to date had been open.
Energy Optimal Transmission Scheduling in Wireless Sensor Networks
Srivastava, Rahul
2010-01-01
One of the main issues in the design of sensor networks is energy efficient communication of time-critical data. Energy wastage can be caused by failed packet transmission attempts at each node due to channel dynamics and interference. Therefore transmission control techniques that are unaware of the channel dynamics can lead to suboptimal channel use patterns. In this paper we propose a transmission controller that utilizes different "grades" of channel side information to schedule packet transmissions in an optimal way, while meeting a deadline constraint for all packets waiting in the transmission queue. The wireless channel is modeled as a finite-state Markov channel. We are specifically interested in the case where the transmitter has low-grade channel side information that can be obtained based solely on the ACK/NAK sequence for the previous transmissions. Our scheduler is readily implementable and it is based on the dynamic programming solution to the finite-horizon transmission control problem. We als...
Hierarchical Ring Network Design Using Branch-and-Price
Thomadsen, Tommy; Stidsen, Thomas K.
2005-01-01
We consider the problem of designing hierarchical two layer ring networks. The top layer consists of a federal-ring which establishes connection between a number of node disjoint metro-rings in a bottom layer. The objective is to minimize the costs of links in the network, taking both the fixed l...... for jointly solving the clustering problem, the metro ring design problem and the routing problem. Computational results are given for networks with up to 36 nodes.......We consider the problem of designing hierarchical two layer ring networks. The top layer consists of a federal-ring which establishes connection between a number of node disjoint metro-rings in a bottom layer. The objective is to minimize the costs of links in the network, taking both the fixed...... link establishment costs and the link capacity costs into account. Hierarchical ring network design problems combines the following optimization problems: Clustering, hub selection, metro ring design, federal ring design and routing problems. In this paper a branch-and-price algorithm is presented...
Schedule for the update of CERN telephone network
2003-01-01
The continuation of ours tasks to update the network is scheduled as follows: May 12 Update of switch N7: Bldg. 39 and 40 We would like to remind you that disturbances or even interruptions of telephony services may occur from 18:30 to 00:00 on the above mentioned dates. CERN divisions are invited to avoid any change requests (set-ups, move or removals) of telephones and fax machines until 12th May. Should you need more details, please send us your questions by email to Standard.Telephone@cern.ch.
Pricing and Capacity Planning Problems in Energy Transmission Networks
Villumsen, Jonas Christoffer
Efficient use of energy is an increasingly important topic. Environmental and climate concerns as well as concerns for security of supply has made renewable energy sources a viable alternative to traditional energy sources. However, the intermittent nature of for instance wind and solar energy...... necessitates a radical change in the way we plan and operate energy systems. Another paradigm change which began in the 1990’s for electricity systems is that of deregulation. This has led to a variety of different market structures implemented across the world. In this thesis we discuss capacity planning...... and transmission pricing problems in energy transmission networks. Although the modelling framework applies to energy networks in general, most of the applications discussed concern the transmission of electricity. A number of the problems presented involves transmission switching, which allows the operator...
Saghari, Poorya; Kamath, P; Arbab, Vahid R; Haghi, Mahta; Willner, Alan E; Bannister, Joe A; Touch, Joe D
2007-12-10
We experimentally demonstrate a transmission scheduling algorithm to avoid congestion collapse in O-CDMA networks. Our result shows that transmission scheduling increases the performance of the system by orders of magnitude.
Collaborative Distributed Scheduling Approaches for Wireless Sensor Network
Zhidong Deng
2009-10-01
Full Text Available Energy constraints restrict the lifetime of wireless sensor networks (WSNs with battery-powered nodes, which poses great challenges for their large scale application. In this paper, we propose a family of collaborative distributed scheduling approaches (CDSAs based on the Markov process to reduce the energy consumption of a WSN. The family of CDSAs comprises of two approaches: a one-step collaborative distributed approach and a two-step collaborative distributed approach. The approaches enable nodes to learn the behavior information of its environment collaboratively and integrate sleep scheduling with transmission scheduling to reduce the energy consumption. We analyze the adaptability and practicality features of the CDSAs. The simulation results show that the two proposed approaches can effectively reduce nodes’ energy consumption. Some other characteristics of the CDSAs like buffer occupation and packet delay are also analyzed in this paper. We evaluate CDSAs extensively on a 15-node WSN testbed. The test results show that the CDSAs conserve the energy effectively and are feasible for real WSNs.
Multiresolution Network Temporal and Spatial Scheduling Model of Scenic Spot
Peng Ge
2013-01-01
Full Text Available Tourism is one of pillar industries of the world economy. Low-carbon tourism will be the mainstream direction of the scenic spots' development, and the ω path of low-carbon tourism development is to develop economy and protect environment simultaneously. However, as the tourists' quantity is increasing, the loads of scenic spots are out of control. And the instantaneous overload in some spots caused the image phenomenon of full capacity of the whole scenic spot. Therefore, realizing the real-time schedule becomes the primary purpose of scenic spot’s management. This paper divides the tourism distribution system into several logically related subsystems and constructs a temporal and spatial multiresolution network scheduling model according to the regularity of scenic spots’ overload phenomenon in time and space. It also defines dynamic distribution probability and equivalent dynamic demand to realize the real-time prediction. We define gravitational function between fields and takes it as the utility of schedule, after resolving the transportation model of each resolution, it achieves hierarchical balance between demand and capacity of the system. The last part of the paper analyzes the time complexity of constructing a multiresolution distribution system.
Scheduling for Emergency Tasks in Industrial Wireless Sensor Networks.
Xia, Changqing; Jin, Xi; Kong, Linghe; Zeng, Peng
2017-07-20
Wireless sensor networks (WSNs) are widely applied in industrial manufacturing systems. By means of centralized control, the real-time requirement and reliability can be provided by WSNs in industrial production. Furthermore, many approaches reserve resources for situations in which the controller cannot perform centralized resource allocation. The controller assigns these resources as it becomes aware of when and where accidents have occurred. However, the reserved resources are limited, and such incidents are low-probability events. In addition, resource reservation may not be effective since the controller does not know when and where accidents will actually occur. To address this issue, we improve the reliability of scheduling for emergency tasks by proposing a method based on a stealing mechanism. In our method, an emergency task is transmitted by stealing resources allocated to regular flows. The challenges addressed in our work are as follows: (1) emergencies occur only occasionally, but the industrial system must deliver the corresponding flows within their deadlines when they occur; (2) we wish to minimize the impact of emergency flows by reducing the number of stolen flows. The contributions of this work are two-fold: (1) we first define intersections and blocking as new characteristics of flows; and (2) we propose a series of distributed routing algorithms to improve the schedulability and to reduce the impact of emergency flows. We demonstrate that our scheduling algorithm and analysis approach are better than the existing ones by extensive simulations.
Hybrid scheduling mechanisms for Next-generation Passive Optical Networks based on network coding
Zhao, Jijun; Bai, Wei; Liu, Xin; Feng, Nan; Maier, Martin
2014-10-01
Network coding (NC) integrated into Passive Optical Networks (PONs) is regarded as a promising solution to achieve higher throughput and energy efficiency. To efficiently support multimedia traffic under this new transmission mode, novel NC-based hybrid scheduling mechanisms for Next-generation PONs (NG-PONs) including energy management, time slot management, resource allocation, and Quality-of-Service (QoS) scheduling are proposed in this paper. First, we design an energy-saving scheme that is based on Bidirectional Centric Scheduling (BCS) to reduce the energy consumption of both the Optical Line Terminal (OLT) and Optical Network Units (ONUs). Next, we propose an intra-ONU scheduling and an inter-ONU scheduling scheme, which takes NC into account to support service differentiation and QoS assurance. The presented simulation results show that BCS achieves higher energy efficiency under low traffic loads, clearly outperforming the alternative NC-based Upstream Centric Scheduling (UCS) scheme. Furthermore, BCS is shown to provide better QoS assurance.
Dynamic supply chain network design with capacity planning and multi-period pricing
Fattahi, Mohammad; Mahootchi, Masoud; Govindan, Kannan
2015-01-01
This paper addresses a new problem in designing and planning a multi-echelon and multi-product supply chain network over a multi-period horizon in which customer zones have price-sensitive demands. Based on price-demand relationships, a generic method is presented to obtain price levels...
Computation and evaluation of scheduled waiting time for railway networks
Landex, Alex
2010-01-01
Timetables are affected by scheduled waiting time (SWT) that prolongs the travel times for trains and thereby passengers. SWT occurs when a train hinders another train to run with the wanted speed. The SWT affects both the trains and the passengers in the trains. The passengers may be further aff...... timetable by analysing different timetables and/or plans of operation. This article presents methods to examine SWT by simulation for both trains and passengers in entire railway networks....... affected due to longer transfer times to other trains. SWT can be estimated analytically for a given timetable or by simulation of timetables and/or plans of operation. The simulation of SWT has the benefit that it is possible to examine the entire network. This makes it possible to improve the future...
FOREST HARVEST SCHEDULING PLAN INTEGRATED TO THE ROAD NETWORK
Pedro Henrique Belavenutti Martins da Silva
2016-03-01
Full Text Available In industrial forest plantations, the spatial distribution of management units for harvest scheduling influences the timber production cost and the non-renewable resources consumption, due to issues related to transport logistic. In this context, this research aimed to formulate Integer Linear Programming (ILP by means of the application of Floyd-Warshall network optimization algorithm to generate timber production routes, minimizing the production costs resulting from harvest activities and forest road maintenance. Then, scenarios were simulated considering different minimal harvest ages for Pinus spp. and Eucalyptus spp. stands. The planning horizon was five years with annual periodicity. The study area was 23,330 hectares of forests, located in Paraná state (southern Brazil. We compared the simulated scenarios according to the following parameter indicators: harvest income, building road network and the production unit cost. The decreasing of the minimal harvest age reduces the mean production of management units scheduled to be harvested, in other hand, it requires fewer roads to be built, and consequently increases the production unit cost. The solutions obtained by using ILP models presented an optimality gap lower than 0.1%.
Approximation for a scheduling problem with application in wireless networks
无
2010-01-01
A network of many sensors and a base station that are deployed over a region is considered.Each sensor has a transmission range,an interference range and a carrier sensing range,which are r,αr and βr,respectively.In this paper,we study the minimum latency conflict-aware many-to-one data aggregation scheduling problem:Given locations of sensors along with a base station,a subset of all sensors,and parameters r,α and β,to find a schedule in which the data of each sensor in the subset can be transmitted to the base station with no conflicts,such that the latency is minimized.We designe an algorithm based on maximal independent sets,which has a latency bound of(a+19b)R + Δb-a + 5 time slots,where a and b are two constant integers relying on α and β,Δ is the maximum degree of network topology,and R is the trivial lower bound of latency.Here Δ contributes to an additive factor instead of a multiplicative one,thus our algorithm is nearly a constant(a+19b)-ratio.
A Packet Scheduling Strategy in Sensor Networks with SGMH Protocol
Cherian, Mary
2011-01-01
Data communication in sensor networks can have timing constraints like end to end deadlines. If the deadlines are not met either a catastrophe can happen in hard real time systems or performance deterioration can occur in soft real time systems. In real time sensor networks, the recovery of data through retransmission should be minimized due to the stringent requirements on the worst case time delays. This paper presents the application of Stop and Go Multihop protocol (SGMH) at node level in wireless sensor networks for scheduling and hence to meet the hard real time routing requirements. SGMH is a distributed multihop packet delivery algorithm. The fractions of the total available bandwidth on each channel is assigned to several traffic classes by which the time it takes to traverse each of the hops from the source to the destination is bounded. It is based on the notion of time frames (Tfr). In sensor networks packets can have different delay guarantees. Multiple frame sizes can be assigned for different t...
Round robin based Secure-Aware Packet Scheduling in Wireless Networks
Arun Raj
2013-03-01
Full Text Available Packet scheduling algorithms enhances the packet delivery rate effectively in wireless networks; it helps to improve the quality of service of the wireless networks. Many algorithms had been deployed in the area of packet scheduling in wireless networks but less attention is paid to security. Some algorithms which offer security often compromise performances such as schedulability, this is not desirable. This performance problem will become worse when the system is under heavy load. In this paper we propose Round robin based Secure- Aware Packet Scheduling algorithm (RSAPS for wireless networks which focuses on secure scheduling. RSAPS is an adaptive algorithm which gives priority to scheduling when system is under heavy load. Under light load RSAPS provide maximum security for the incoming packets. Simulation has been performed using the proposed method and compared with existing algorithms SPSS and ISPAS. And it is found that RSAPS shows excellent scheduling quality holding the security levels.
The Price of Anarchy in Cooperative Network Creation Games
Demaine, Erik D; Mahini, Hamid; Zadimoghaddam, Morteza
2009-01-01
In general, the games are played on a host graph, where each node is a selfish independent agent (player) and each edge has a fixed link creation cost \\alpha. Together the agents create a network (a subgraph of the host graph) while selfishly minimizing the link creation costs plus the sum of the distances to all other players (usage cost). In this paper, we pursue two important facets of the network creation game. First, we study extensively a natural version of the game, called the cooperative model, where nodes can collaborate and share the cost of creating any edge in the host graph. We prove the first nontrivial bounds in this model, establishing that the price of anarchy is polylogarithmic in n for all values of α in complete host graphs. This bound is the first result of this type for any version of the network creation game; most previous general upper bounds are polynomial in n. Interestingly, we also show that equilibrium graphs have polylogarithmic diameter for the most natural range of \\a...
Stochastic project networks temporal analysis, scheduling and cost minimization
Neumann, Klaus
1990-01-01
Project planning, scheduling, and control are regularly used in business and the service sector of an economy to accomplish outcomes with limited resources under critical time constraints. To aid in solving these problems, network-based planning methods have been developed that now exist in a wide variety of forms, cf. Elmaghraby (1977) and Moder et al. (1983). The so-called "classical" project networks, which are used in the network techniques CPM and PERT and which represent acyclic weighted directed graphs, are able to describe only projects whose evolution in time is uniquely specified in advance. Here every event of the project is realized exactly once during a single project execution and it is not possible to return to activities previously carried out (that is, no feedback is permitted). Many practical projects, however, do not meet those conditions. Consider, for example, a production process where some parts produced by a machine may be poorly manufactured. If an inspection shows that a part does no...
Prediction Model of Weekly Retail Price for Eggs Based on Chaotic Neural Network
LI Zhe-min; CUI Li-guo; XU Shi-wei; WENG Ling-yun; DONG Xiao-xia; LI Gan-qiong; YU Hai-peng
2013-01-01
This paper establishes a short-term prediction model of weekly retail prices for eggs based on chaotic neural network with the weekly retail prices of eggs from January 2008 to December 2012 in China. In the process of determining the structure of the chaotic neural network, the number of input layer nodes of the network is calculated by reconstructing phase space and computing its saturated embedding dimension, and then the number of hidden layer nodes is estimated by trial and error. Finally, this model is applied to predict the retail prices of eggs and compared with ARIMA. The result shows that the chaotic neural network has better nonlinear iftting ability and higher precision in the prediction of weekly retail price of eggs. The empirical result also shows that the chaotic neural network can be widely used in the ifeld of short-term prediction of agricultural prices.
Opportunistic Channel Scheduling for Ad Hoc Networks with Queue Stability
Dong, Lei; Wang, Yongchao
2015-03-01
In this paper, a distributed opportunistic channel access strategy in ad hoc network is proposed. We consider the multiple sources contend for the transmission opportunity, the winner source decides to transmit or restart contention based on the current channel condition. Owing to real data assumption at all links, the decision still needs to consider the stability of the queues. We formulate the channel opportunistic scheduling as a constrained optimization problem which maximizes the system average throughput with the constraints that the queues of all links are stable. The proposed optimization model is solved by Lyapunov stability in queueing theory. The successive channel access problem is decoupled into single optimal stopping problem at every frame and solved with Lyapunov algorithm. The threshold for every frame is different, and it is derived based on the instantaneous queue information. Finally, computer simulations are conducted to demonstrate the validity of the proposed strategy.
New schedule for the update of CERN telephone network
2003-01-01
The continuation of ours tasks to update the network is scheduled as follows: Date Change type Affected area May 6 Update of switch N4 Meyrin Ouest May 8 Update of switch N6 Prévessin Site May 12 Update of switch N7 Building 39 and 40 We would like to remind you that disturbances or even interruptions of telephony services may occur from 18:30 to 00:00 on the above mentioned dates. CERN divisions are invited to avoid any change requests (set-ups, move or removals) of telephones and fax machines until 12th May. Should you need more details, please send us your questions by email to Standard.Telephone@cern.ch.
New schedule for the update of CERN telephone network
2003-01-01
The continuation of ours tasks to update the network is scheduled as follows: Date Change type Affected area April 28 Update of switch in LHC 1 LHC 1 Point April 29 Update of switch in LHC 5 LHC 5 Point May 6 Update of switch N4 Meyrin Ouest May 8 Update of switch N6 Prévessin Site May 12 Update of switch N7 Building 39 and 40 We would like to remind you that disturbances or even interruptions of telephony services may occur from 18:30 to 00:00 on the above mentioned dates. CERN divisions are invited to avoid any change requests (set-ups, move or removals) of telephones and fax machines until 12th May. Should you need more details, please send us your questions by email to Standard.Telephone@cern.ch.
Energy Efficient Greedy Link Scheduling and Power Control in wireless networks
Sridharan, Arun
2012-01-01
We consider the problem of joint link scheduling and power control for wireless networks with average transmission power constraints. Due to the high computational complexity of the optimal policies, we extend the class of greedy link scheduling policies to handle average power constraints. We develop a greedy link scheduling and power control scheme GECS, with provable performance guarantees. We show that the performance of our greedy scheduler can be characterized using the Local Pooling Factor (LPF) of a network graph, which has been previously used to characterize the stability of the Greedy Maximal Scheduling (GMS) policy for wireless networks. We also simulate the performance of GECS on wireless network, and compare its performance to another candidate greedy link scheduling and power control policy.
Building an Early Warning System for Crude Oil Price Using Neural Network
Wonho Song
2010-12-01
Full Text Available In this paper, a crisis index for the oil price shock is defined and a neural network model is specified for the prediction of the crisis index. This paper contributes to the literature in three ways. First, we build an early warning system for crude oil price. Although the oil price became one of the most important price index recently, no research efforts have been made to build an early warning system for crude oil price. Second, the neural network (NN model is used to construct the early warning sysIn this paper, a crisis index for the oil price shock is defined and a neural network model is specified for the prediction of the crisis index. This paper contributes to the literature in three ways. First, we build an early warning system for crude oil price. Although the oil price became one of the most important price index recently, no research efforts have been made to build an early warning system for crude oil price. Second, the neural network (NN model is used to construct the early warning system. Most early warning systems are built based on the signaling approach. In this paper, we show that the neural network models are more flexible and have greater potential as EWS than the signaling approach. Third, we allow the multi-level crisis index. Previous models allowed only a zero/one crisis index whereas our model permits as many levels as possible. With this new model, we try to answer whether the oil price collapse following the historical peak in 2008 was predictable. We compare the results from the NN model with those from the ordered probit (OP model, and show that the oil price crisis and the following crash were predictable by the NN model, but not by the OP model.
Dafny, Leemore S; Hendel, Igal; Marone, Victoria; Ody, Christopher
2017-09-01
Anecdotal reports and systematic research highlight the prevalence of narrow-network plans on the Affordable Care Act's health insurance Marketplaces. At the same time, Marketplace premiums in the period 2014-16 were much lower than projected by the Congressional Budget Office in 2009. Using detailed data on the breadth of both hospital and physician networks, we studied the prevalence of narrow networks and quantified the association between network breadth and premiums. Controlling for many potentially confounding factors, we found that a plan with narrow physician and hospital networks was 16 percent cheaper than a plan with broad networks for both, and that narrowing the breadth of just one type of network was associated with a 6-9 percent decrease in premiums. Narrow-network plans also have a sizable impact on federal outlays, as they depress the premium of the second-lowest-price silver plan, to which subsidy amounts are linked. Holding all else constant, we estimate that federal subsidies would have been 10.8 percent higher in 2014 had Marketplaces required all plans to offer broad provider networks. Narrow networks are a promising source of potential savings for other segments of the commercial insurance market. Project HOPE—The People-to-People Health Foundation, Inc.
Access pricing for transmission networks: Hypotheses and empirical evidence
Martoccia, Maria [Decision Technology Centre, London (United Kingdom)
1999-08-01
The sectors characterised by the use of transmission or transport networks as inputs of production (electricity, gas, telecommunications) have long been considered as natural monopolies. Thanks to the technological innovations which have modified the economics of production (as in electricity generation) or that have driven the development of high value added services (as in telecommunications), the boundaries of the old natural monopolies have been eroded by the presence of operators potentially able to compete in national and international markets. The objective is to delineate, by analysing the more significant theoretical contributions and some of the restructuring experiences of the sector in question, the possible regulatory solutions which, in the perspective of a `European market` for electricity, makes the management and the expansion of the transmission networks adequate for the `open access` of national electricity sectors. The analysis of some mature experiences, such as in Chile, Argentina, the UK and Norway, in the second section, will offer a useful support to this evaluation. The regulatory solution here adopted will be analysed, in particular, with reference to the two main problems outlined above: on the one hand, the problem of providing through prices the necessary information about the opportunities of using the transmission assets; and on the other hand, the problem of defining an efficient incentive mechanism for the behaviour of the monopolist (the owner of the transmission assets). Finally, by considering the limits found in the solutions explored in these models, we will try, in the third section, to delineate the evolution that the regulation of the analysed sectors could follow, in an attempt to make the optimal solution defined in the first section consistent with the imperfections of the real scenarios. (EHS)
Towards a Fair and Efficient Packet Scheduling Scheme in Inter-Flow Network Coding
Jin Wang
2014-11-01
Full Text Available Network coding techniques are usually applied upon network-layer protocols to improve throughput in wireless networks. In scenarios with multiple unicast sessions, fairness is also an important factor. Therefore, a network coding-aware packet-scheduling algorithm is required. A packet-scheduling algorithm determines which packet to send next from a node’s packet backlog. Existing protocols mostly employ a basic round-robin scheduling algorithm to give “equal” opportunities to different packet flows. In fact, this “equal”-opportunity scheduling is neither fair, nor efficient. This paper intends to accentuate the importance of a coding-aware scheduling scheme. With a good scheduling scheme, we can gain more control over the per-flow throughput and fairness. Specifically, we first formulate a static scheduling problem and propose an algorithm to find the optimal scheduling scheme. We then extend the technique to a dynamic setting and, later, to practical routing protocols. Results show that the algorithm is comparatively scalable, and it can improve the throughput gain when the network is not severely saturated. The fairness among flows is drastically improved as a result of this scheduling scheme.
Jia, Xiaoliang; An, Haizhong; Sun, Xiaoqi; Huang, Xuan; Gao, Xiangyun
2016-04-01
The globalization and regionalization of crude oil trade inevitably give rise to the difference of crude oil prices. The understanding of the pattern of the crude oil prices' mutual propagation is essential for analyzing the development of global oil trade. Previous research has focused mainly on the fuzzy long- or short-term one-to-one propagation of bivariate oil prices, generally ignoring various patterns of periodical multivariate propagation. This study presents a wavelet-based network approach to help uncover the multipath propagation of multivariable crude oil prices in a joint time-frequency period. The weekly oil spot prices of the OPEC member states from June 1999 to March 2011 are adopted as the sample data. First, we used wavelet analysis to find different subseries based on an optimal decomposing scale to describe the periodical feature of the original oil price time series. Second, a complex network model was constructed based on an optimal threshold selection to describe the structural feature of multivariable oil prices. Third, Bayesian network analysis (BNA) was conducted to find the probability causal relationship based on periodical structural features to describe the various patterns of periodical multivariable propagation. Finally, the significance of the leading and intermediary oil prices is discussed. These findings are beneficial for the implementation of periodical target-oriented pricing policies and investment strategies.
Dynamic Hierarchical Sleep Scheduling for Wireless Ad-Hoc Sensor Networks
Chih-Yu Wen
2009-05-01
Full Text Available This paper presents two scheduling management schemes for wireless sensor networks, which manage the sensors by utilizing the hierarchical network structure and allocate network resources efficiently. A local criterion is used to simultaneously establish the sensing coverage and connectivity such that dynamic cluster-based sleep scheduling can be achieved. The proposed schemes are simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithms provide efficient network power control and can achieve high scalability in wireless sensor networks.
An efficient schedule based data aggregation using node mobility for wireless sensor network
Dnyaneshwar, Mantri; Pawar, Pranav M.; Prasad, Neeli R.;
2014-01-01
In the Wireless Sensor Networks, (WSNs) a key challenge is to schedule the activities of the mobile node for improvement in throughput, energy consumption and delay. This paper proposes efficient schedule based data aggregation algorithm using node mobility (SDNM). It considers the cluster-based...... myopic and non-myopic scheduling scheme for conflict free schedule based on the current and next state. It uses TDMA as the MAC layer protocol and schedules the aggregated packets with consecutive slots. Simulation results show that, SDNM is energy efficient, has less delay as compared with state...
Visibility graph network analysis of natural gas price: The case of North American market
Sun, Mei; Wang, Yaqi; Gao, Cuixia
2016-11-01
Fluctuations in prices of natural gas significantly affect global economy. Therefore, the research on the characteristics of natural gas price fluctuations, turning points and its influencing cycle on the subsequent price series is of great significance. Global natural gas trade concentrates on three regional markets: the North American market, the European market and the Asia-Pacific market, with North America having the most developed natural gas financial market. In addition, perfect legal supervision and coordinated regulations make the North American market more open and more competitive. This paper focuses on the North American natural gas market specifically. The Henry Hub natural gas spot price time series is converted to a visibility graph network which provides a new direction for macro analysis of time series, and several indicators are investigated: degree and degree distribution, the average shortest path length and community structure. The internal mechanisms underlying price fluctuations are explored through the indicators. The results show that the natural gas prices visibility graph network (NGP-VGN) is of small-world and scale-free properties simultaneously. After random rearrangement of original price time series, the degree distribution of network becomes exponential distribution, different from the original ones. This means that, the original price time series is of long-range negative correlation fractal characteristic. In addition, nodes with large degree correspond to significant geopolitical or economic events. Communities correspond to time cycles in visibility graph network. The cycles of time series and the impact scope of hubs can be found by community structure partition.
An Integrated Control and Scheduling Optimization Method of Networked Control Systems
HE Jian-qiang; ZHANG Huan-chun; JING Ya-zhi
2004-01-01
Feedback control systems wherein the control loops are closed through a real-time network are called networked control systems (NCSs). The limitation of communication bandwidth results in transport delay, affects the property of real-time system, and degrades the performance of NCSs. An integrated control and scheduling optimization method using genetic algorithm is proposed in this paper.This method can synchronously optimize network scheduling and improve the performance of NCSs. To illustrate its effectiveness, an example is provided.
Capacity Limit, Link Scheduling and Power Control in Wireless Networks
Zhou, Shan
2013-01-01
The rapid advancement of wireless technology has instigated the broad deployment of wireless networks. Different types of networks have been developed, including wireless sensor networks, mobile ad hoc networks, wireless local area networks, and cellular networks. These networks have different structures and applications, and require different…
Dezong Zhao
2014-01-01
of multiple induction motors through a shared communication network. An integrated feedback scheduling algorithm is designed to allocate the optimal sampling period and priority to each control loop to optimize the global performance of a networked control system (NCS, while satisfying the constraints of stability and schedulability. A speed synchronization method is incorporated into the scheduling algorithm to improve the speed synchronization performance of multiple induction motors. The rational gain of the network speed controllers is calculated using the Lyapunov theorem and tuned online by fuzzy logic to guarantee the robustness against complicated variations on the communication network. Furthermore, a state predictor is designed to compensate the time delay which occurred in data transmission from the sensor to the controller, as a part of the networked controller. Simulation results support the effectiveness of the proposed control-and-scheduling codesign approach.
The Spectrum Sharing in Cognitive Radio Networks Based on Competitive Price Game
Y. B. Li
2012-09-01
Full Text Available The competitive price game model is used to analyze the spectrum sharing problem in the cognitive radio networks, and the spectrum sharing problem with the constraints of available spectrum resource from primary users is further discussed in this paper. The Rockafeller multiplier method is applied to deal with the constraints of available licensed spectrum resource, and the improved profits function is achieved, which can be used to measure the impact of shared spectrum price strategies on the system profit. However, in the competitive spectrum sharing problem of practical cognitive radio network, primary users have to determine price of the shared spectrum without the acknowledgement of the other primary user’s price strategies. Thus a fast gradient iterative calculation method of equilibrium price is proposed, only with acknowledgement of the price strategies of shared spectrum during last cycle. Through the adaptive iteration at the direction with largest gradient of improved profit function, the equilibrium price strategies can be achieved rapidly. It can also avoid the predefinition of adjustment factor according to the parameters of communication system in conventional linear iteration method. Simulation results show that the proposed competitive price spectrum sharing model can be applied in the cognitive radio networks with constraints of available licensed spectrum, and it has better convergence performance.
牛东晓; 刘达; 邢棉
2008-01-01
A combined model based on principal components analysis (PCA) and generalized regression neural network (GRNN) was adopted to forecast electricity price in day-ahead electricity market. PCA was applied to mine the main influence on day-ahead price, avoiding the strong correlation between the input factors that might influence electricity price, such as the load of the forecasting hour, other history loads and prices, weather and temperature; then GRNN was employed to forecast electricity price according to the main information extracted by PCA. To prove the efficiency of the combined model, a case from PJM (Pennsylvania-New Jersey-Maryland) day-ahead electricity market was evaluated. Compared to back-propagation (BP) neural network and standard GRNN, the combined method reduces the mean absolute percentage error about 3%.
Zhang Xizheng; Wang Yaonan
2009-01-01
Due to the mutual interference and sharing of wireless links in TDMA wireless sensor networks, conflicts will occur when data messages are transmitting between nodes. The broadcast scheduling problem (BSP) is aimed to schedule each node in different slot of fixed length frame at least once, and the objective of BSP is to seek for the optimal feasible solution, which has the shortest length of frame slots, as well as the maximum node transmission. A two-stage mixed algorithm based on a fuzzy Hopfield neural network is proposed to solve this BSP in wireless sensor network. In the first stage, a modified sequential vertex coloring algorithm is adopted to obtain a minimal TDMA frame length. In the second stage, the fuzzy Hopfield network is utilized to maximize the channel utilization ratio. Experimental results, obtained from the running on three benchmark graphs, show that the algorithm can achieve better performance with shorter frame length and higher channel utilizing ratio than other exiting BSP solutions.
Price-Based Resource Allocation for Spectrum-Sharing Femtocell Networks: A Stackelberg Game Approach
Kang, Xin; Motani, Mehul
2011-01-01
This paper investigates the price-based resource allocation strategies for the uplink transmission of a spectrum-sharing femtocell network, in which a central macrocell is underlaid with distributed femtocells, all operating over the same frequency band as the macrocell. Assuming that the macrocell base station (MBS) protects itself by pricing the interference from the femtocell users, a Stackelberg game is formulated to study the joint utility maximization of the macrocell and the femtocells subject to a maximum tolerable interference power constraint at the MBS. Especially, two practical femtocell channel models: sparsely deployed scenario for rural areas and densely deployed scenario for urban areas, are investigated. For each scenario, two pricing schemes: uniform pricing and non-uniform pricing, are proposed. Then, the Stackelberg equilibriums for these proposed games are studied, and an effective distributed interference price bargaining algorithm with guaranteed convergence is proposed for the uniform-...
Daily Crude Oil Price Forecasting Using Hybridizing Wavelet and Artificial Neural Network Model
Ani Shabri
2014-01-01
Full Text Available A new method based on integrating discrete wavelet transform and artificial neural networks (WANN model for daily crude oil price forecasting is proposed. The discrete Mallat wavelet transform is used to decompose the crude price series into one approximation series and some details series (DS. The new series obtained by adding the effective one approximation series and DS component is then used as input into the ANN model to forecast crude oil price. The relative performance of WANN model was compared to regular ANN model for crude oil forecasting at lead times of 1 day for two main crude oil price series, West Texas Intermediate (WTI and Brent crude oil spot prices. In both cases, WANN model was found to provide more accurate crude oil prices forecasts than individual ANN model.
Joint Network Coding and Opportunistic Scheduling for the Bidirectional Relay Channel
Shaqfeh, Mohammad
2013-05-27
In this paper, we consider a two-way communication system in which two users communicate with each other through an intermediate relay over block-fading channels. We investigate the optimal opportunistic scheduling scheme in order to maximize the long-term average transmission rate in the system assuming symmetric information flow between the two users. Based on the channel state information, the scheduler decides that either one of the users transmits to the relay, or the relay transmits to a single user or broadcasts to both users a combined version of the two users’ transmitted information by using linear network coding. We obtain the optimal scheduling scheme by using the Lagrangian dual problem. Furthermore, in order to characterize the gains of network coding and opportunistic scheduling, we compare the achievable rate of the system versus suboptimal schemes in which the gains of network coding and opportunistic scheduling are partially exploited.
Coordinated Workload Scheduling in Hierarchical Sensor Networks for Data Fusion Applications
Xiao-Lin Li; Jian-Nong Cao
2008-01-01
To minimize the execution time of a sensing task over a multi-hop hierarchical sensor network, we present acoordinated scheduling method following the divisible load scheduling paradigm. The proposed scheduling strategy builds on eliminating transmission collisions and idle gaps between two successive data transmissions. We consider a sensor network consisting of several clusters. In a cluster, after related raw data measured by source nodes are collected at the fusion node,in-network data aggregation is further considered. The scheduling strategies consist of two phases: intra-cluster scheduling and inter-cluster scheduling. Intra-cluster scheduling deals with assigning different fractions of a sensing workload among source nodes in each cluster; inter-cluster scheduling involves the distribution of fused data among all fusion nodes. Closed-form solutions to the problem of task scheduling are derived. Finally, numerical examples are presented to demonstrate the impacts of different system parameters such as the number of sensor nodes, measurement, communication, and processing speed, on the finish time and energy consumption.
Yu, Hao; Yan, Ying; Berger, Michael Stubert
2009-01-01
of Service (QoS) provisioning abilities, which guarantee end-to-end performances of voice, video and data traffic delivered over networks. This paper introduces a topology-based hierarchical scheduler scheme, which controls the incoming traffic at the edge of the network based on the network topology...
New Downlink Scheduling Framework for Hybrid Unicast and Multicast Traffic in WiMAX Networks
Rashid Karimi
2012-10-01
Full Text Available WiMAX networks based on IEEE 802.16 standard has expedited broadband wireless access surge in recent years. The traffic in these networks is identified in four types of class of service with different QoS requirements. Therefore, scheduling mechanism to manage these services in order to meet QoS requirements is a crucial fact and an important challenge. In this paper, for PMP mode of WiMAX networks, a two-level scheduling mechanism in MAC layer of Base Station (BS has been proposed. The proposed scheduling algorithm takes into account hybrid unicast and multicast downlink traffic including three classes of service: rtps, nrtps and BE. In the first level of this scheduling mechanism, we have used the scheduling algorithms WRR and FCFS to schedule the connections and in its second level, the PQ algorithm based on Aging method is used to manage and schedule the packets. The functionality of the proposed scheduling algorithm is compared with priority queuing (PQ algorithm. The resulting outcome of simulation shows that the proposed design has quite a better performance for Best Effort (BE service class. Furthermore the delay of the rtps class and total throughput of the network is increased noticeably
A Metaheuristic Scheduler for Time Division Multiplexed Network-on-Chip
Sørensen, Rasmus Bo; Sparsø, Jens; Pedersen, Mark Ruvald
2014-01-01
This paper presents a metaheuristic scheduler for inter-processor communication in multi-processor platforms using time division multiplexed (TDM) networks on chip (NOC). Compared to previous works, the scheduler handles a broader and more general class of platforms. Another contribution, which has...
ZHOU Peng; YAO JiangHe; PEI JiuLing
2009-01-01
Flow against pipeline leakage and the pipe network sudden burst pipe to pipeline leakage flow for the application objects,an energy-efficient real-time scheduling scheme is designed extensively used in pipeline leak monitoring.The proposed scheme can adaptively adjust the network rate in real-time and reduce the cell loss rate,so that it can efficiently avoid the traffic congestion.The recent evolution of wireless sensor networks has yielded a demand to improve energy-efficient scheduling algorithms and energy-efficient medium access protocols.This paper proposes an energy-efficient real-time scheduling scheme that reduces power consumption and network errors on pipeline flux leak monitoring networks.The proposed scheme is based on a dynamic modulation scaling scheme which can scale the number of bits per symbol and a switching scheme which can swap the polling schedule between channels.Built on top of EDF scheduling policy,the proposed scheme enhances the power performance without violating the constraints of real-time streams.The simulation results show that the proposed scheme enhances fault-tolerance and reduces power consumption.Furthermore,that Network congestion avoidance strategy with an energy-efficient real-time scheduling scheme can efficiently improve the bandwidth utilization,TCP friendliness and reduce the packet drop rate in pipeline flux leak monitoring networks.
Variable Quantum Deficit Round Robin Scheduling for Improved Fairness In Multihop Networks
B.Suresh
2011-02-01
Full Text Available To increase the coverage area, Multichip WiMAX networks are particularly useful without the need to deploy expensive base stations. One of the most common variants in Multihop WiMAX is the Wireless Mesh Networks.Scheduling algorithms for WiMAX has been a topic of interest for a long time since the very inception of WiMAX networks. Though a lot of literature is available for scheduling in point–tomultipoint (PMP networks, relatively less emphasis has been on scheduling in Multihop networks. One problem inherent with Multihop networks is unfairness between users with different service class types. This problem is even worse with real time bursty traffic. This necessitates the need for a scheduling algorithm that allows a fair share of resources among the users. In this work, we propose a vqDRR based scheduling mechanism that provides Quality of Service while at the same time maintaining fairness among users in a Multi-hop networks. We compare the performance of the proposed algorithm with the fair distributed credit based scheduler in terms of latency, throughput utilization and fairness.
Sensor scheduling strategies for fault isolation in networked control system.
Sid, M A
2015-01-01
A framework for the joint design of sensor scheduling and fault isolation is proposed. First, the synthesis of fault isolation filter and the communication sequence that ensures the isolability of fault is given. The proposed filter can be viewed as a special structure of the traditional Kalman filter. Several sensor scheduling strategies are proposed in order to ensure the minimization of the noise effect on the generated residual. A numerical example illustrates the effectiveness of the proposed approach.
A Metaheuristic Scheduler for Time Division Multiplexed Network-on-Chip
Sørensen, Rasmus Bo; Sparsø, Jens; Pedersen, Mark Ruvald
This report presents a metaheuristic scheduler for inter-processor communication in multi-core platforms using time division multiplexed (TDM) networks on chip (NOC). Input to the scheduler is a specification of the target multi-core platform and a specification of the application. Compared...... that this is possible with only negligible impact on the schedule period. We evaluate the scheduler with seven different applications from the MCSL NOC benchmark suite. We observe that the metaheuristics perform better than the greedy solution. In the special case of all-to-all communication with equal bandwidths...
YAN JiHong(闫纪红); WU Cheng(吴澄)
2003-01-01
Scheduling activities in concurrent product development process is of great sig-nificance to shorten development lead time and minimize the cost. Moreover, it can eliminate theunnecessary redesign periods and guarantee that serial activities can be executed as concurrently aspossible. This paper presents a constraint satisfaction neural network and heuristic combined ap-proach for concurrent activities scheduling. In the combined approach, the neural network is usedto obtain a feasible starting time of all the activities based on sequence constraints, the heuris-tic algorithm is used to obtain a feasible solution of the scheduling problem based on resourceconstraints. The feasible scheduling solution is obtained by a gradient optimization function. Sim-ulations have shown that the proposed combined approach is efficient and feasible with respect toconcurrent activities scheduling.
AREA-EFFICIENT DESIGN OF SCHEDULER FOR ROUTING NODE OF NETWORK-ON-CHIP
Rehan Maroofi
2011-10-01
Full Text Available Traditional System-on-Chip (SoC design employed shared buses for data transfer among varioussubsystems. As SoCs become more complex involving a larger number of subsystems, traditional busbasedarchitecture is giving way to a new paradigm for on-chip communication. This paradigm is calledNetwork-on-Chip (NoC. A communication network of point-to-point links and routing switches is used tofacilitate communication between subsystems. The routing switch proposed in this paper consists of fourcomponents, namely the input ports, output ports, switching fabric, and scheduler. The scheduler design isdescribed in this paper. The function of the scheduler is to arbitrate between requests by data packets foruse of the switching fabric. The scheduler uses an improved round robin based arbitration algorithm. Dueto the symmetric structure of the scheduler, an area-efficient design is proposed by folding the scheduleronto itself, thereby reducing its area roughly by 50%.
SURVEYING BEST SUITABLE SCHEDULING ALGORITHM FOR WIMAX- WI-FI INTEGRATED HETEROGENEOUS NETWORK
Poulomi Das
2013-02-01
Full Text Available To provide uninterrupted service to all subscribers in a wireless network, we need to incorporate a low cost, flexible Heterogeneous network which will be able to link with any kind of network for efficient spectrum utilization, hence improved system capacity. In this connection, Wi-Fi/ Wi MAX integrated network seems to be an ideal solution as it is able to provide easy deployment, high speed data rate and wide range coverage with high throughput, low end to end delay, flat and low jitter. Wi-Fi/ WiMAX integrated network provides Quality of Service (QoS that can support all kinds of real-time application in wireless networks that includes priority scheduling and queuing for bandwidth allocation that is based on traffic scheduling algorithms within wireless networks. In this paper, we have designed a Wi-Fi/ WiMAX integrated network and analyze the performance of different scheduling algorithms for that integrated network and highlight our findings on the scheduling algorithm which will give the best performance for a heterogeneous network.
Constant Price of Anarchy in Network Creation Games via Public Service Advertising
Demaine, Erik D.; Zadimoghaddam, Morteza
Network creation games have been studied in many different settings recently. These games are motivated by social networks in which selfish agents want to construct a connection graph among themselves. Each node wants to minimize its average or maximum distance to the others, without paying much to construct the network. Many generalizations have been considered, including non-uniform interests between nodes, general graphs of allowable edges, bounded budget agents, etc. In all of these settings, there is no known constant bound on the price of anarchy. In fact, in many cases, the price of anarchy can be very large, namely, a constant power of the number of agents. This means that we have no control on the behavior of network when agents act selfishly. On the other hand, the price of stability in all these models is constant, which means that there is chance that agents act selfishly and we end up with a reasonable social cost.
Alam, Muhammad Mahbub; Hamid, Md. Abdul; Razzaque, Md. Abdur; Hong, Choong Seon
Broadband wireless access networks are promising technology for providing better end user services. For such networks, designing a scheduling algorithm that fairly allocates the available bandwidth to the end users and maximizes the overall network throughput is a challenging task. In this paper, we develop a centralized fair scheduling algorithm for IEEE 802.16 mesh networks that exploits the spatio-temporal bandwidth reuse to further enhance the network throughput. The proposed mechanism reduces the length of a transmission round by increasing the number of non-contending links that can be scheduled simultaneously. We also propose a greedy algorithm that runs in polynomial time. Performance of the proposed algorithms is evaluated by extensive simulations. Results show that our algorithms achieve higher throughput than that of the existing ones and reduce the computational complexity.
Logical Link Control and Channel Scheduling for Multichannel Underwater Sensor Networks
Jun Li
2012-08-01
Full Text Available With recent developments in terrestrial wireless networks and advances in acoustic communications, multichannel technologies have been proposed to be used in underwater networks to increase data transmission rate over bandwidth-limited underwater channels. Due to high bit error rates in underwater networks, an efficient error control technique is critical in the logical link control (LLC sublayer to establish reliable data communications over intrinsically unreliable underwater channels. In this paper, we propose a novel protocol stack architecture featuring cross-layer design of LLC sublayer and more efficient packetto- channel scheduling for multichannel underwater sensor networks. In the proposed stack architecture, a selective-repeat automatic repeat request (SR-ARQ based error control protocol is combined with a dynamic channel scheduling policy at the LLC sublayer. The dynamic channel scheduling policy uses the channel state information provided via cross-layer design. It is demonstrated that the proposed protocol stack architecture leads to more efficient transmission of multiple packets over parallel channels. Simulation studies are conducted to evaluate the packet delay performance of the proposed cross-layer protocol stack architecture with two different scheduling policies: the proposed dynamic channel scheduling and a static channel scheduling. Simulation results show that the dynamic channel scheduling used in the cross-layer protocol stack outperforms the static channel scheduling. It is observed that, when the dynamic channel scheduling is used, the number of parallel channels has only an insignificant impact on the average packet delay. This confirms that underwater sensor networks will benefit from the use of multichannel communications.
Virtual topology-based traffic scheduling algorithm for slotted optical networks
Qin, Yang; Xue, Daojun; Kheong Siew, Chee
2007-02-01
We consider the scheduling problem in a new slotted optical network called TWIN. The TWIN architecture possesses interesting properties, which may offer solutions for next-generation optical networks. Besides, TWIN has the ability to support quality of service (QoS) by controlling two important parameters: queueing delay and delay variance. However, to the best of our knowledge, the existing scheduling algorithms in TWIN focused mainly on maximizing the throughput and ignored the consideration of QoS. We formulate the scheduling problem into an integer linear programming problem and propose a heuristic--virtual topology-based dynamic scheduling (VTBDS) algorithm to solve it fast and efficiently. Besides, we derive an analytical model for TWIN and investigate the performance of VTBDS in it. By means of simulations, we demonstrate that our model approximates the TWIN network very well, and VTBDS incurs smaller queueing delay and delay variance, which are advantageous for guaranteeing better QoS.
Fuzzy Networked Control Systems Design Considering Scheduling Restrictions
H. Benítez-Pérez
2012-01-01
known a priory but from a dynamic real-time behavior. To do so, the use of priority dynamic Priority exchange scheduling is performed. The objective of this paper is to show a way to tackle multiple time delays that are bounded and the dynamic response from real-time scheduling approximation. The related control law is designed considering fuzzy logic approximation for nonlinear time delays coupling, where the main advantage is the integration of this behavior through extended state space representation keeping certain linear and bounded behavior and leading to a stable situation during events presentation by guaranteeing stability through Lyapunov.
Hybrid Clustering-GWO-NARX neural network technique in predicting stock price
Das, Debashish; Safa Sadiq, Ali; Mirjalili, Seyedali; Noraziah, A.
2017-09-01
Prediction of stock price is one of the most challenging tasks due to nonlinear nature of the stock data. Though numerous attempts have been made to predict the stock price by applying various techniques, yet the predicted price is not always accurate and even the error rate is high to some extent. Consequently, this paper endeavours to determine an efficient stock prediction strategy by implementing a combinatorial method of Grey Wolf Optimizer (GWO), Clustering and Non Linear Autoregressive Exogenous (NARX) Technique. The study uses stock data from prominent stock market i.e. New York Stock Exchange (NYSE), NASDAQ and emerging stock market i.e. Malaysian Stock Market (Bursa Malaysia), Dhaka Stock Exchange (DSE). It applies K-means clustering algorithm to determine the most promising cluster, then MGWO is used to determine the classification rate and finally the stock price is predicted by applying NARX neural network algorithm. The prediction performance gained through experimentation is compared and assessed to guide the investors in making investment decision. The result through this technique is indeed promising as it has shown almost precise prediction and improved error rate. We have applied the hybrid Clustering-GWO-NARX neural network technique in predicting stock price. We intend to work with the effect of various factors in stock price movement and selection of parameters. We will further investigate the influence of company news either positive or negative in stock price movement. We would be also interested to predict the Stock indices.
Prediction and Research on Vegetable Price Based on Genetic Algorithm and Neural Network Model
2011-01-01
Considering the complexity of vegetables price forecast,the prediction model of vegetables price was set up by applying the neural network based on genetic algorithm and using the characteristics of genetic algorithm and neural work.Taking mushrooms as an example,the parameters of the model are analyzed through experiment.In the end,the results of genetic algorithm and BP neural network are compared.The results show that the absolute error of prediction data is in the scale of 10%;in the scope that the absolute error in the prediction data is in the scope of 20% and 15%.The accuracy of genetic algorithm based on neutral network is higher than the BP neutral network model,especially the absolute error of prediction data is within the scope of 20%.The accuracy of genetic algorithm based on neural network is obviously better than BP neural network model,which represents the favorable generalization capability of the model.
Scheduled Collision Avoidance in wireless sensor network using Zigbee
Dnyaneshwar, Mantri; Prasad, Neeli R.; Prasad, Ramjee
2014-01-01
. This paper proposes the Schedule based Collision Avoidance (SCA) algorithm for finding the tradeoff between reliability and energy efficiency by fusion of CSMA/CA and TDMA techniques in Zigbee/ IEEE802.15.4. It uses the multi-path data propagation for collision avoidance and effective utilization...
Learning Search Control Knowledge for Deep Space Network Scheduling
Gratch, Jonathan; Chien, Steve; DeJong, Gerald
1993-01-01
While the general class of most scheduling problems is NP-hard in worst-case complexity, in practice, for specific distributions of problems and constraints, domain-specific solutions have been shown to perform in much better than exponential time.
Analysis of full-duplex relay networks with opportunistic scheduling
Lei Shao
2015-05-01
Full Text Available This Letter addresses a two-hop decode-and-forward relay system with full-duplex relaying and opportunistic scheduling. Exact expressions for outage probability, average capacity and symbol error rate are presented in an independent identically distributed Rayleigh fading environment. Numerical and simulated results show the validity of the analytical results.
QoS Differentiated and Fair Packet Scheduling in Broadband Wireless Access Networks
Zhang Yan
2009-01-01
Full Text Available This paper studies the packet scheduling problem in Broadband Wireless Access (BWA networks. The key difficulties of the BWA scheduling problem lie in the high variability of wireless channel capacity and the unknown model of packet arrival process. It is difficult for traditional heuristic scheduling algorithms to handle the situation and guarantee satisfying performance in BWA networks. In this paper, we introduce learning-based approach for a better solution. Specifically, we formulate the packet scheduling problem as an average cost Semi-Markov Decision Process (SMDP. Then, we solve the SMDP by using reinforcement learning. A feature-based linear approximation and the Temporal-Difference learning technique are employed to produce a near optimal solution of the corresponding SMDP problem. The proposed algorithm, called Reinforcement Learning Scheduling (RLS, has in-built capability of self-training. It is able to adaptively and timely regulate its scheduling policy according to the instantaneous network conditions. Simulation results indicate that RLS outperforms two classical scheduling algorithms and simultaneously considers: (i effective QoS differentiation, (ii high bandwidth utilization, and (iii both short-term and long-term fairness.
LI Hongbo; SUN Zengqi; CHEN Badong; LIU Huaping
2008-01-01
The use of communication networks in control loops has gained increasing attention in recent years due to its advantages and flexible applications. The network quality-of-service (QoS) in those so-called networked control systems always fluctuates due to changes of the traffic load and available network resources. This paper presents an intelligent scheduling controller design approach for a class of NCSs to handle network QoS variations. The sampling period and control parameters in the controller are simultane-ously scheduled to compensate for the network QoS variations. The estimation of distribution algorithm is used to optimize the sampling period and control parameters for better performance. Compared with exist-ing networked control methods, the controller has better ability to compensate for the network QoS varia-tions and to balance network loads. Simulation results show that the plant setting time with the intelligent scheduling controller is reduced by about 64.0% for the medium network load and 49.1% for high network load and demonstrate the effectiveness of the proposed approaches.
Research on fault-tolerant control of networked control systems based on information scheduling
Huo Zhihong; Zhang Zhixue; Fang Huajing
2008-01-01
A kind of networked control system is studied; the networked control system with noise disturbance is modeled based on information scheduling and control co-design.Augmented state matrix analysis method is introduced,and robust fault-tolerant control problem of networked control systems with noise disturbance under actuator failures is studied.The parametric expression of the controller under actuator failures is given.Furthermore,the result is analyzed by simulation tests,which not only satisfies the networked control systems stability,but also decreases the data information number in network channel and makes full use of the network resources.
A Greedy link scheduler for Wireless Networks having Gaussian Broadcast and Multiple Access Channels
Sridharan, Arun; Uysal-Biyikoglu, Elif
2010-01-01
Information theoretic Broadcast Channels (BC) and Multiple Access Channels (MAC) enable a single node to transmit data simultaneously to multiple nodes, and multiple nodes to transmit data simultaneously to a single node respectively. In this paper, we address the problem of link scheduling in multihop wireless networks containing nodes with BC and MAC capabilities. We first propose an interference model that extends protocol interference models, originally designed for point to point channels, to include the possibility of BC and MAC. Due to the high complexity of optimal link schedulers, we introduce the Multiuser Greedy Maximum Weight algorithm for link scheduling in multihop wireless networks containing BCs and MACs. Given a network graph, we develop new local pooling conditions and show that the performance of our algorithm can be fully characterized using the associated parameter, the multiuser local pooling factor. We provide examples of some network graphs, on which we apply local pooling conditions a...
Minimum-Time Aggregation Scheduling in Duty-Cycled Wireless Sensor Networks
Bo Yu; Jian-Zhong Li
2011-01-01
Aggregation is an important and commonplace operation in wireless sensor networks.Due to wireless interferences,aggregation in wireless sensor networks often suffers fTom packet collisions.In order to solve the collision problem,aggregation scheduling is extensively researched in recent years.In many sensor network applications such as real-time monitoring,aggregation time is the most concerned performance.This paper considers the minimum-time aggregation scheduling problem in duty-cycled wireless sensor networks for the first time.We show that this problem is NP-hard and present an approximation algorithm based on connected dominating set.The theoretical analysis shows that the proposed algorithm is a nearly-constant approximation.Simulation shows that the scheduling algorithm has a good performance.
Fuzzy-Based Dynamic Distributed Queue Scheduling for Packet Switched Networks
Chollette C.Chude-Olisah; Uche A.K.Chude-Okonkwo; Kamalrulnizam A.Balar; Ghazali Sulong
2013-01-01
Addressing the problem of queue scheduling for the packet-switched system is a vital aspect of congestion control.In this paper,the fuzzy logic based decision method is adopted for queue scheduling in order to enforce some level of control for traffic of different quality of service requirements using predetermined values.The fuzzy scheduler proposed in this paper takes into account the dynamic nature of the Internet traffic with respect to its time-varying packet arrival process that affects the network states and performance.Three queues are defined,viz low,medium and high priority queues.The choice of prioritizing packets influences how queues are served.The fuzzy scheduler not only utilizes queue priority in the queue scheduling scheme,but also considers packet drop susceptibility and queue limit.Through simulation it is shown that the fuzzy scheduler is more appropriate for the dynamic nature of Internet traffic in a packet-switched system as compared with some existing queue scheduling methods.Results show that the scheduling strategy of the proposed fuzzy scheduler reduces packet drop,provides good link utilization and minimizes queue delay as compared with the priority queuing (PQ),first-in-first-out (FIFO),and weighted fair queuing (WFQ).
无
2002-01-01
A high-speed and effective packet scheduling method is crucial to the performance of Gigabit routers. The paper studies the variable-length packet scheduling problem in Gigabit router with crossbar switch fabric and input queuing, and a scheduling method based on neural network is proposed. For the proposed method, a scheduling system structure fit for the variable-length packet case is presented first, then some rules for scheduling are given, At last, an optimal scheduling method using Hopfield neural network is proposed based on the rules. Furthermore, the paper discusses that the proposed method can be realized by hardware circuit. The simulation result shows the effectiveness of the proposed method.
程瑞; 徐得潜; 韩慧; 郑启萍; 杨建
2013-01-01
The rational water delivery schedule is an important way to reduce water engineering cost, and the appropriate comparative method is the premise of optimization schedule. Currently, water delivery schedule selection is mainly based on the initial investment cost comparison. It is simple, but did not consider the value of the power cost of pipe network, peak-valley electricity price and the other factors. With the rise of electricity prices, power cost is a growing proportion in the total costs. As peak-valley electricity price carrying out, transmitting water in the time of the lower electrovalency can reduce power cost, but water pipeline and storage structure put forward new requirements. The cost for the filling and emptying system optimization will be between capital cost and power cost optimization. Therefore, this paper presents the annual cost method based on peak-valley electricity price as a new method of comparison, considering the initial capital investment costs, the power cost during the network operation, depreciation and overhaul costs and the other factors. This paper presents three water delivery schedules: 1) transmitting water uniformly in 24 hours by two parallel pipes;2) transmitting water uniformly in 24 hours by one pipe with a reservoir in the end;3) transmitting water uniformly in the time of lower electrovalency by one pipe with a reservoir in the end. Using the minimum annual cost of the water delivery as the objective function, and the reliability of water delivery system as the constraint condition, we find out the minimum annual cost of the three water delivery schedules. The results of power costs have a large proportion in annual cost, the price of electricity has an important effect on the water transmission selection. As peak-valley electricity price carrying out, rational water transmitting in time of lower electrovalency can reduce power cost.% 选择合理的输水方案是降低输水工程费用的重要途径，合适
An Efficient Multitask Scheduling Model for Wireless Sensor Networks
Hongsheng Yin
2014-01-01
Full Text Available The sensor nodes of multitask wireless network are constrained in performance-driven computation. Theoretical studies on the data processing model of wireless sensor nodes suggest satisfying the requirements of high qualities of service (QoS of multiple application networks, thus improving the efficiency of network. In this paper, we present the priority based data processing model for multitask sensor nodes in the architecture of multitask wireless sensor network. The proposed model is deduced with the M/M/1 queuing model based on the queuing theory where the average delay of data packets passing by sensor nodes is estimated. The model is validated with the real data from the Huoerxinhe Coal Mine. By applying the proposed priority based data processing model in the multitask wireless sensor network, the average delay of data packets in a sensor nodes is reduced nearly to 50%. The simulation results show that the proposed model can improve the throughput of network efficiently.
Ohyun Jo
2016-01-01
Full Text Available We introduce the concept of self-organizing VCN (virtual cell network. Here self-organizing VCN topology for efficient operation will be configured, and the functions of the each element will be defined. Also, the operation scenarios of VCN will be described. Then, we propose an efficient scheduling algorithm that considers the asymmetry of interference between downlink and uplink to mitigate intercell interference with little computing overhead. The basic concept is to construct scheduling groups that consist of several users. Each user in a scheduling group is affiliated with a different cell. Then, the intercell groups are managed efficiently in the proposed VCNs. There is no need for the exchange of a lot of information among base stations to schedule the users over the entire network.
Interference Aware Routing for Minimum Frame Length Schedules in Wireless Mesh Networks
Katerina Papadaki
2008-10-01
Full Text Available The focus of this paper is on routing in wireless mesh networks (WMNs that results in spatial TDMA (STDMA schedules with minimum frame length. In particular, the emphasis is on spanning tree construction; and we formulate the joint routing, power control, and scheduling problem as a mixedinteger linear program (MILP. Since this is an Ã°ÂÂ’Â©Ã°ÂÂ’Â«-complete problem, we propose a low-complexity iterative pruning-based routing scheme that utilizes scheduling information to construct the spanning tree. A randomized version of this scheme is also discussed and numerical investigations reveal that the proposed iterative pruning algorithms outperform previously proposed routing schemes that aim to minimize the transmitted power or interference produced in the network without explicitly taking into account scheduling decisions.
Optimal residential smart appliances scheduling considering distribution network constraints
Kim, Yu-Ree; Kim, Min-Jeong; Park, Yong-Gi; Roh, Jae-Hyung; Park, Jong-Bae; Son, Sung-Yong
2016-01-01
As smart appliances (SAs) are more widely adopted within distribution networks, residential consumers can contribute to electricity market operations with demand response resources and reduce their electricity bill...
无
2011-01-01
Reliability and real-time requirements bring new challenges to the energy-constrained wireless sensor networks, especially to the industrial wireless sensor networks. Meanwhile, the capacity of wireless sensor networks can be substantially increased by operating on multiple nonoverlapping channels. In this context, new routing, scheduling, and power control algorithms are required to achieve reliable and real-time communications and to fully utilize the increased bandwidth in multichannel wireless sensor ne...
Bicriteria Optimization in Wireless Sensor Networks: Link Scheduling and Energy Consumption
Jian Chen
2015-01-01
Full Text Available Link scheduling is important for reliable data communication in wireless sensor networks. Previous works mainly focus on how to find the minimum scheduling length but ignore the impact of energy consumption. In this paper, we integrate them together and solve them by multiobjective genetic algorithms. As a contribution, by jointly modeling the route selection and interference-free link scheduling problem, we give a systematical analysis on the relationship between link scheduling and energy consumption. Considering the specific many-to-one communication nature of WSNs, we propose a novel link scheduling scheme based on NSGA-II (Non-dominated Sorting Genetic Algorithm II. Our approach aims to search the optimal routing tree which satisfies the minimum scheduling length and energy consumption for wireless sensor networks. To achieve this goal, the solution representation based on the routing tree, the genetic operations including tree based recombination and mutation, and the fitness evaluation based on heuristic link scheduling algorithm are well designed. Extensive simulations demonstrate that our algorithm can quickly converge to the Pareto optimal solution between the two performance metrics.
An Integer Linear Programming Solution to the Telescope Network Scheduling Problem
Lampoudi, Sotiria; Eastman, Jason
2015-01-01
Telescope networks are gaining traction due to their promise of higher resource utilization than single telescopes and as enablers of novel astronomical observation modes. However, as telescope network sizes increase, the possibility of scheduling them completely or even semi-manually disappears. In an earlier paper, a step towards software telescope scheduling was made with the specification of the Reservation formalism, through the use of which astronomers can express their complex observation needs and preferences. In this paper we build on that work. We present a solution to the discretized version of the problem of scheduling a telescope network. We derive a solvable integer linear programming (ILP) model based on the Reservation formalism. We show computational results verifying its correctness, and confirm that our Gurobi-based implementation can address problems of realistic size. Finally, we extend the ILP model to also handle the novel observation requests that can be specified using the more advanc...
Chih-Chiang Lin
2010-01-01
Full Text Available The broadcast scheduling problem (BSP in packet radio networks is a well-known NP-complete combinatorial optimization problem. The broadcast scheduling avoids packet collisions by allowing only one node transmission in each collision domain of a time division multiple access (TDMA network. It also improves the transmission utilization by assigning one transmission time slot to one or more nodes; thus, each node transmits at least once in each time frame. An optimum transmission schedule could minimize the length of a time frame while minimizing the number of idle nodes. In this paper, we propose a new iterated local search (ILS algorithm that consists of two special perturbation and local search operators to solve the BSPs. Computational experiments are applied to benchmark data sets and randomly generated problem instances. The experimental results show that our ILS approach is effective in solving the problems with only a few runtimes, even for very large networks with 2,500 nodes.
The Asymptotic Limits of Interference in Multicell Networks with Channel Aware Scheduling
de Kerret, P
2011-01-01
Interference is emerging as a fundamental bottleneck in many important wireless communication scenarios, including dense cellular networks and cognitive networks with spectrum sharing by multiple service providers. Although multipleantenna (MIMO) signal processing is known to offer useful degrees of freedom to cancel interference, extreme-value theoretic analysis recently showed that, even in the absence of MIMO processing, the scaling law of the capacity in the number of users for a multi-cell network with and without inter-cell interference was asymptotically identical provided a simple signal to noise and interference ratio (SINR) maximizing scheduler is exploited. This suggests that scheduling can help reduce inter-cell interference substantially, thus possibly limiting the need for multiple-antenna processing. However, the convergence limits of interference after scheduling in a multi-cell setting are not yet identified. In this paper1 we analyze such limits theoretically. We consider channel statistics ...
On the Integrated Job Scheduling and Constrained Network Routing Problem
Gamst, Mette
This paper examines the NP-hard problem of scheduling a number of jobs on a finite set of machines such that the overall profit of executed jobs is maximized. Each job demands a number of resources, which must be sent to the executing machine via constrained paths. Furthermore, two resource demand...... transmissions cannot use the same edge in the same time period. An exact solution approach based on Dantzig-Wolfe decomposition is proposed along with several heuristics. The methods are computationally evaluated on test instances arising from telecommunications with up to 500 jobs and 500 machines. Results...
PRIORITY BASED UPLINK SCHEDULER FOR IEEE 802.16 NETWORKS
Gurpreet Singh,
2011-06-01
Full Text Available IEEE 802.16, the standard for fixed, portable and mobile Broadband Wireless Access (BWA systems, is promising to support different classes of traffic with Quality of Service (QoS. The Medium Access Control (MAC protocol defines a wide variety of mechanisms for bandwidth allocation and QoS provision. However, the details of how to schedule traffic are left unspecified. In this paper, we propose ascheduling strategy for uplink traffic. Simulation results show that our scheme is capable to provide required QoS.
An Optimal CDS Construction Algorithm with Activity Scheduling in Ad Hoc Networks
Penumalli, Chakradhar; Palanichamy, Yogesh
2015-01-01
A new energy efficient optimal Connected Dominating Set (CDS) algorithm with activity scheduling for mobile ad hoc networks (MANETs) is proposed. This algorithm achieves energy efficiency by minimizing the Broadcast Storm Problem [BSP] and at the same time considering the node's remaining energy. The Connected Dominating Set is widely used as a virtual backbone or spine in mobile ad hoc networks [MANETs] or Wireless Sensor Networks [WSN]. The CDS of a graph representing a network has a significant impact on an efficient design of routing protocol in wireless networks. Here the CDS is a distributed algorithm with activity scheduling based on unit disk graph [UDG]. The node's mobility and residual energy (RE) are considered as parameters in the construction of stable optimal energy efficient CDS. The performance is evaluated at various node densities, various transmission ranges, and mobility rates. The theoretical analysis and simulation results of this algorithm are also presented which yield better results. PMID:26221627
M/S Controller Area Network(CAN) System Using Shared-Clock Scheduler
LIU Jianxin; TAN Ping; LIU Yu
2006-01-01
The Controller Area Network (CAN) is a well established control network for automotive and automation control applications. Time-Triggered Controller Area Network (TTCAN) is a recent development which introduces a session layer, for message scheduling, to the existing CAN standard, which is a two layer standard comprising of a physical layer and a data link layer. TTCAN facilitates network communication in a time-triggered fashion, by introducing a Time Division Multiple Access style communication scheme. This allows deterministic network behavior, where maximum message latency times can be quantified and guaranteed. In order to solve the problem of determinate time latency and synchronization among several districted units in one auto panel CAN systems, this paper proposed a prototype design implementation for a shared-clock scheduler based on PIC18F458 MCU. This leads to improved CAN system performance and avoid the latency jitters and guarantee a deterministic communication pattern on the bus. The real runtime performance is satisfied.
Hossein Naderi
2012-08-01
Full Text Available Stock market prediction is one of the most important interesting areas of research in business. Stock markets prediction is normally assumed as tedious task since there are many factors influencing the market. The primary objective of this paper is to forecast trend closing price movement of Tehran Stock Exchange (TSE using financial accounting ratios from year 2003 to year 2008. The proposed study of this paper uses two approaches namely Artificial Neural Networks and multi-layer perceptron. Independent variables are accounting ratios and dependent variable of stock price , so the latter was gathered for the industry of Motor Vehicles and Auto Parts. The results of this study show that neural networks models are useful tools in forecasting stock price movements in emerging markets but multi-layer perception provides better results in term of lowering error terms.
Efficient Resource Scheduling by Exploiting Relay Cache for Cellular Networks
Chun He
2015-01-01
Full Text Available In relay-enhanced cellular systems, throughput of User Equipment (UE is constrained by the bottleneck of the two-hop link, backhaul link (or the first hop link, and access link (the second hop link. To maximize the throughput, resource allocation should be coordinated between these two hops. A common resource scheduling algorithm, Adaptive Distributed Proportional Fair, only ensures that the throughput of the first hop is greater than or equal to that of the second hop. But it cannot guarantee a good balance of the throughput and fairness between the two hops. In this paper, we propose a Two-Hop Balanced Distributed Scheduling (TBS algorithm by exploiting relay cache for non-real-time data traffic. The evolved Node Basestation (eNB adaptively adjusts the number of Resource Blocks (RBs allocated to the backhaul link and direct links based on the cache information of relays. Each relay allocates RBs for relay UEs based on the size of the relay UE’s Transport Block. We also design a relay UE’s ACK feedback mechanism to update the data at relay cache. Simulation results show that the proposed TBS can effectively improve resource utilization and achieve a good trade-off between system throughput and fairness by balancing the throughput of backhaul and access link.
A target coverage scheduling scheme based on genetic algorithms in directional sensor networks.
Gil, Joon-Min; Han, Youn-Hee
2011-01-01
As a promising tool for monitoring the physical world, directional sensor networks (DSNs) consisting of a large number of directional sensors are attracting increasing attention. As directional sensors in DSNs have limited battery power and restricted angles of sensing range, maximizing the network lifetime while monitoring all the targets in a given area remains a challenge. A major technique to conserve the energy of directional sensors is to use a node wake-up scheduling protocol by which some sensors remain active to provide sensing services, while the others are inactive to conserve their energy. In this paper, we first address a Maximum Set Covers for DSNs (MSCD) problem, which is known to be NP-complete, and present a greedy algorithm-based target coverage scheduling scheme that can solve this problem by heuristics. This scheme is used as a baseline for comparison. We then propose a target coverage scheduling scheme based on a genetic algorithm that can find the optimal cover sets to extend the network lifetime while monitoring all targets by the evolutionary global search technique. To verify and evaluate these schemes, we conducted simulations and showed that the schemes can contribute to extending the network lifetime. Simulation results indicated that the genetic algorithm-based scheduling scheme had better performance than the greedy algorithm-based scheme in terms of maximizing network lifetime.
LI Zhi-yuan; WANG Ru-chuan
2010-01-01
With the fast development of the micro-electro-mechanical systems(MEMS),wireless sensor networks(WSNs)have been extensively studied.Most of the studies focus on saving energy consumption because of restricted energy supply in WSNs.Cluster-based node scheduling scheme is commonly considered as one of the most energy-efficient approaches.However,it is not always so efficient especially when there exist hot spot and network attacks in WSNs.In this article,a secure coverage-preserved node scheduling scheme for WSNs based on energy prediction is proposed in an uneven deployment environment.The scheme is comprised of an uneven clustering algorithm based on arithmetic progression,a cover set partition algorithm based on trust and a node scheduling algorithm based on energy prediction.Simulation results show that network lifetime of the scheme is 350 rounds longer than that of other scheduling algorithms.Furthermore,the scheme can keep a high network coverage ratio during the network lifetime and achieve the designed objective which makes energy dissipation of most nodes in WSNs balanced.
Energy-Optimal Scheduling in Low Duty Cycle Sensor Networks
Aydin, Nursen; Ercetin, Ozgur
2011-01-01
Energy consumption of a wireless sensor node mainly depends on the amount of time the node spends in each of the high power active (e.g., transmit, receive) and low power sleep modes. It has been well established that in order to prolong node's lifetime the duty-cycle of the node should be low. However, low power sleep modes usually have low current draw but high energy cost while switching to the active mode with a higher current draw. In this work, we investigate a MaxWeightlike opportunistic sleep-active scheduling algorithm that takes into account time- varying channel and traffic conditions. We show that our algorithm is energy optimal in the sense that the proposed ESS algorithm can achieve an energy consumption which is arbitrarily close to the global minimum solution. Simulation studies are provided to confirm the theoretical results.
Method and apparatus for scheduling broadcasts in social networks
Manzoor, Emaad Ahmed
2016-08-25
A method, apparatus, and computer readable medium are provided for maximizing consumption of broadcasts by a producer. An example method includes receiving selection of a total number of time slots to use for scheduling broadcasts, and receiving information regarding the producer\\'s followers. The example method further 5 includes identifying, by a processor and based on the received information, discount factors associated with the producer\\'s followers, and calculating, by the processor and based on the received information, a predicted number of competitor broadcasts during each time slot of the total number of time slots. Finally, the example method includes determining, by the processor and based on the discount factors and the predicted 10 number of competitor broadcasts during each time slot, a number of broadcasts for the producer to transmit in each time slot of the total number of time slots.
AREA-EFFICIENT DESIGN OF SCHEDULER FOR ROUTING NODE OF NETWORK-ON-CHIP
Rehan Maroof
2011-09-01
Full Text Available Traditional System-on-Chip (SoC design employed shared buses for data transfer among various subsystems. As So Cs become more complex involving a larger number of subsystems, traditional bus based architecture is giving way to a new paradigm for on-chip communication. This paradigm is called Network-on-Chip (NoC. A communication network of point-to-point links and routing switches is used to facilitate communication between subsystems. The routing switch proposed in this paper consists of four components, namely the input ports, output ports, switching fabric, and scheduler. The scheduler design is described in this paper. The function of the scheduler is to arbitrate between requests by data packets for use of the switching fabric. The scheduler uses an improved round robin based arbitration algorithm. Due to the symmetric structure of the scheduler, an area-efficient design is proposed by folding the scheduler onto itself, thereby reducing its area roughly by 50%.
Energy-efficient scheduling under delay constraints for wireless networks
Berry, Randal; Zafer, Murtaza
2012-01-01
Packet delay and energy consumption are important considerations in wireless and sensor networks as these metrics directly affect the quality of service of the application and the resource consumption of the network; especially, for a rapidly growing class of real-time applications that impose strict restrictions on packet delays. Dynamic rate control is a novel technique for adapting the transmission rate of wireless devices, almost in real-time, to opportunistically exploit time-varying channel conditions as well as changing traffic patterns. Since power consumption is not a linear function
The Price of Selfish Stackelberg Leadership in a Network Game
Goldberg, P W
2007-01-01
We study a class of games in which a finite number of agents each controls a quantity of flow to be routed through a network, and are able to split their own flow between multiple paths through the network. Recent work on this model has contrasted the social cost of Nash equilibria with the best possible social cost. Here we show that additional costs are incurred in situations where a selfish ``leader'' agent allocates his flow, and then commits to that choice so that other agents are compelled to minimise their own cost based on the first agent's choice. We find that even in simple networks, the leader can often improve his own cost at the expense of increased social cost. Focusing on the 2-player case, we give upper and lower bounds on the worst-case additional cost incurred.
Stock prices forecasting based on wavelet neural networks with PSO
Wang Kai-Cheng
2017-01-01
Full Text Available This research examines the forecasting performance of wavelet neural network (WNN model using published stock data obtained from Financial Times Stock Exchange (FTSE Taiwan Stock Exchange (TWSE 50 index, also known as Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX, hereinafter referred to as Taiwan 50. Our WNN model uses particle swarm optimization (PSO to choose the appropriate initial network values for different companies. The findings come with two advantages. First, the network initial values are automatically selected instead of being a constant. Second, threshold and training data percentage become constant values, because PSO assists with self-adjustment. We can achieve a success rate over 73% without the necessity to manually adjust parameter or create another math model.
Bi-objective network equilibrium, traffic assignment and road pricing
Wang, JYT; Ehrgott, M
2014-01-01
Multi-objective equilibrium models of traffic assignment state that users of road networks travel on routes that are efficient with respect to several objectives, such as travel time and toll. This concept provides a general framework for modelling traffic flow in tolled road networks. We present the concept of time surplus maximisation as a way of handling user preferences. Given a toll, users have a maximum time they are willing to spend for a trip. Time surplus is this maximum time minus a...
A Round-based Pricing Scheme for Maximizing Service Provider's Revenue in P2PTV Networks
Bhutani, Gitanjali
2009-01-01
In this paper, we analyze a round-based pricing scheme that encourages favorable behavior from users of real-time P2P applications like P2PTV. In the design of pricing schemes, we consider price to be a function of usage and capacity of download/upload streams, and quality of content served. Users are consumers and servers at the same time in such networks, and often exhibit behavior that is unfavorable towards maximization of social benefits. Traditionally, network designers have overcome this difficulty by building-in traffic latencies. However, using simulations, we show that appropriate pricing schemes and usage terms can enable designers to limit required traffic latencies, and be able to earn nearly 30% extra revenue from providing P2PTV services. The service provider adjusts the prices of individual programs incrementally within rounds, while making relatively large-scale adjustments at the end of each round. Through simulations, we show that it is most beneficial for the service provider to carry out ...
Real Time Updating Genetic Network Programming for Adapting to the Change of Stock Prices
Chen, Yan; Mabu, Shingo; Shimada, Kaoru; Hirasawa, Kotaro
The key in stock trading model is to take the right actions for trading at the right time, primarily based on the accurate forecast of future stock trends. Since an effective trading with given information of stock prices needs an intelligent strategy for the decision making, we applied Genetic Network Programming (GNP) to creating a stock trading model. In this paper, we propose a new method called Real Time Updating Genetic Network Programming (RTU-GNP) for adapting to the change of stock prices. There are three important points in this paper: First, the RTU-GNP method makes a stock trading decision considering both the recommendable information of technical indices and the candlestick charts according to the real time stock prices. Second, we combine RTU-GNP with a Sarsa learning algorithm to create the programs efficiently. Also, sub-nodes are introduced in each judgment and processing node to determine appropriate actions (buying/selling) and to select appropriate stock price information depending on the situation. Third, a Real Time Updating system has been firstly introduced in our paper considering the change of the trend of stock prices. The experimental results on the Japanese stock market show that the trading model with the proposed RTU-GNP method outperforms other models without real time updating. We also compared the experimental results using the proposed method with Buy&Hold method to confirm its effectiveness, and it is clarified that the proposed trading model can obtain much higher profits than Buy&Hold method.
Pricing, Competition, and Routing for Selfish and Strategic Nodes in Multi-hop Relay Networks
Xi, Yufang
2007-01-01
We study a pricing game in multi-hop relay networks where nodes price their services and route their traffic selfishly and strategically. In this game, each node (1) announces pricing functions which specify the payments it demands from its respective customers depending on the amount of traffic they route to it and (2) allocates the total traffic it receives to its service providers. The profit of a node is the difference between the revenue earned from servicing others and the cost of using others' services. We show that the socially optimal routing of such a game can always be induced by an equilibrium where no node can increase its profit by unilaterally changing its pricing functions or routing decision. On the other hand, there may also exist inefficient equilibria. We characterize the loss of efficiency by deriving the price of anarchy at inefficient equilibria. We show that the price of anarchy is finite for oligopolies with concave marginal cost functions, while it is infinite for general topologies ...
A Hybrid Artificial Neural Network-based Scheduling Knowledge Acquisition Algorithm
WANG Weida; WANG Wei; LIU Wenjian
2006-01-01
It is a key issue that constructing successful knowledge base to satisfy an efficient adaptive scheduling for the complex manufacturing system. Therefore, a hybrid artificial neural network (ANN)-based scheduling knowledge acquisition algorithm is presented in this paper. We combined genetic algorithm (GA) with simulated annealing (SA) to develop a hybrid optimization method, in which GA was introduced to present parallel search architecture and SA was introduced to increase escaping probability from local optima and ability to neighbor search. The hybrid method was utilized to resolve the optimal attributes subset of manufacturing system and determine the optimal topology and parameters of ANN under different scheduling objectives; ANN was used to evaluate the fitness of chromosome in the method and generate the scheduling knowledge after obtaining the optimal attributes subset, optimal ANN's topology and parameters. The experimental results demonstrate that the proposed algorithm produces significant performance improvements over other machine learning-based algorithms.
Feedback Scheduling of Model-based Networked Control Systems with Flexible Workload
Xian-Ming Tang; Jin-Shou Yu
2008-01-01
In this paper, a novel control structure called feedback scheduling of model-based networked control systems is proposed to cope with a flexible network load and resource constraints. The state update time is adjusted according to the real-time network congestion situation. State observer is used under the situation where the state of the controlled plant could not be acquired. The stability criterion of the proposed structure is proved with time-varying state update time. On the basis of the stability of the novel system structure, the compromise between the control performance and the network utilization is realized by using feedback scheduler.Examples are provided to show the advantage of the proposed control structure.
Multipath Routing With Novel Packet Scheduling Approach In Wireless Sensor Networks
Cherian, Mary
2012-01-01
Wireless sensor networks sense and monitor real-time events. They supervise a geographic area where a phenomenon is to be monitored. The data in sensor networks have different levels of priority and hence their criticality differs. In order to keep up the real time commitment, the applications need higher transmission rates and reliability in information delivery. In this work we propose a multipath routing algorithm which enables the reliable delivery of data. By controlling the scheduling rate, it is possible to prevent congestion and packet loss in the network. The algorithm provides an efficient way to prevent the packet loss at each node. This results in congestion management in the sensor networks. This protocol prevents packet clustering and provides smoothness to the traffic. Through monitoring and controlling the scheduling rate the flow control and congestion control are managed.
BROADCAST SCHEDULING WITH MIMO LINKS IN MULTI-HOP AD HOC NETWORKS
Zhang Guanghui; Li Jiandong; Zhao Min; Li Changle
2007-01-01
As the current medium access control protocols with Multiple Input Multiple Output (MIMO) links only bear point to point service, broadcast scheduling algorithm in ad hoc networks with MIMO links is proposed. The key to the proposed broadcast scheduling algorithm is the time slot scheduling algorithm which guarantees collision-free transmissions for every node and the minimum frame length. The proposed algorithm increases the simultaneous transmissions of MIMO links efficiently. Due to the interference null capacity of MIMO links, the interference node set of each node can decrease from two-hop neighbors to one-hop neighbors possibly. Simulation results show that our algorithm can greatly improve network capacity and decrease average packet delay.
Distributed Wake-Up Scheduling for Energy Saving in Wireless Networks
De Pellegrini, Francesco; Miorandi, Daniele; Chlamtac, Imrich
2011-01-01
A customary solution to reduce the energy consumption of wireless communication devices is to periodically put the radio into low-power sleep mode. A relevant problem is to schedule the wake-up of nodes in such a way as to ensure proper coordination among devices, respecting delay constraints while still saving energy. In this paper, we introduce a simple algebraic characterization of the problem of periodic wake-up scheduling under both energy consumption and delay constraints. We demonstrate that the general problem of wake-up times coordination is equivalent to integer factorization and discuss the implications on the design of efficient scheduling algorithms. We then propose simple polynomial time heuristic algorithms that can be implemented in a distributed fashion and present a message complexity of the order of the number of links in the network. Numerical results are provided in order to assess the performance of the proposed techniques when applied to wireless sensor networks.
Adaptive Sensor Activity Scheduling in Distributed Sensor Networks: A Statistical Mechanics Approach
Abhishek Srivastav; Asok Ray; Shashi Phoha
2009-01-01
This article presents an algorithm for adaptive sensor activity scheduling (A-SAS) in distributed sensor networks to enable detection and dynamic footprint tracking of spatial-temporal events. The sensor network is modeled as a Markov random field on a graph, where concepts of Statistical Mechanics are employed to stochastically activate the sensor nodes. Using an Ising-like formulation, the sleep and wake modes of a sensor node are modeled as spins with ferromagnetic neighborhood interaction...
Studying on equilibriums between price and QoS in multi-provider overlay access networks
Wang Yufeng; Wang Wendong
2006-01-01
From the viewpoint of game theory, this paper proposes a model that combines QoS index with price factor in overlay access networks, and uses the multinomial logit (MNL) to model the choice behaviour of users. Each service class is considered an independent and competitive entity offered by each provider,which aims at maximizing its own utility. Based on noncooperative game, we prove the existence and uniqueness of equilibriums between QoS levels and prices among various service classes, and demonstrate the properties of equilibriums. Finally, these results are verified via numerical analysis.
Coordinated scheduling for the downlink of cloud radio-access networks
Douik, Ahmed S.
2015-09-11
This paper addresses the coordinated scheduling problem in cloud-enabled networks. Consider the downlink of a cloud-radio access network (CRAN), where the cloud is only responsible for the scheduling policy and the synchronization of the transmit frames across the connected base-stations (BS). The transmitted frame of every BS consists of several time/frequency blocks, called power-zones (PZ), maintained at fixed transmit power. The paper considers the problem of scheduling users to PZs and BSs in a coordinated fashion across the network, by maximizing a network-wide utility under the practical constraint that each user cannot be served by more than one base-station, but can be served by one or more power-zones within each base-station frame. The paper solves the problem using a graph theoretical approach by introducing the scheduling graph in which each vertex represents an association of users, PZs and BSs. The problem is formulated as a maximum weight clique, in which the weight of each vertex is the benefit of the association represented by that vertex. The paper further presents heuristic algorithms with low computational complexity. Simulation results show the performance of the proposed algorithms and suggest that the heuristics perform near optimal in low shadowing environments. © 2015 IEEE.
Optimizing Intermodal Train Schedules with a Design Balanced Network Design Model
Pedersen, Michael Berliner; Crainic, Teodor Gabriel
We present a modeling approach for optimizing intermodal trains schedules based on an infrastructure divided into time-dependent train paths. The formulation can be generalized to a capacitated multi commodity network design model with additional design balance constraints. We present a Tabu Search...
A Scheduling Discipline for Latency and Bandwidth Guarantees in Asynchronous Network-on-Chip
Bjerregaard, Tobias; Sparsø, Jens
2005-01-01
Guaranteed services (GS) are important in that they provide predictability in the complex dynamics of shared communication structures. This paper discusses the implementation of GS in asynchronous Network-on-Chip. We present a novel scheduling discipline called Asynchronous Latency Guarantee (ALG...
Time-optimum packet scheduling for many-to-one routing in wireless sensor networks
Song, W.-Z.; Yuan, F.; LaHusen, R.; Shirazi, B.
2007-01-01
This paper studies the wireless sensor networks (WSN) application scenario with periodical traffic from all sensors to a sink. We present a time-optimum and energy-efficient packet scheduling algorithm and its distributed implementation. We first give a general many-to-one packet scheduling algorithm for wireless networks, and then prove that it is time-optimum and costs [image omitted], N(u0)-1) time slots, assuming each node reports one unit of data in each round. Here [image omitted] is the total number of sensors, while [image omitted] denotes the number of sensors in a sink's largest branch subtree. With a few adjustments, we then show that our algorithm also achieves time-optimum scheduling in heterogeneous scenarios, where each sensor reports a heterogeneous amount of data in each round. Then we give a distributed implementation to let each node calculate its duty-cycle locally and maximize efficiency globally. In this packet-scheduling algorithm, each node goes to sleep whenever it is not transceiving, so that the energy waste of idle listening is also mitigated. Finally, simulations are conducted to evaluate network performance using the Qualnet simulator. Among other contributions, our study also identifies the maximum reporting frequency that a deployed sensor network can handle.
Multi-Channel Scheduling for Fast Convergecast in Wireless Sensor Networks
Durmaz, O.; Ghosh, A.; Krishnamachari, B.; Chintalapudi, K.
We explore the following fundamental question - how fast can information be collected from a wireless sensor network? We consider a number of design parameters such as, power control, time and frequency scheduling, and routing. There are essentially two factors that hinder efficient data collection
Scheduling Data Access in Smart Grid Networks Utilizing Context Information
Findrik, Mislav; Grønbæk, Jesper; Olsen, Rasmus Løvenstein
2014-01-01
Current electrical grid is facing increased penetration of intermittent energy resources, in particular wind and solar energy. Fast variability of the power supply due to renewable energy resources can be balanced out using different energy storage systems or shifting the loads. Efficiently...... of this approach for a constraint communication networks of the smart grid and compared three general data access mechanisms, namely, push, pull and event-based....
Scheduling of network access for feedback-based embedded systems
Liberatore, Vincenzo
2002-07-01
nd communication capabilities. Examples range from smart dust embedded in building materials to networks of appliances in the home. Embedded devices will be deployed in unprecedented numbers, will enable pervasive distributed computing, and will radically change the way people interact with the surrounding environment [EGH00a]. The paper targets embedded systems and their real-time (RT) communication requirements. RT requirements arise from the
Using Artificial Neural Networks to Predict Stock Prices
Kozdraj, Tomasz
2009-01-01
Artificial neural networks constitute one of the most developed conception of artificial intelligence. They are based on pragmatic mathematical theories adopted to tasks resolution. A wide range of their applications also includes financial investments issues. The reason for NN's popularity is mainly connected with their ability to solve complex or not well recognized computational tasks, efficiency in finding solutions as well as the possibility of learning based on patterns or without them....
The Price of Anarchy in Network Creation Games Is (Mostly) Constant
Mihalák, Matúš; Schlegel, Jan Christoph
We study the price of anarchy and the structure of equilibria in network creation games. A network creation game (first defined and studied by Fabrikant et al. [4]) is played by n players {1,2,...,n}, each identified with a vertex of a graph (network), where the strategy of player i, i = 1,...,n, is to build some edges adjacent to i. The cost of building an edge is α> 0, a fixed parameter of the game. The goal of every player is to minimize its creation cost plus its usage cost. The creation cost of player i is α times the number of built edges. In the SumGame (the original variant of Fabrikant et al. [4]) the usage cost of player i is the sum of distances from i to every node of the resulting graph. In the MaxGame (variant defined and studied by Demaine et al. [3]) the usage cost is the eccentricity of i in the resulting graph of the game. In this paper we improve previously known bounds on the price of anarchy of the game (of both variants) for various ranges of α, and give new insights into the structure of equilibria for various values of α. The two main results of the paper show that for α > 273·n all equilibria in SumGame are trees and thus the price of anarchy is constant, and that for α> 129 all equilibria in MaxGame are trees and the price of anarchy is constant. For SumGame this (almost) answers one of the basic open problems in the field - is price of anarchy of the network creation game constant for all values of α? - in an affirmative way, up to a tiny range of α.
Mixed Integer Programming and Heuristic Scheduling for Space Communication Networks
Lee, Charles H.; Cheung, Kar-Ming
2012-01-01
In this paper, we propose to solve the constrained optimization problem in two phases. The first phase uses heuristic methods such as the ant colony method, particle swarming optimization, and genetic algorithm to seek a near optimal solution among a list of feasible initial populations. The final optimal solution can be found by using the solution of the first phase as the initial condition to the SQP algorithm. We demonstrate the above problem formulation and optimization schemes with a large-scale network that includes the DSN ground stations and a number of spacecraft of deep space missions.
Mixed Integer Programming and Heuristic Scheduling for Space Communication Networks
Lee, Charles H.; Cheung, Kar-Ming
2012-01-01
In this paper, we propose to solve the constrained optimization problem in two phases. The first phase uses heuristic methods such as the ant colony method, particle swarming optimization, and genetic algorithm to seek a near optimal solution among a list of feasible initial populations. The final optimal solution can be found by using the solution of the first phase as the initial condition to the SQP algorithm. We demonstrate the above problem formulation and optimization schemes with a large-scale network that includes the DSN ground stations and a number of spacecraft of deep space missions.
Forecasting Natural Gas Prices Using Wavelets, Time Series, and Artificial Neural Networks.
Jin, Junghwan; Kim, Jinsoo
2015-01-01
Following the unconventional gas revolution, the forecasting of natural gas prices has become increasingly important because the association of these prices with those of crude oil has weakened. With this as motivation, we propose some modified hybrid models in which various combinations of the wavelet approximation, detail components, autoregressive integrated moving average, generalized autoregressive conditional heteroskedasticity, and artificial neural network models are employed to predict natural gas prices. We also emphasize the boundary problem in wavelet decomposition, and compare results that consider the boundary problem case with those that do not. The empirical results show that our suggested approach can handle the boundary problem, such that it facilitates the extraction of the appropriate forecasting results. The performance of the wavelet-hybrid approach was superior in all cases, whereas the application of detail components in the forecasting was only able to yield a small improvement in forecasting performance. Therefore, forecasting with only an approximation component would be acceptable, in consideration of forecasting efficiency.
Class-Based Weighted Fair Queuing Scheduling on Dual-Priority Delta Networks
D. C. Vasiliadis
2012-01-01
Full Text Available Contemporary networks accommodate handling of multiple priorities, aiming to provide suitable QoS levels to different traffic classes. In the presence of multiple priorities, a scheduling algorithm is employed to select each time the next packet to transmit over the data link. Class-based Weighted Fair Queuing (CBWFQ scheduling and its variations is widely used as a scheduling technique, since it is easy to implement and prevents the low-priority queues from being completely neglected during periods of high-priority traffic. By using this scheduling, low-priority queues have the opportunity to transmit packets even though the high-priority queues are not empty. In this work, the modeling, analysis and performance evaluation of a single-buffered, dual-priority multistage interconnection network (MIN operating under the CBWFQ scheduling policy is presented. Performance evaluation is conducted through simulation, and the performance measures obtained can be valuable assets for MIN designers, in order to minimize the overall deployment costs and delivering efficient systems.
A Game Theoretic Framework for Bandwidth Allocation and Pricing in Federated Wireless Networks
Gu, Bo; Yamori, Kyoko; Xu, Sugang; Tanaka, Yoshiaki
With the proliferation of IEEE 802.11 wireless local area networks, large numbers of wireless access points have been deployed, and it is often the case that a user can detect several access points simultaneously in dense metropolitan areas. Most owners, however, encrypt their networks to prevent the public from accessing them due to the increased traffic and security risk. In this work, we use pricing as an incentive mechanism to motivate the owners to share their networks with the public, while at the same time satisfying users' service demand. Specifically, we propose a “federated network” concept, in which radio resources of various wireless local area networks are managed together. Our algorithm identifies two candidate access points with the lowest price being offered (if available) to each user. We then model the price announcements of access points as a game, and characterize the Nash Equilibrium of the system. The efficiency of the Nash Equilibrium solution is evaluated via simulation studies as well.
Mohammad Fathian
2012-04-01
Full Text Available In this paper, the problem of predicting the exchange rate time series in the foreign exchange rate market is going to be solved using a time-delayed multilayer perceptron neural network with gold price as external factor. The input for the learning phase of the artificial neural network are the exchange rate data of the last five days plus the gold price in two different currencies of the exchange rate as the external factor for helping the artificial neural network improving its forecast accuracy. The five-day delay has been chosen because of the weekly cyclic behavior of the exchange rate time series with the consideration of two holidays in a week. The result of forecasts are then compared with using the multilayer peceptron neural network without gold price external factor by two most important evaluation techniques in the literature of exchange rate prediction. For the experimental analysis phase, the data of three important exchange rates of EUR/USD, GBP/USD, and USD/JPY are used.
Low-Feedback Opportunistic Scheduling Schemes for Wireless Networks with Heterogenous Users
Rashid, Faraan
2012-07-01
Efficient implementation of resource sharing strategies in a multi-user wireless environment can improve the performance of a network significantly. In this thesis we study various scheduling strategies for wireless networks and handle the problem of opportunistically scheduling transmissions using channel aware schemes. First we propose a scheme that can handle users with asymmetric channel conditions and is opportunistic in the sense that it exploits the multi-user diversity of the network. The scheme requires the users to have a priori knowledge of their channel distributions. The associated overhead is limited meaning it offers reduced feedback load, that does not scale with the increasing number of users. The main technique used to shrink the feedback load is the contention based distributed implementation of a splitting algorithm that does not require explicit feedback to the scheduler from every user. The users find the best among themselves, in a distributed manner, while requiring just a ternary broadcast feedback from the scheduler at the end of each mini-slot. In addition, it can also handle fairness constraints in time and throughput to various degrees. Next we propose another opportunistic scheduler that offers most of the benefits of the previously proposed scheme but is more practical because it can also handle heterogenous users whose channel distributions are unknown. This new scheme actually reduces the complexity and is also more robust for changing traffic patterns. Finally we extend both these schemes to the scenario where there are fixed thresholds, this enables us to handle opportunistic scheduling in practical systems that can only transmit over finite number of discrete rates with the additional benefit that full feedback session, even from the selected user, is never required.
Distributed and Cooperative Link Scheduling for Large-Scale Multihop Wireless Networks
Ananthram Swami
2007-12-01
Full Text Available A distributed and cooperative link-scheduling (DCLS algorithm is introduced for large-scale multihop wireless networks. With this algorithm, each and every active link in the network cooperatively calibrates its environment and converges to a desired link schedule for data transmissions within a time frame of multiple slots. This schedule is such that the entire network is partitioned into a set of interleaved subnetworks, where each subnetwork consists of concurrent cochannel links that are properly separated from each other. The desired spacing in each subnetwork can be controlled by a tuning parameter and the number of time slots specified for each frame. Following the DCLS algorithm, a distributed and cooperative power control (DCPC algorithm can be applied to each subnetwork to ensure a desired data rate for each link with minimum network transmission power. As shown consistently by simulations, the DCLS algorithm along with a DCPC algorithm yields significant power savings. The power savings also imply an increased feasible region of averaged link data rates for the entire network.
Distributed and Cooperative Link Scheduling for Large-Scale Multihop Wireless Networks
Swami Ananthram
2007-01-01
Full Text Available A distributed and cooperative link-scheduling (DCLS algorithm is introduced for large-scale multihop wireless networks. With this algorithm, each and every active link in the network cooperatively calibrates its environment and converges to a desired link schedule for data transmissions within a time frame of multiple slots. This schedule is such that the entire network is partitioned into a set of interleaved subnetworks, where each subnetwork consists of concurrent cochannel links that are properly separated from each other. The desired spacing in each subnetwork can be controlled by a tuning parameter and the number of time slots specified for each frame. Following the DCLS algorithm, a distributed and cooperative power control (DCPC algorithm can be applied to each subnetwork to ensure a desired data rate for each link with minimum network transmission power. As shown consistently by simulations, the DCLS algorithm along with a DCPC algorithm yields significant power savings. The power savings also imply an increased feasible region of averaged link data rates for the entire network.
Power Saving Scheduling Scheme for Internet of Things over LTE/LTE-Advanced Networks
Yen-Wei Kuo
2015-01-01
Full Text Available The devices of Internet of Things (IoT will grow rapidly in the near future, and the power consumption and radio spectrum management will become the most critical issues in the IoT networks. Long Term Evolution (LTE technology will become a promising technology used in IoT networks due to its flat architecture, all-IP network, and greater spectrum efficiency. The 3rd Generation Partnership Project (3GPP specified the Discontinuous Reception (DRX to reduce device’s power consumption. However, the DRX may pose unexpected communication delay due to missing Physical Downlink Control Channel (PDCCH information in sleep mode. Recent studies mainly focus on optimizing DRX parameters to manage the tradeoff between the energy consumption and communication latency. In this paper, we proposed a fuzzy-based power saving scheduling scheme for IoT over the LTE/LTE-Advanced networks to deal with the issues of the radio resource management and power consumption from the scheduling and resource allocation perspective. The proposed scheme considers not only individual IoT device’s real-time requirement but also the overall network performance. The simulation results show that our proposed scheme can meet the requirements of the DRX cycle and scheduling latency and can save about half of energy consumption for IoT devices compared to conventional approaches.
Jie CHEN; Min-jian ZHAO; Qiao ZHOU; Shi-ju LI
2008-01-01
We propose the spectrum allocation and resource scheduling algorithms in cognitive point to multipoint (PMP)networks with rapid changes of spectrum opportunities and present a media access control (MAC) protocol based on these algorithms. The objective of spectrum allocation is to make efficient use of the spectrum while maintaining the transceiver synchronization on frequency and time in the network. The objective of resource scheduling is to guarantee the quality of service (QoS)requirements of different kinds of connections and to minimize the total energy consumption in the network as well. By sensing only a small set of possible channels in each slot based on the state transition probability of each channel, our spectrum allocation algorithm achieves high spectrum efficiency in the network. The resource scheduling problem is divided into three sub problems and we derive optimal solutions to these problems by greedy algorithm and convex optimization. The simulation results show that our algorithm can make efficient use of the spectrum and the network resources at a cost of low computational complexity.
CLUSTER BASED TIME DIVISION MULTIPLE ACCESS SCHEDULING SCHEME FOR ZIGBEE WIRELESS SENSOR NETWORKS
P. Anandhakumar
2012-01-01
Full Text Available In IEEE 802.15.4 ZigBee Wireless Sensor Networks, an efficient scheduling mechanism is required for reliable data transmission. Further, concurrent transmission of huge data through CSMA/CA incurs more packet collision rate. This complicated condition has to be eliminated to improve the system throughput. In this study, we propose to deploy cluster based TDMA scheduling mechanism for IEEE 802.15.4 ZigBee Wireless Sensor Networks. This TDMA slot allocation strategy allocates slots to the nodes based on queue occupancy information. It assigns TDMA slots starting from nodes with high queue occupancy value. Nodes that have high queue occupancy value will probably get long TDMA slot period. We prove the proficiency of our mechanism using Network Simulator 2 (NS-2. Our approach fairly allocates slots to the nodes and considerably reduces packet collision rate."
张闯; 赵洪林; 贾敏
2015-01-01
In non-dedicated cooperative relay networks, each node is autonomous and selfish in nature, and thus spontaneous cooperation among nodes is challenged. To stimulate the selfish node to participate in cooperation, a pricing-based cooperation engine using game theory was designed. Firstly, the feasible regions of the charge price and reimbursement price were deduced. Then, the non-cooperative and cooperative games were adopted to analyze the amount of bandwidth that initiating cooperation node (ICN) forwards data through participating cooperation node (PCN) and the amount of bandwidth that PCN helps ICN to relay data. Meanwhile, the Nash equilibrium solutions of cooperation bandwidth allocations (CBAs) were obtained through geometrical interpretation. Secondly, a pricing-based cooperation engine was proposed and a cooperative communication system model with cooperation engines was depicted. Finally, an algorithm based on game theory was proposed to realize the cooperation engine. The simulation results demonstrate that, compared with the system without pricing-based incentive, the proposed system can significantly improve the ICN’s metric measured by bit-per-Joule and increase the PCN’s revenue.
Fair Energy Scheduling for Vehicle-to-Grid Networks Using Adaptive Dynamic Programming.
Xie, Shengli; Zhong, Weifeng; Xie, Kan; Yu, Rong; Zhang, Yan
2016-08-01
Research on the smart grid is being given enormous supports worldwide due to its great significance in solving environmental and energy crises. Electric vehicles (EVs), which are powered by clean energy, are adopted increasingly year by year. It is predictable that the huge charge load caused by high EV penetration will have a considerable impact on the reliability of the smart grid. Therefore, fair energy scheduling for EV charge and discharge is proposed in this paper. By using the vehicle-to-grid technology, the scheduler controls the electricity loads of EVs considering fairness in the residential distribution network. We propose contribution-based fairness, in which EVs with high contributions have high priorities to obtain charge energy. The contribution value is defined by both the charge/discharge energy and the timing of the action. EVs can achieve higher contribution values when discharging during the load peak hours. However, charging during this time will decrease the contribution values seriously. We formulate the fair energy scheduling problem as an infinite-horizon Markov decision process. The methodology of adaptive dynamic programming is employed to maximize the long-term fairness by processing online network training. The numerical results illustrate that the proposed EV energy scheduling is able to mitigate and flatten the peak load in the distribution network. Furthermore, contribution-based fairness achieves a fast recovery of EV batteries that have deeply discharged and guarantee fairness in the full charge time of all EVs.
Dual scheduling and quantised control for networked control systems with communication constraints
Lu, Hui; Zhou, Chuan
2016-07-01
A novel integrated design scheme of average dwell time scheduling strategy, dynamic bandwidth allocation policy and quantised control for a collection of networked control systems (NCSs) with time delay and communication constraints is proposed in this paper. A scheduling policy is presented to accommodate the limitation of communication capacity which depends on the convergence rate of closed-loop system and divergence rate of open-loop plant. Linear programming technique is adopted to dynamically allocate bit rate for each node and the strategy is used to make trade-offs between the network utilisation and the control performance which provides an effective way of optimising the quality of control (QoC) and the quality of service (QoS) for NCSs. Mid-tread uniform quantisers update the quantisation rules according to the assignment of the bit rate and convert the quantised state into a kind of input saturation with bounded disturbances. Taking into account the effect of dual scheduling strategy and quantisation, the NCSs are modelled as discrete-time switched systems with bounded disturbances. Furthermore, a scheduling and quantised feedback control co-design procedure is proposed for the simultaneous stabilisation of the collection of networked subsystems. Finally, a simulation example is given to illustrate the effectiveness of the proposed method.
Xie, Wen-Jie; Li, Ming-Xia; Xu, Hai-Chuan; Chen, Wei; Zhou, Wei-Xing; Stanley, H. Eugene
2016-10-01
Traders in a stock market exchange stock shares and form a stock trading network. Trades at different positions of the stock trading network may contain different information. We construct stock trading networks based on the limit order book data and classify traders into k classes using the k-shell decomposition method. We investigate the influences of trading behaviors on the price impact by comparing a closed national market (A-shares) with an international market (B-shares), individuals and institutions, partially filled and filled trades, buyer-initiated and seller-initiated trades, and trades at different positions of a trading network. Institutional traders professionally use some trading strategies to reduce the price impact and individuals at the same positions in the trading network have a higher price impact than institutions. We also find that trades in the core have higher price impacts than those in the peripheral shell.
Bayesian Network Modeling to Improve Water Pricing Practices in Northwest China
Yusuyunjiang Mamitimin
2015-10-01
Full Text Available Water pricing is regarded as the most important and simplest economic instrument to encourage more efficient use of irrigation water in crop production. In the extremely water-scarce Tarim River basin in northwest China, improving water use efficiency has high relevance for research and policy. A Bayesian network modeling approach was applied, which is especially suitable under data-scarce conditions and the complex geo-hydrological, socioeconomic, and institutional settings of the study region, as it allows the integration of data from various types of sources. The transdisciplinary approach aimed at understanding the actual water pricing practices, the shortcomings of the current system, and possible ways of improvement. In an iterative procedure of expert interviews and group workshops, the key factors related to water pricing and water use efficiency were identified. The interactions among specific factors were defined by the respective experts, generating a causal network, which describes all relevant aspects of the investigated system. This network was finally populated with probabilistic relationships through a second round of expert interviews and group discussions. The Bayesian modeling exercise was then conducted using Netica software. The modeling results show that the mere increase of water price does not lead to significant increases in water use efficiency in crop production. Additionally, the model suggests a shift to volumetric water pricing, subsidization of water saving irrigation technology, and advancing agricultural extension to enable the farmer to efficiently react to increased costs for water. The applied participatory modeling approach helped to stimulate communication among relevant stakeholders from different domains in the region, which is necessary to create mutual understanding and joint targeted action. Finally, the challenges related to the applied transdisciplinary Bayesian modeling approach are discussed in the
Topology-Transparent Transmission Scheduling Algorithms in Wireless Ad Hoc Networks
MA Xiao-lei; WANG Chun-jiang; LIU Yuan-an; MA Lei-lei
2005-01-01
In order to maximize the average throughput and minimize the transmission slot delay in wireless Ad Hoc networks,an optimal topology-transparent transmission scheduling algorithm-multichannel Time-Spread Multiple Access(TSMA)is proposed.Further analysis is shown that the maximum degree is very sensitive to the network performance for a wireless Ad Hoc networks with N mobile nodes.Moreover,the proposed multichannel TSMA can improve the average throughput M times and decrease the average transmission slot delay M times,as compared with singlechannel TSMA when M channels are available.
Coordinated node scheduling for energy-conserving in large wireless sensor networks
SHI Gao-tao; LIAO Ming-hong; XU Wen-xu
2008-01-01
Aiming at developing a node scheduling protocol for sensor networks with fewer active nodes, we pro-pose a coordinated node scheduling protocol based on the presentation of a solution and its optimization to deter-mine whether a node is redundant. The proposed protocol can reduce the number of working nodes by turning off as many redundant nodes as possible without degrading the coverage and connectivity. The simulation result shows that our protocol outperforms the peer with respect to the working node number and dynamic coverage percentage.
Ryu, Minsoo
Time-Triggered Controller Area Network is widely accepted as a viable solution for real-time communication systems such as in-vehicle communications. However, although TTCAN has been designed to support both periodic and sporadic real-time messages, previous studies mostly focused on providing deterministic real-time guarantees for periodic messages while barely addressing the performance issue of sporadic messages. In this paper, we present an O(n2) scheduling algorithm that can minimize the maximum duration of exclusive windows occupied by periodic messages, thereby minimizing the worst-case scheduling delays experienced by sporadic messages.
Modified Opportunistic Deficit Round Robin Scheduling for improved QOS in IEEE 802.16 WBA networks
Prof. P.V.G.D. Prasad Reddy; C. Kalyana Chakravarthy
2009-01-01
Packet and flow scheduling algorithms for WiMAX has been a topic of interest for a long time since the very inception of WiMAX networks. WiMAX offers advantages particularly in terms of Quality of service it offers over a longer range at the MAC level. In our work, we propose two credit based scheduling schemes one in which completed flows distributes the left over credits equally to all higher priority uncompleted flows(ODRREDC) and another in which completed flows give away all the excess c...
Xiang Yan
2013-01-01
Full Text Available This paper addresses the optimal bandwidth scheduling problem for a double-layer networked learning control system (NLCS. To deal with this issue, auction mechanism is employed, and a dynamic bandwidth scheduling methodology is proposed to allocate the bandwidth for each subsystem. A noncooperative game fairness model is formulated, and the utility function of subsystems is designed. Under this framework, estimation of distribution algorithm (EDA is used to obtain Nash equilibrium for NLCS. Finally, simulation and experimental results are given to demonstrate the effectiveness of the proposed approach.
无
2007-01-01
Most of current wireless packet scheduling algorithms aim at resource allocation as fairly as possible or maximizing throughput. This paper proposed a new packet scheduling algorithm that aims at satisfying delay requirement and is the improvement of earliest due first (EDF) algorithm in wired networks. The main idea is to classify the packets based on their delay bound, scheduling the most "urgent" class of user and the users that have the best channel condition with higher priority. This algorithm can easily integrate with common buffer management algorithms, when buffer management algorithm cannot accept new arrival packets, try to modify scheduling policy. Packet scheduling algorithms in multiple bottleneck wireless networks were also discussed. A new variable multi-hop factor was defined to estimate the congestion situation (including channel condition) of future hops.Multi-hop factor can be integrated into packet scheduling algorithms as assistant and supplement to improve its performance in multi-bottleneck wireless networks.
A HYBRID GENETIC ALGORITHM-NEURAL NETWORK APPROACH FOR PRICING CORES AND REMANUFACTURED CORES
M. Seidi
2012-01-01
Full Text Available
ENGLISH ABSTRACT:Sustainability has become a major issue in most economies, causing many leading companies to focus on product recovery and reverse logistics. Remanufacturing is an industrial process that makes used products reusable. One of the important aspects in both reverse logistics and remanufacturing is the pricing of returned and remanufactured products (called cores. In this paper, we focus on pricing the cores and remanufactured cores. First we present a mathematical model for this purpose. Since this model does not satisfy our requirements, we propose a simulation optimisation approach. This approach consists of a hybrid genetic algorithm based on a neural network employed as the fitness function. We use automata learning theory to obtain the learning rate required for training the neural network. Numerical results demonstrate that the optimal value of the acquisition price of cores and price of remanufactured cores is obtained by this approach.
AFRIKAANSE OPSOMMING: Volhoubaarheid het ‘n belangrike saak geword in die meeste ekonomieë, wat verskeie maatskappye genoop het om produkherwinning en omgekeerde logistiek te onder oë te neem. Hervervaardiging is ‘n industriële proses wat gebruikte produkte weer bruikbaar maak. Een van die belangrike aspekte in beide omgekeerde logistiek en hervervaardiging is die prysbepaling van herwinne en hervervaardigde produkte. Hierdie artikel fokus op die prysbepalingsaspekte by wyse van ‘n wiskundige model.
Boivin, Rémi
2014-03-01
Illegal drug prices are extremely high, compared to similar goods. There is, however, considerable variation in value depending on place, market level and type of drugs. A prominent framework for the study of illegal drugs is the "risks and prices" model (Reuter & Kleiman, 1986). Enforcement is seen as a "tax" added to the regular price. In this paper, it is argued that such economic models are not sufficient to explain price variations at country-level. Drug markets are analysed as global trade networks in which a country's position has an impact on various features, including illegal drug prices. This paper uses social network analysis (SNA) to explain price markups between pairs of countries involved in the trafficking of illegal drugs between 1998 and 2007. It aims to explore a simple question: why do prices increase between two countries? Using relational data from various international organizations, separate trade networks were built for cocaine, heroin and cannabis. Wholesale price markups are predicted with measures of supply, demand, risks of seizures, geographic distance and global positioning within the networks. Reported prices (in $US) and purchasing power parity-adjusted values are analysed. Drug prices increase more sharply when drugs are headed to countries where law enforcement imposes higher costs on traffickers. The position and role of a country in global drug markets are also closely associated with the value of drugs. Price markups are lower if the destination country is a transit to large potential markets. Furthermore, price markups for cocaine and heroin are more pronounced when drugs are exported to countries that are better positioned in the legitimate world-economy, suggesting that relations in legal and illegal markets are directed in opposite directions. Consistent with the world-system perspective, evidence is found of coherent world drug markets driven by both local realities and international relations. Copyright © 2013 Elsevier B
Subono .
2016-04-01
Full Text Available ZigBee applications of IEEE 802.15.4 Wireless Sensor Network (WSN with Low Rate Wireless Personal Area Network (LR-WPAN can be integrated with e-health technology Wireless Body Area Network (WBAN. WBAN are small size and can communicate quickly making it easier for people to obtain information accurately.WBAN has a variety of functions that can help human life. It can be used in the e-health, military and sports. WBAN has the potential to be the future of wireless communication solutions. WBAN use battery as its primary power source. WBAN has limited energy and must be able to save energy consumption in order to operate for a long time. In this study, we propose a method of time scheduling called cycle sleep period (CSP as WBAN solutions to save energy and improve energy efficiency. The CSP method is implemented in the real hardware testbed using sensor e-health includes temperature body and current sensor. We compared the performance of CSP method with duty cycle management (DCM time scheduling-based and without using time scheduling.From the measurement results, our proposed idea has decreasingenergy consumption. Keywords: WSN, LR-WPAN, WBAN, e-health, Time Scheduling
Data Mining on Romanian Stock Market Using Neural Networks for Price Prediction
Magdalena Daniela NEMES
2013-01-01
Full Text Available Predicting future prices by using time series forecasting models has become a relevant trading strategy for most stock market players. Intuition and speculation are no longer reliable as many new trading strategies based on artificial intelligence emerge. Data mining represents a good source of information, as it ensures data processing in a convenient manner. Neural networks are considered useful prediction models when designing forecasting strategies. In this paper we present a series of neural networks designed for stock exchange rates forecasting applied on three Romanian stocks traded on the Bucharest Stock Exchange (BSE. A multistep ahead strategy was used in order to predict short-time price fluctuations. Later, the findings of our study can be integrated with an intelligent multi-agent system model which uses data mining and data stream processing techniques for helping users in the decision making process of buying or selling stocks.
Yongtu Liang
2014-01-01
Full Text Available This paper presents the new software which specifically developed based on Visual Studio 2010 for Daqing Oilfield China includes the most complex light hydrocarbon pipeline network system in Asia, has become a powerful auxiliary tool to manage field data, makes scheduling plans for batching operation, and optimizes pumping plans. Firstly, DMM for recording and managing field data is summarized. Then, the batch scheduling simulation module called SSM for the difficult batch-scheduling issues of the multiple-source pipeline network system is introduced. Finally, SOM, that is Scheduling Optimization Module, is indicated for solving the problem of the pumps being started up/shut-down frequently.
SELFLESS DISTRIBUTED CREDIT BASED SCHEDULING FOR IMPROVED QOS IN IEEE 802.16 WBA NETWORKS
C.Kalyana Chakravarthy
2009-11-01
Full Text Available Packet and flow scheduling algorithms for WiMAX has been a topic of interest for a long time since the very inception of WiMAX networks. WiMAX offers advantages particularly in terms of Quality of service it offers over a longer range at the MAC level. In our paper, we propose two credit based scheduling schemes one in which completed flows distributes the left over credits equally to all higher priority flows(FDCBSS and another in which completed flows give away all the excess credits to the highest priority uncompleted flow(SDCBSS. Both the schemes are compatible with 802.16 MAC protocol and can efficiently serve real time bursty traffic with reduced latency and hence improved QOS for real time flows. We compare the two proposed schemes for their latency, bandwidth utilization and throughput for real time burst flows with the basic Deficit Round Robin scheduling scheme.
Ka-Shun Hung
2010-01-01
Full Text Available In target monitoring problem, it is generally assumed that the whole target object can be monitored by a single sensor if the target falls within its sensing range. Unfortunately, this assumption becomes invalid when the target object is very large that a sensor can only monitor part of it. In this paper, we study the perimeter coverage problem where the perimeter of a big object needs to be monitored, but each sensor can only cover a single continuous portion of the perimeter. We describe how to schedule the sensors so as to maximize the network lifetime in this problem. We formally prove that the perimeter coverage scheduling problem is NP-hard in general. However, polynomial time solution exists in some special cases. We further identify the sufficient conditions for a scheduling algorithm to be a 2-approximation solution to the general problem, and propose a simple distributed 2-approximation solution with a small message overhead.
A discrete multi-swarm optimizer for radio frequency identification network scheduling
陈瀚宁; 朱云龙
2014-01-01
Due to the effectiveness, simple deployment and low cost, radio frequency identification (RFID) systems are used in a variety of applications to uniquely identify physical objects. The operation of RFID systems often involves a situation in which multiple readers physically located near one another may interfere with one another’s operation. Such reader collision must be minimized to avoid the faulty or miss reads. Specifically, scheduling the colliding RFID readers to reduce the total system transaction time or response time is the challenging problem for large-scale RFID network deployment. Therefore, the aim of this work is to use a successful multi-swarm cooperative optimizer called PS2O to minimize both the reader-to-reader interference and total system transaction time in RFID reader networks. The main idea of PS2O is to extend the single population PSO to the interacting multi-swarm model by constructing hierarchical interaction topology and enhanced dynamical update equations. As the RFID network scheduling model formulated in this work is a discrete problem, a binary version of PS2O algorithm is proposed. With seven discrete benchmark functions, PS2O is proved to have significantly better performance than the original PSO and a binary genetic algorithm. PS2O is then used for solving the real-world RFID network scheduling problem. Numerical results for four test cases with different scales, ranging from 30 to 200 readers, demonstrate the performance of the proposed methodology.
Analysis of Hierarchical Diff-EDF Schedulability over Heterogeneous Real-Time Packet Networks
M. Saleh
2007-01-01
Full Text Available Packet networks are currently enabling the integration of traffic with a wide range of characteristics that extend from video traffic with stringent QoS requirements to the best-effort traffic requiring no guarantees. QoS guarantees can be provided in conventional packet networks by the use of proper packet scheduling algorithms. As a computer revolution, many scheduling algorithms have been proposed to provide different schemes of QoS guarantees with Earliest Deadline First (EDF as the most popular one. With EDF scheduling, all flows receive the same miss rate regardless of their traffic characteristics and deadlines. This makes the standard EDF algorithm unsuitable for situations in which the different flows have different miss rate requirements since in order to meet all miss rate requirements it is necessary to limit admissions so as to satisfy the flow with the most stringent miss rate requirements. In this paper, we propose a new priority assignment scheduling algorithm, Hierarchal Diff-EDF (Differentiate Earliest Deadline First, which can meet the real-time needs of these applications while continuing to provide best effort service to non-real time traffic. The Hierarchal Diff-EDF features a feedback control mechanism that detects overload conditions and modifies packet priority assignments accordingly. To examine our proposed scheduler model, we introduced our attempt to provide an exact analytical solution. The attempt showed that the solution was apparently very complicated due to the high interdependence between the system queues' service. Hence, the use of simulation techniques seems inevitable. The simulation results showed that the Hierarchical Diff-EDF achieved the minimum packet average delay when compared with both EDF and Diff-EDF schedulers.
Global path and bandwidth scheduling in inter-data-center IP/optical transport network
Zhao, Yang; Wang, Lei; Chen, Xue; Yang, Futao; Shi, Sheping; Wang, Huitao
2016-07-01
We propose a flow-oriented global path and bandwidth scheduling scheme for inter-data-center IP/optical network. To improve the throughput of network and reduce the mutual impact between flows, we allow each flow to be carried by a multi-path optical channel data unit (ODU) channel. In addition bandwidth is allocated to flows fairly according to weight. Simulation results reveal that compared to high-priority-first mechanism, the method proposed improves average bandwidth allocation ratio by about 15% and allocation fairness between flows by 30%. Furthermore, compared to pure IP network, router ports are significantly saved and network cost can be reduced by up to 40% with scheme proposed in unified controlled IP/optical network.
Huang, Shaojun; Wu, Qiuwei; Oren, Shmuel S.
2015-01-01
This paper presents the distribution locational mar- ginal pricing (DLMP) method through quadratic programming (QP) designed to alleviate the congestion that might occur in a distribution network with high penetration of flexible demands. In the DLMP method, the distribution system operator (DSO...... ensure that the central- ized DSO optimization and the decentralized aggregator optimi- zation converge. Case studies using a distribution network with high penetration of electric vehicles (EVs) and heat pumps (HPs) validate the equivalence of the two optimization setups, and the efficacy...
R.Muthu Selvi
2015-10-01
Full Text Available This paper presents a new approach to optimize the schedule of the variable length multimedia packets in Ad hoc networks using hybridized Genetic Algorithm (HGA.Existing algorithm called Virtual Deadline Scheduling (VDS attempts to guarantee m out of k job instances (consecutive packets in a real-time stream by their deadlines are serviced. VDS is capable of generating a feasible window constrained schedule that utilizes 100% of resources. However, when VDS either services a packet or switches to a new request period, it must update the corresponding virtual deadline. Updating the service constraints is a bottleneck for the algorithm which increases the time complexity. HGA overcomes the problem of updating the service constraints that leads to the increased time complexity. The packet length and the number of packets to be serviced are the two conflicting criteria which are affecting the throughput of scheduling. Using HGA, a trade off can be achieved between the packet length and the number of packets to be serviced. HGA produces an optimized schedule for the multimedia packets. Journals.
Robustness Results for Hierarchical Diff-EDF Scheduling upon Heterogeneous Real-Time Packet Networks
Moutaz Saleh
2007-01-01
Full Text Available Packet networks are currently enabling the integration of traffic with a wide range of characteristics that extend from video traffic with stringent QoS requirements to the best-effort traffic requiring no guarantees. QoS guarantees can be provided in conventional packet networks by the use of proper packet scheduling algorithms. As a computer revolution, many scheduling algorithms have been proposed to provide different schemes of QoS guarantees with Earliest Deadline First (EDF as the most popular one. With EDF scheduling, all flows receive the same miss rate regardless of their traffic characteristics and deadlines. This makes the standard EDF algorithm unsuitable for situations in which the different flows have different miss rate requirements since in order to meet all miss rate requirements it is necessary to limit admissions so as to satisfy the flow with the most stringent miss rate requirements. In this study, we propose a new priority assignment scheduling algorithm, Hierarchal Diff-EDF (Differentiate Earliest Deadline First, which can meet the real-time needs of these applications while continuing to provide best effort service to non-real time traffic. The Hierarchal Diff-EDF features a feedback control mechanism that detects overload conditions and modifies packet priority assignments accordingly.
AN EFFICIENT PACKET SCHEDULING ALGORITHM FOR 4G IP-BASED MOBILE NETWORKS
Hussaim Mohammed
2010-09-01
Full Text Available Next generation mobile networks are expected to provide seamless personal mobile communication and quality of service (QoS. Lossless handoff is a key issue for providing the QoS. This paper presents 4G node B Architecture, a two-layer downlink queuing model and proposes a scheduling mechanism for providing lossless handoff and QoS in mobile networks, which exploit IP as a transport technology for transferring datagrams between base stations and the high-speed downlink packet access (HSDPA at the radio layer. In order to reduce handoff packet dropping rate at the radio layer and packet forwarding rate at the IP layer and to provide high system performance, new scheduling algorithms are performed at both IP and radio layer, which exploit handoff priority scheduling principles and take into account buffer occupancy and channel conditions. Performance results obtained by computer simulation show that, by exploiting the downlink queuing model and scheduling algorithms, the system is able to provide low handoff packet dropping rate, low packet forwarding rate, and high downlink throughput.
Energy-Efficient Node Scheduling Method for Cooperative Target Tracking in Wireless Sensor Networks
Weirong Liu
2015-01-01
Full Text Available Using the sensor nodes to achieve target tracking is a challenging problem in resource-limited wireless sensor networks. The tracking nodes are usually required to consume much energy to improve the tracking performance. In this paper, an energy-efficient node scheduling method is proposed to minimize energy consumption while ensuring the tracking accuracy. Firstly, the Kalman-consensus filter is constructed to improve the tracking accuracy and predict the target position. Based on the predicted position, an adaptive node scheduling mechanism is utilized to adjust the sample interval and the number of active nodes dynamically. Rather than using traditional search algorithm, the scheduling problem is decomposed to decouple the sample interval and number of nodes. And the node index is mapped into real domain to get closed-form solution to decide the active nodes. Thus, the NP-complete nature is avoided in the proposed method. The proposed scheduling method can keep the tracking accuracy while minimizing energy consumption. Simulation results validate its effective performance for target tracking in wireless sensor networks.
Comparison between Different Scheduling Strategies by Using Cost239 Optical Network
Pooja Meena, Manish Shrivastava, Sushil Chaturvedi
2012-12-01
Full Text Available In this paper we present different demand policies in scheduled lightpath demand (SLDs .SLD is a demand for a set of lightpaths (connections, defined by a tuple (s,d,n,α,ω where s and d are the source and destination nodes of the lightpaths, n is the number of requested lightpaths α, ω and are the set-up and tear-down times of the lightpaths. The objective of this paper to increase resource utilization ratio by using channel reuse. In this paper we works on Cost 239 network by assigning the same channel to several lightpaths, by using different wavelengths which varies according to the time (set-up and tear-down.By comparison of demand policies which also depend upon time(set-up and tear-down every demand policy has own schedule. By using Cost 239 network we found the result which demand policy is effective and scheduled first and we compare each policy by using graphical representation and then find which policy is best for scheduling and increase the resource utilization .
Coordinated Scheduling and Power Control in Cloud-Radio Access Networks
Douik, Ahmed
2015-12-01
This paper addresses the joint coordinated scheduling and power control problem in cloud-enabled networks. Consider the downlink of a cloud-radio access network (CRAN), where the cloud is only responsible for the scheduling policy, power control, and synchronization of the transmit frames across the single-antenna base-stations (BS). The transmit frame consists of several time/frequency blocks, called power-zones (PZ). The paper considers the problem of scheduling users to PZs and determining their power levels (PL), by maximizing the weighted sum-rate under the practical constraints that each user cannot be served by more than one base-station, but can be served by one or more power-zones within each base-station frame. The paper solves the problem using a graph theoretical approach by introducing the joint scheduling and power control graph formed by several clusters, where each is formed by a set of vertices, representing the possible association of users, BSs, and PLs for one specific PZ. The problem is, then, formulated as a maximumweight clique problem, in which the weight of each vertex is the sum of the benefits of the individual associations belonging to that vertex. Simulation results suggest that the proposed crosslayer scheme provides appreciable performance improvement as compared to schemes from recent literature.
Adjacency Matrix Based Energy Efficient Scheduling using S-MAC Protocol in Wireless Sensor Networks
Singh, Shweta
2012-01-01
Communication is the main motive in any Networks whether it is Wireless Sensor Network, Ad-Hoc networks, Mobile Networks, Wired Networks, Local Area Network, Metropolitan Area Network, Wireless Area Network etc, hence it must be energy efficient. The main parameters for energy efficient communication are maximizing network lifetime, saving energy at the different nodes, sending the packets in minimum time delay, higher throughput etc. This paper focuses mainly on the energy efficient communication with the help of Adjacency Matrix in the Wireless Sensor Networks. The energy efficient scheduling can be done by putting the idle node in to sleep node so energy at the idle node can be saved. The proposed model in this paper first forms the adjacency matrix and broadcasts the information about the total number of existing nodes with depths to the other nodes in the same cluster from controller node. When every node receives the node information about the other nodes for same cluster they communicate based on the s...
Price-based Energy Control for V2G Networks in the Industrial Smart Grid
Rong Yu
2015-08-01
Full Text Available The energy crisis and global warming call for a new industrial revolution in production and distribution of renewable energy. Distributed power generation will be well developed in the new smart electricity distribution grid, in which robust power distribution will be the key technology. In this paper, we present a new vehicle-to-grid (V2G network for energy transfer, in which distributed renewable energy helps the power grid balance demand and supply. Plug-in hybrid electric vehicles (PHEVs will act as transporters of electricity for distributed renewable energy dispatching. We formulate and analyze the V2G network within the theoretical framework of complex network. We also employ the generalized synchronization method to study the dynamic behavior of V2G networks. Furthermore, we develop a new price-based energy control method to stimulate the PHEV's behavior of charging and discharging. Simulation results indicate that the V2G network can achieve synchronization and each region is able to balance energy supply and demand through price-based control.
Minimum-Energy Wireless Real-Time Multicast by Joint Network Coding and Scheduling Optimization
Guoping Tan
2015-01-01
Full Text Available For real-time multicast services over wireless multihop networks, to minimize the energy of transmissions with satisfying the requirements of a fixed data rate and high reliabilities, we construct a conflict graph based framework by joint optimizing network coding and scheduling. Then, we propose a primal-dual subgradient optimization algorithm by random sampling K maximal stable sets in a given conflict graph. This method transforms the NP-hard scheduling subproblem into a normal linear programming problem to obtain an approximate solution. The proposed algorithm only needs to adopt centralized technique for solving the linear programming problem while all of the other computations can be distributed. The simulation results show that, comparing with the existing algorithm, this algorithm can not only achieve about 20% performance gain, but also have better performance in terms of convergence and robustness.
Jaramillo, Juan Jose
2009-01-01
This paper studies the problem of congestion control and scheduling in ad hoc wireless networks that have to support a mixture of best-effort and real-time traffic. Optimization and stochastic network theory have been successful in designing architectures for fair resource allocation to meet long-term throughput demands. However, to the best of our knowledge, strict packet delay deadlines were not considered in this framework previously. In this paper, we propose for the first time a model for incorporating the quality of service (QoS) requirements of packets with deadlines in the optimization framework. The solution to the problem results in a joint congestion control and scheduling algorithm which fairly allocates resources to meet the fairness objectives of both elastic and inelastic flows, and per-packet delay requirements of inelastic flows.
Scheduling for Optimal Rate Allocation in Ad Hoc Networks With Heterogeneous Delay Constraints
Jaramillo, Juan Jose; Ying, Lei
2010-01-01
This paper studies the problem of scheduling in single-hop wireless networks with real-time traffic, where every packet arrival has an associated deadline and a minimum fraction of packets must be transmitted before the end of the deadline. Using optimization and stochastic network theory we propose a framework to model the quality of service (QoS) requirements under delay constraints. The model allows for fairly general arrival models with heterogeneous constraints. The framework results in an optimal scheduling algorithm which fairly allocates data rates to all flows while meeting long-term delay demands. We also prove that under a simplified scenario our solution translates into a greedy strategy that makes optimal decisions with low complexity.
Multi-operator collaboration for green cellular networks under roaming price consideration
Ghazzai, Hakim
2014-09-01
This paper investigates the collaboration between multiple mobile operators to optimize the energy efficiency of cellular networks. Our framework studies the case of LTE-Advanced networks deployed in the same area and owning renewable energy generators. The objective is to reduce the CO2 emissions of cellular networks via collaborative techniques and using base station sleeping strategy while respecting the network quality of service. Low complexity and practical algorithm is employed to achieve green goals during low traffic periods. Cooperation decision criteria are also established basing on derived roaming prices and profit gains of competitive mobile operators. Our numerical results show a significant save in terms of CO2 compared to the non-collaboration case and that cooperative mobile operator exploiting renewables are more awarded than traditional operators.
Matsypura, Dmytro
In this dissertation, I develop a new theoretical framework for the modeling, pricing analysis, and computation of solutions to electric power supply chains with power generators, suppliers, transmission service providers, and the inclusion of consumer demands. In particular, I advocate the application of finite-dimensional variational inequality theory, projected dynamical systems theory, game theory, network theory, and other tools that have been recently proposed for the modeling and analysis of supply chain networks (cf. Nagurney (2006)) to electric power markets. This dissertation contributes to the extant literature on the modeling, analysis, and solution of supply chain networks, including global supply chains, in general, and electric power supply chains, in particular, in the following ways. It develops a theoretical framework for modeling, pricing analysis, and computation of electric power flows/transactions in electric power systems using the rationale for supply chain analysis. The models developed include both static and dynamic ones. The dissertation also adds a new dimension to the methodology of the theory of projected dynamical systems by proving that, irrespective of the speeds of adjustment, the equilibrium of the system remains the same. Finally, I include alternative fuel suppliers, along with their behavior into the supply chain modeling and analysis framework. This dissertation has strong practical implications. In an era in which technology and globalization, coupled with increasing risk and uncertainty, complicate electricity demand and supply within and between nations, the successful management of electric power systems and pricing become increasingly pressing topics with relevance not only for economic prosperity but also national security. This dissertation addresses such related topics by providing models, pricing tools, and algorithms for decentralized electric power supply chains. This dissertation is based heavily on the following
无
2011-01-01
An energy-balanced multiple-sensor collaborative scheduling is proposed for maneuvering target tracking in wireless sensor networks (WSNs). According to the position of the maneuvering target, some sensor nodes in WSNs are awakened to form a sensor cluster for target tracking collaboratively. In the cluster, the cluster head node is selected to implement tracking task with changed sampling interval. The distributed interactive multiple model (IMM) filter is employed to estimate the target state. The estimat...
Energy-saving scheme based on downstream packet scheduling in ethernet passive optical networks
Zhang, Lincong; Liu, Yejun; Guo, Lei; Gong, Xiaoxue
2013-03-01
With increasing network sizes, the energy consumption of Passive Optical Networks (PONs) has grown significantly. Therefore, it is important to design effective energy-saving schemes in PONs. Generally, energy-saving schemes have focused on sleeping the low-loaded Optical Network Units (ONUs), which tends to bring large packet delays. Further, the traditional ONU sleep modes are not capable of sleeping the transmitter and receiver independently, though they are not required to transmit or receive packets. Clearly, this approach contributes to wasted energy. Thus, in this paper, we propose an Energy-Saving scheme that is based on downstream Packet Scheduling (ESPS) in Ethernet PON (EPON). First, we design both an algorithm and a rule for downstream packet scheduling at the inter- and intra-ONU levels, respectively, to reduce the downstream packet delay. After that, we propose a hybrid sleep mode that contains not only ONU deep sleep mode but also independent sleep modes for the transmitter and the receiver. This ensures that the energy consumed by the ONUs is minimal. To realize the hybrid sleep mode, a modified GATE control message is designed that involves 10 time points for sleep processes. In ESPS, the 10 time points are calculated according to the allocated bandwidths in both the upstream and the downstream. The simulation results show that ESPS outperforms traditional Upstream Centric Scheduling (UCS) scheme in terms of energy consumption and the average delay for both real-time and non-real-time packets downstream. The simulation results also show that the average energy consumption of each ONU in larger-sized networks is less than that in smaller-sized networks; hence, our ESPS is better suited for larger-sized networks.
Energy latency tradeoffs for medium access and sleep scheduling in wireless sensor networks
Gang, Lu
Wireless sensor networks are expected to be used in a wide range of applications from environment monitoring to event detection. The key challenge is to provide energy efficient communication; however, latency remains an important concern for many applications that require fast response. The central thesis of this work is that energy efficient medium access and sleep scheduling mechanisms can be designed without necessarily sacrificing application-specific latency performance. We validate this thesis through results from four case studies that cover various aspects of medium access and sleep scheduling design in wireless sensor networks. Our first effort, DMAC, is to design an adaptive low latency and energy efficient MAC for data gathering to reduce the sleep latency. We propose staggered schedule, duty cycle adaptation, data prediction and the use of more-to-send packets to enable seamless packet forwarding under varying traffic load and channel contentions. Simulation and experimental results show significant energy savings and latency reduction while ensuring high data reliability. The second research effort, DESS, investigates the problem of designing sleep schedules in arbitrary network communication topologies to minimize the worst case end-to-end latency (referred to as delay diameter). We develop a novel graph-theoretical formulation, derive and analyze optimal solutions for the tree and ring topologies and heuristics for arbitrary topologies. The third study addresses the problem of minimum latency joint scheduling and routing (MLSR). By constructing a novel delay graph, the optimal joint scheduling and routing can be solved by M node-disjoint paths algorithm under multiple channel model. We further extended the algorithm to handle dynamic traffic changes and topology changes. A heuristic solution is proposed for MLSR under single channel interference. In the fourth study, EEJSPC, we first formulate a fundamental optimization problem that provides tunable
An SPN analysis method for parallel scheduling in Ad Hoc networks
盛琳阳; 徐文超; 贾世楼
2004-01-01
In this paper, a new analytic method for modeling and evaluating mobile ad hoc networks (MANET)is proposed. Petri nets technique is introduced into MANET and a packet-flow parallel scheduling scheme is presented using Stochastic Petri Nets (SPN). The flowing of tokens is used in graphics mode to characterize dynamical features of sharing a single wireless channel. Through SPN reachability analysis and isomorphic continuous time Markov process equations, some network parameters, such as channel efficiency, one-hop transmission delay etc. , can be obtained. Compared with conventional performance evaluation methods, the above parameters are mathematical expressions instead of test results from a simulator.
Stochastic User Equilibrium Assignment in Schedule-Based Transit Networks with Capacity Constraints
Wangtu Xu
2012-01-01
Full Text Available This paper proposes a stochastic user equilibrium (SUE assignment model for a schedule-based transit network with capacity constraint. We consider a situation in which passengers do not have the full knowledge about the condition of the network and select paths that minimize a generalized cost function encompassing five components: (1 ride time, which is composed of in-vehicle and waiting times, (2 overload delay, (3 fare, (4 transfer constraints, and (5 departure time difference. We split passenger demands among connections which are the space-time paths between OD pairs of the network. All transit vehicles have a fixed capacity and operate according to some preset timetables. When the capacity constraint of the transit line segment is reached, we show that the Lagrange multipliers of the mathematical programming problem are equivalent to the equilibrium passenger overload delay in the congested transit network. The proposed model can simultaneously predict how passengers choose their transit vehicles to minimize their travel costs and estimate the associated costs in a schedule-based congested transit network. A numerical example is used to illustrate the performance of the proposed model.
Power Allocation and Pricing in Multi-User Relay Networks Using Stackelberg and Bargaining Games
Cao, Qian; Jing, Yindi
2012-01-01
This paper considers a multi-user single-relay wireless network, where the relay gets paid for helping the users forward signals, and the users pay to receive the relay service. We study the relay power allocation and pricing problems, and model the interaction between the users and the relay as a two-level Stackelberg game. In this game, the relay, modeled as the service provider and the leader of the game, sets the relay price to maximize its revenue; while the users are modeled as customers and the followers who buy power from the relay for higher transmission rates. We use a bargaining game to model the negotiation among users to achieve a fair allocation of the relay power. Based on the proposed fair relay power allocation rule, the optimal relay power price that maximizes the relay revenue is derived analytically. Simulation shows that the proposed power allocation scheme achieves higher network sum-rate and relay revenue than the even power allocation. Furthermore, compared with the sum-rate-optimal so...
End-to-End Network QoS via Scheduling of Flexible Resource Reservation Requests
Sharma, S.; Katramatos, D.; Yu, D.
2011-11-14
Modern data-intensive applications move vast amounts of data between multiple locations around the world. To enable predictable and reliable data transfer, next generation networks allow such applications to reserve network resources for exclusive use. In this paper, we solve an important problem (called SMR3) to accommodate multiple and concurrent network reservation requests between a pair of end-sites. Given the varying availability of bandwidth within the network, our goal is to accommodate as many reservation requests as possible while minimizing the total time needed to complete the data transfers. We first prove that SMR3 is an NP-hard problem. Then we solve it by developing a polynomial-time heuristic, called RRA. The RRA algorithm hinges on an efficient mechanism to accommodate large number of requests by minimizing the bandwidth wastage. Finally, via numerical results, we show that RRA constructs schedules that accommodate significantly larger number of requests compared to other, seemingly efficient, heuristics.
Simulation of heat exchanger network (HEN) and planning the optimum cleaning schedule
Sanaye, Sepehr [Energy Systems Improvement Laboratory, Mechanical Engineering Department, Iran University of Science and Technology (IUST), Narmak, Tehran 16488 (Iran, Islamic Republic of)]. E-mail: sepehr@iust.ac.ir; Niroomand, Behzad [Energy Systems Improvement Laboratory, Mechanical Engineering Department, Iran University of Science and Technology (IUST), Narmak, Tehran 16488 (Iran, Islamic Republic of)
2007-05-15
Modeling and simulation of heat exchanger networks for estimating the amount of fouling, variations in overall heat transfer coefficient, and variations in outlet temperatures of hot and cold streams has a significant effect on production analysis. In this analysis, parameters such as the exchangers' types and arrangements, their heat transfer surface areas, mass flow rates of hot and cold streams, heat transfer coefficients and variations of fouling with time are required input data. The main goal is to find the variations of the outlet temperatures of the hot and cold streams with time to plan the optimum cleaning schedule of heat exchangers that provides the minimum operational cost or maximum amount of savings. In this paper, the simulation of heat exchanger networks is performed by choosing an asymptotic fouling function. Two main parameters in the asymptotic fouling formation model, i.e. the decay time of fouling formation ({tau}) and the asymptotic fouling resistance (R{sub f}{sup {approx}}) were obtained from empirical data as input parameters to the simulation relations. These data were extracted from the technical history sheets of the Khorasan Petrochemical Plant to guaranty the consistency between our model outputs and the real operating conditions. The output results of the software program developed, including the variations with time of the outlet temperatures of the hot and cold streams, the heat transfer coefficient and the heat transfer rate in the exchangers, are presented for two case studies. Then, an objective function (operational cost) was defined, and the optimal cleaning schedule of the HEN (heat exchanger network) in the Urea and Ammonia units were found by minimizing the objective function using a numerical search method. Based on this minimization procedure, the decision was made whether a heat exchanger should be cleaned or continue to operate. The final result was the most cost effective plan for the HEN cleaning schedule. The
On the Interaction Between Multiple Paths and Wireless Mesh Networks Scheduler Approaches
Valeria Loscrì
2008-07-01
Full Text Available Multi-path routing allows building and use of multiple paths for routing between a source-destination pair. This paper investigates the problem of selecting multiple routing paths to provide better reliability and load balancing in wireless mesh networks with stationary nodes. Previous work has investigated the use of additional data redundancy to improve the throughput of the network. In these specific cases, node disjoint-ness property of the multiple paths is required. In this work we investigate multipath routing without packet duplication, and no disjointed paths for achieving better performance in terms of packet delivery rate and low delay. We propose a very simple reactive on-demand distance vector routing protocol. Multiple paths built through this approach are loop-free. In order to better exploit resources redundancy (with the term resources redundancy we mean the possibility to exploit more nodes to send data packets, it is our belief that a routing protocol cannot be independent of the MAC layer. For this reason, we evaluated our routing protocol on four different MAC approaches specifically designed for Wireless Mesh Networks (WMNs. Firstly, we implemented the Coordinated Distributed Scheduler scheme of the Std. IEEE 802.16. Secondly, since some parameters have been left unstandardized in this scheme, we proposed an enhanced version of the CDS, in which a simple and dynamic criterion has been designed to set one of these parameters. Furthermore, we proposed two different scheduling schemes called Randomized- MAC (R-MAC and Distributed Scheduling Scheme (DSS. We evaluated the impact of multiple paths in respect of the single path on all the scheduler schemes cited above. Results show as the simple routing approach is effective with every MAC protocol considered.
Fairness resource allocation and scheduling for IEEE 802.16 Mesh networks
Limin Peng
2010-06-01
Full Text Available The IEEE 802.16 standard provides a scheme for creating multi-hop relay networks, which can be deployed as a high speed wide area wireless network at low cost. Although the standard defines signaling mechanisms in mesh mode, however, it doesn’t specify wireless resource management in the protocol. In this paper, we address the problem of resource allocation with the goal of providing fairness access to wireless channel for all the nodes as well as high network throughput in IEEE 802.16 mesh networks. We first define node’s unsatisfactory index and throughput function. Then, a multi-objective programming formulation is proposed for optimizing network performance. Accordingly, a dynamic programming based resource allocation and scheduling algorithm is presented to provide an optimal resource allocation to achieve fairness among different nodes as well as high network throughput in IEEE 802.16 mesh networks. Simulation results show that our proposed algorithm significantly provides both fairness of channel access and optimal network throughput.
Variable scheduling to mitigate channel losses in energy-efficient body area networks.
Tselishchev, Yuriy; Boulis, Athanassios; Libman, Lavy
2012-11-02
We consider a typical body area network (BAN) setting in which sensor nodes send data to a common hub regularly on a TDMA basis, as defined by the emerging IEEE 802.15.6 BAN standard. To reduce transmission losses caused by the highly dynamic nature of the wireless channel around the human body, we explore variable TDMA scheduling techniques that allow the order of transmissions within each TDMA round to be decided on the fly, rather than being fixed in advance. Using a simple Markov model of the wireless links, we devise a number of scheduling algorithms that can be performed by the hub, which aim to maximize the expected number of successful transmissions in a TDMA round, and thereby significantly reduce transmission losses as compared with a static TDMA schedule. Importantly, these algorithms do not require a priori knowledge of the statistical properties of the wireless channels, and the reliability improvement is achieved entirely via shuffling the order of transmissions among devices, and does not involve any additional energy consumption (e.g., retransmissions). We evaluate these algorithms directly on an experimental set of traces obtained from devices strapped to human subjects performing regular daily activities, and confirm that the benefits of the proposed variable scheduling algorithms extend to this practical setup as well.
Task and Participant Scheduling of Trading Platforms in Vehicular Participatory Sensing Networks
Heyuan Shi
2016-11-01
Full Text Available The vehicular participatory sensing network (VPSN is now becoming more and more prevalent, and additionally has shown its great potential in various applications. A general VPSN consists of many tasks from task, publishers, trading platforms and a crowd of participants. Some literature treats publishers and the trading platform as a whole, which is impractical since they are two independent economic entities with respective purposes. For a trading platform in markets, its purpose is to maximize the profit by selecting tasks and recruiting participants who satisfy the requirements of accepted tasks, rather than to improve the quality of each task. This scheduling problem for a trading platform consists of two parts: which tasks should be selected and which participants to be recruited? In this paper, we investigate the scheduling problem in vehicular participatory sensing with the predictable mobility of each vehicle. A genetic-based trading scheduling algorithm (GTSA is proposed to solve the scheduling problem. Experiments with a realistic dataset of taxi trajectories demonstrate that GTSA algorithm is efficient for trading platforms to gain considerable profit in VPSN.
Task and Participant Scheduling of Trading Platforms in Vehicular Participatory Sensing Networks
Shi, Heyuan; Song, Xiaoyu; Gu, Ming; Sun, Jiaguang
2016-01-01
The vehicular participatory sensing network (VPSN) is now becoming more and more prevalent, and additionally has shown its great potential in various applications. A general VPSN consists of many tasks from task, publishers, trading platforms and a crowd of participants. Some literature treats publishers and the trading platform as a whole, which is impractical since they are two independent economic entities with respective purposes. For a trading platform in markets, its purpose is to maximize the profit by selecting tasks and recruiting participants who satisfy the requirements of accepted tasks, rather than to improve the quality of each task. This scheduling problem for a trading platform consists of two parts: which tasks should be selected and which participants to be recruited? In this paper, we investigate the scheduling problem in vehicular participatory sensing with the predictable mobility of each vehicle. A genetic-based trading scheduling algorithm (GTSA) is proposed to solve the scheduling problem. Experiments with a realistic dataset of taxi trajectories demonstrate that GTSA algorithm is efficient for trading platforms to gain considerable profit in VPSN. PMID:27916807
Modified Opportunistic Deficit Round Robin Scheduling for improved QOS in IEEE 802.16 WBA networks
Chakravarthy, C Kalyana
2009-01-01
Packet and flow scheduling algorithms for WiMAX has been a topic of interest for a long time since the very inception of WiMAX networks. WiMAX offers advantages particularly in terms of Quality of service it offers over a longer range at the MAC level. In our work, we propose two credit based scheduling schemes one in which completed flows distributes the left over credits equally to all higher priority uncompleted flows(ODRREDC) and another in which completed flows give away all the excess credits to the highest priority uncompleted flow(ODRRSDC). Both the schemes are compatible with 802.16 MAC protocol and can efficiently serve real time bursty traffic with reduced latency and hence improved QOS for real time flows. We compare the two proposed schemes for their latency, bandwidth utilization and throughput for real time burst flows with the opportunity based Deficit Round Robin scheduling scheme. While the ODRR scheduler focuses on reducing the credits for the flows with errors, our approach also distribute...
Variable Scheduling to Mitigate Channel Losses in Energy-Efficient Body Area Networks
Lavy Libman
2012-11-01
Full Text Available We consider a typical body area network (BAN setting in which sensor nodes send data to a common hub regularly on a TDMA basis, as defined by the emerging IEEE 802.15.6 BAN standard. To reduce transmission losses caused by the highly dynamic nature of the wireless channel around the human body, we explore variable TDMA scheduling techniques that allow the order of transmissions within each TDMA round to be decided on the fly, rather than being fixed in advance. Using a simple Markov model of the wireless links, we devise a number of scheduling algorithms that can be performed by the hub, which aim to maximize the expected number of successful transmissions in a TDMA round, and thereby significantly reduce transmission losses as compared with a static TDMA schedule. Importantly, these algorithms do not require a priori knowledge of the statistical properties of the wireless channels, and the reliability improvement is achieved entirely via shuffling the order of transmissions among devices, and does not involve any additional energy consumption (e.g., retransmissions. We evaluate these algorithms directly on an experimental set of traces obtained from devices strapped to human subjects performing regular daily activities, and confirm that the benefits of the proposed variable scheduling algorithms extend to this practical setup as well.
R.Muthu Selvi
2011-09-01
Full Text Available This paper presents a new approach to optimize the schedule of the variable length multimedia packets inAd hoc networks using hybridized Genetic Algorithm (HGA.Existing algorithm called Virtual DeadlineScheduling (VDS attempts to guarantee m out of k job instances (consecutive packets in a real-timestream by their deadlines are serviced. VDS is capable of generating a feasible window constrainedschedule that utilizes 100% of resources. However, when VDS either services a packet or switches to a newrequest period, it must update the corresponding virtual deadline. Updating the service constraints is abottleneck for the algorithm which increases the time complexity. HGA overcomes the problem of updatingthe service constraints that leads to the increased time complexity. The packet length and the number ofpackets to be serviced are the two conflicting criteria which are affecting the throughput of scheduling.Using HGA, a trade off can be achieved between the packet length and the number of packets to beserviced. HGA produces an optimized schedule for the multimedia packets. Journals
Task and Participant Scheduling of Trading Platforms in Vehicular Participatory Sensing Networks.
Shi, Heyuan; Song, Xiaoyu; Gu, Ming; Sun, Jiaguang
2016-11-28
The vehicular participatory sensing network (VPSN) is now becoming more and more prevalent, and additionally has shown its great potential in various applications. A general VPSN consists of many tasks from task, publishers, trading platforms and a crowd of participants. Some literature treats publishers and the trading platform as a whole, which is impractical since they are two independent economic entities with respective purposes. For a trading platform in markets, its purpose is to maximize the profit by selecting tasks and recruiting participants who satisfy the requirements of accepted tasks, rather than to improve the quality of each task. This scheduling problem for a trading platform consists of two parts: which tasks should be selected and which participants to be recruited? In this paper, we investigate the scheduling problem in vehicular participatory sensing with the predictable mobility of each vehicle. A genetic-based trading scheduling algorithm (GTSA) is proposed to solve the scheduling problem. Experiments with a realistic dataset of taxi trajectories demonstrate that GTSA algorithm is efficient for trading platforms to gain considerable profit in VPSN.
Energy-Efficient BOP-Based Beacon Transmission Scheduling in Wireless Sensor Networks
Kim, Eui-Jik; Youm, Sungkwan; Choi, Hyo-Hyun
Many applications in wireless sensor networks (WSNs) require the energy efficiency and scalability. Although IEEE 802.15.4/Zigbee which is being considered as general technology for WSNs enables the low duty-cycling with time synchronization of all the nodes in network, it still suffer from its low scalability due to the beacon frame collision. Recently, various algorithms to resolve this problem are proposed. However, their manners to implement are somewhat ambiguous and the degradation of energy/communication efficiency is serious by the additional overhead. This paper describes an Energy-efficient BOP-based Beacon transmission Scheduling (EBBS) algorithm. EBBS is the centralized approach, in which a resource-sufficient node called as Topology Management Center (TMC) allocates the time slots to transmit a beacon frame to the nodes and manages the active/sleep schedules of them. We also propose EBBS with Adaptive BOPL (EBBS-AB), to adjust the duration to transmit beacon frames in every beacon interval, adaptively. Simulation results show that by using the proposed algorithm, the energy efficiency and the throughput of whole network can be significantly improved. EBBS-AB is also more effective for the network performance when the nodes are uniformly deployed on the sensor field rather than the case of random topologies.
Energy-aware scheduling of surveillance in wireless multimedia sensor networks.
Wang, Xue; Wang, Sheng; Ma, Junjie; Sun, Xinyao
2010-01-01
Wireless sensor networks involve a large number of sensor nodes with limited energy supply, which impacts the behavior of their application. In wireless multimedia sensor networks, sensor nodes are equipped with audio and visual information collection modules. Multimedia contents are ubiquitously retrieved in surveillance applications. To solve the energy problems during target surveillance with wireless multimedia sensor networks, an energy-aware sensor scheduling method is proposed in this paper. Sensor nodes which acquire acoustic signals are deployed randomly in the sensing fields. Target localization is based on the signal energy feature provided by multiple sensor nodes, employing particle swarm optimization (PSO). During the target surveillance procedure, sensor nodes are adaptively grouped in a totally distributed manner. Specially, the target motion information is extracted by a forecasting algorithm, which is based on the hidden Markov model (HMM). The forecasting results are utilized to awaken sensor node in the vicinity of future target position. According to the two properties, signal energy feature and residual energy, the sensor nodes decide whether to participate in target detection separately with a fuzzy control approach. Meanwhile, the local routing scheme of data transmission towards the observer is discussed. Experimental results demonstrate the efficiency of energy-aware scheduling of surveillance in wireless multimedia sensor network, where significant energy saving is achieved by the sensor awakening approach and data transmission paths are calculated with low computational complexity.
Yogesh Y. Shinde,
2014-04-01
Full Text Available A sensor networked applications can be formed for critical applications where it could send the detected information to the user or to the other sink node. This message is often called as alarm message where it is indicating the current operational state of the system. An alarm needs to be broadcast to the other nodes as soon as possible,when a critical event (e.g., gas leak or fire occurs in the monitoring area and is detected by a sensor node, then, sensor nodes can inform users nearby to take some response to the event. The life of sensor nodes for event monitoring are expected to work for a long time without recharging their batteries, sleep scheduling method is always preferred during the monitoring process. Sleep scheduling could cause transmission delay because sender nodes should wait until receiver nodes are active and ready to receive the message. The delay could be important as the network scale increases. Hence, a delay-efficient sleep scheduling method needs to be designed to ensure low broadcasting delay from any node in the WSN.
Design and analysis of self-adapted task scheduling strategies in wireless sensor networks.
Guo, Wenzhong; Xiong, Naixue; Chao, Han-Chieh; Hussain, Sajid; Chen, Guolong
2011-01-01
In a wireless sensor network (WSN), the usage of resources is usually highly related to the execution of tasks which consume a certain amount of computing and communication bandwidth. Parallel processing among sensors is a promising solution to provide the demanded computation capacity in WSNs. Task allocation and scheduling is a typical problem in the area of high performance computing. Although task allocation and scheduling in wired processor networks has been well studied in the past, their counterparts for WSNs remain largely unexplored. Existing traditional high performance computing solutions cannot be directly implemented in WSNs due to the limitations of WSNs such as limited resource availability and the shared communication medium. In this paper, a self-adapted task scheduling strategy for WSNs is presented. First, a multi-agent-based architecture for WSNs is proposed and a mathematical model of dynamic alliance is constructed for the task allocation problem. Then an effective discrete particle swarm optimization (PSO) algorithm for the dynamic alliance (DPSO-DA) with a well-designed particle position code and fitness function is proposed. A mutation operator which can effectively improve the algorithm's ability of global search and population diversity is also introduced in this algorithm. Finally, the simulation results show that the proposed solution can achieve significant better performance than other algorithms.
Design and Analysis of Self-Adapted Task Scheduling Strategies in Wireless Sensor Networks
Sajid Hussain
2011-06-01
Full Text Available In a wireless sensor network (WSN, the usage of resources is usually highly related to the execution of tasks which consume a certain amount of computing and communication bandwidth. Parallel processing among sensors is a promising solution to provide the demanded computation capacity in WSNs. Task allocation and scheduling is a typical problem in the area of high performance computing. Although task allocation and scheduling in wired processor networks has been well studied in the past, their counterparts for WSNs remain largely unexplored. Existing traditional high performance computing solutions cannot be directly implemented in WSNs due to the limitations of WSNs such as limited resource availability and the shared communication medium. In this paper, a self-adapted task scheduling strategy for WSNs is presented. First, a multi-agent-based architecture for WSNs is proposed and a mathematical model of dynamic alliance is constructed for the task allocation problem. Then an effective discrete particle swarm optimization (PSO algorithm for the dynamic alliance (DPSO-DA with a well-designed particle position code and fitness function is proposed. A mutation operator which can effectively improve the algorithm’s ability of global search and population diversity is also introduced in this algorithm. Finally, the simulation results show that the proposed solution can achieve significant better performance than other algorithms.
Energy Efficient Routing and Node Activity Scheduling in the OCARI Wireless Sensor Network
Saoucene Mahfoudh
2010-08-01
Full Text Available Sensor nodes are characterized by a small size, a low cost, an advanced communication technology, but also a limited amount of energy. Energy efficient strategies are required in such networks to maximize network lifetime. In this paper, we focus on a solution integrating energy efficient routing and node activity scheduling. The energy efficient routing we propose, called EOLSR, selects the route and minimizes the energy consumed by an end-to-end transmission, while avoiding nodes with low residual energy. Simulation results show that EOLSR outperforms the solution selecting the route of minimum energy as well as the solution based on node residual energy. Cross-layering allows EOLSR to use information from the application layer or the MAC layer to reduce its overhead and increase network lifetime. Node activity scheduling is based on the following observation: the sleep state is the least power consuming state. So, to schedule node active and sleeping periods, we propose SERENA that colors all network nodes using a small number of colors, such that two nodes with the same color can transmit without interfering. The node color is mapped into a time slot during which the node can transmit. Consequently, each node is awake during its slot and the slots of its one-hop neighbors, and sleeps in the remaining time. We evaluate SERENA benefits obtained in terms of bandwidth, delay and energy. We also show how cross-layering with the application layer can improve the end-to-end delays for data gathering applications.
APPLYING ARTIFICIAL NEURAL NETWORK OPTIMIZED BY FIREWORKS ALGORITHM FOR STOCK PRICE ESTIMATION
Khuat Thanh Tung
2016-04-01
Full Text Available Stock prediction is to determine the future value of a company stock dealt on an exchange. It plays a crucial role to raise the profit gained by firms and investors. Over the past few years, many methods have been developed in which plenty of efforts focus on the machine learning framework achieving the promising results. In this paper, an approach based on Artificial Neural Network (ANN optimized by Fireworks algorithm and data preprocessing by Haar Wavelet is applied to estimate the stock prices. The system was trained and tested with real data of various companies collected from Yahoo Finance. The obtained results are encouraging.
Analysis of Cloud Network Management Using Resource Allocation and Task Scheduling Services
K.C. Okafor
2016-01-01
Full Text Available Network failure in cloud datacenter could result from inefficient resource allocation; scheduling and logical segmentation of physical machines (network constraints. This is highly undesirable in Distributed Cloud Computing Networks (DCCNs running mission critical services. Such failure has been identified in the University of Nigeria datacenter network situated in the south eastern part of Nigeria. In this paper, the architectural decomposition of a proposed DCCN was carried out while exploring its functionalities for grid performance. Virtualization services such as resource allocation and task scheduling were employed in heterogeneous server clusters. The validation of the DCCN performance was carried out using trace files from Riverbed Modeller 17.5 in order to ascertain the influence of virtualization on server resource pool. The QoS metrics considered in the analysis are: the service delay time, resource availability, throughput and utilization. From the validation analysis of the DCCN, the following results were obtained: average throughput (bytes/Sec for DCCN = 40.00%, DCell = 33.33% and BCube = 26.67%. Average resource availability response for DCCN = 38.46%, DCell = 33.33%, and BCube = 28.21%. DCCN density on resource utilization = 40% (when logically isolated and 60% (when not logically isolated. From the results, it was concluded that using virtualization in a cloud DataCenter servers will result in enhanced server performance offering lower average wait time even with a higher request rate and longer duration of resource use (service availability. By evaluating these recursive architectural designs for network operations, enterprises ready for Spine and leaf model could further develop their network resource management schemes for optimal performance.
Cognitive Mobile Virtual Network Operator: Investment and Pricing with Supply Uncertainty
Duan, Lingjie; Shou, Biying
2009-01-01
This paper presents the first analytical study of optimal investment and pricing decisions of a cognitive mobile virtual network operator (C-MVNO) under spectrum supply uncertainty. Compared with a traditional MVNO who often leases spectrum via long-term contracts, a C-MVNO can acquire spectrum dynamically in short-term by both sensing the empty ``spectrum holes'' of licensed bands and leasing from the spectrum owner. As a result, a C-MVNO can make flexible investment and pricing decisions to match the current demands of the secondary unlicensed users. Compared to dynamic spectrum leasing, spectrum sensing is typically cheaper, but the obtained useful spectrum amount is random due to primary licensed users' stochastic traffic. The C-MVNO needs to determine the optimal amounts of spectrum sensing and leasing by evaluating the trade-off between cost and uncertainty. The C-MVNO also needs to determine the optimal price to sell the spectrum to the secondary unlicensed users, taking into account wireless heterogen...
Forecasting Natural Gas Prices Using Wavelets, Time Series, and Artificial Neural Networks.
Junghwan Jin
Full Text Available Following the unconventional gas revolution, the forecasting of natural gas prices has become increasingly important because the association of these prices with those of crude oil has weakened. With this as motivation, we propose some modified hybrid models in which various combinations of the wavelet approximation, detail components, autoregressive integrated moving average, generalized autoregressive conditional heteroskedasticity, and artificial neural network models are employed to predict natural gas prices. We also emphasize the boundary problem in wavelet decomposition, and compare results that consider the boundary problem case with those that do not. The empirical results show that our suggested approach can handle the boundary problem, such that it facilitates the extraction of the appropriate forecasting results. The performance of the wavelet-hybrid approach was superior in all cases, whereas the application of detail components in the forecasting was only able to yield a small improvement in forecasting performance. Therefore, forecasting with only an approximation component would be acceptable, in consideration of forecasting efficiency.
Hybrid Scheduling/Signal-Level Coordination in the Downlink of Multi-Cloud Radio-Access Networks
Douik, Ahmed
2016-03-28
In the context of resource allocation in cloud- radio access networks, recent studies assume either signal-level or scheduling-level coordination. This paper, instead, considers a hybrid level of coordination for the scheduling problem in the downlink of a multi-cloud radio- access network, so as to benefit from both scheduling policies. Consider a multi-cloud radio access network, where each cloud is connected to several base-stations (BSs) via high capacity links, and therefore allows joint signal processing between them. Across the multiple clouds, however, only scheduling-level coordination is permitted, as it requires a lower level of backhaul communication. The frame structure of every BS is composed of various time/frequency blocks, called power- zones (PZs), and kept at fixed power level. The paper addresses the problem of maximizing a network-wide utility by associating users to clouds and scheduling them to the PZs, under the practical constraints that each user is scheduled, at most, to a single cloud, but possibly to many BSs within the cloud, and can be served by one or more distinct PZs within the BSs\\' frame. The paper solves the problem using graph theory techniques by constructing the conflict graph. The scheduling problem is, then, shown to be equivalent to a maximum- weight independent set problem in the constructed graph, in which each vertex symbolizes an association of cloud, user, BS and PZ, with a weight representing the utility of that association. Simulation results suggest that the proposed hybrid scheduling strategy provides appreciable gain as compared to the scheduling-level coordinated networks, with a negligible degradation to signal-level coordination.
Liu, Huanlin; Li, Yuan; Peng, Han; Huang, Jun; Kong, Deqian
2017-01-01
Resolving the optical multicast contention in optical switch node is an effective approach to improve the performance of elastic optical multicast switch. An optical node architecture integrating with output shared all-optical Orthogonal Frequency Division Multiplexing (OFDM) network coding technology and shared feedback fiber delay lines (FDLs) buffer is designed. And a time-frequency joint scheduling strategy (TFJSS) is proposed. In TFJSS, the maximal weighted independent set algorithm is used to select the output packets with no overlapping spectrum among the contending multicast packets. The remaining contention packets are compressed by OFDM network coding with all-optical XOR operation. Hence, the contention is avoided in spectrum domain by encoding the contending unicast/multicast packets and changing the carrier frequency of encoded packets. If the network coding cannot successfully resolve the contending packets, the shared feedback FDLs are called to address the contention in time domain. Compared with the existing node architecture and scheduling algorithm, the simulation results show that the proposed architecture and the TFJSS can reduce the packet loss probability with low delay largely.
TRADING-OFF CONSTRAINTS IN THE PUMP SCHEDULING OPTIMIZATION OF WATER DISTRIBUTION NETWORKS
Gencer Genço\\u011Flu
2016-01-01
Full Text Available Pumps are one of the essential components of water supply systems. Depending of the topography, a water supply system may completely rely on pumping. They may consume non-negligible amount of water authorities' budgets during operation. Besides their energy costs, maintaining the healthiness of pumping systems is another concern for authorities. This study represents a multi-objective optimization method for pump scheduling problem. The optimization objective contains hydraulic and operational constraints. Switching of pumps and usage of electricity tariff are assumed to be key factors for operational reliability and energy consumption and costs of pumping systems. The local optimals for systems operational reliability, energy consumptions and energy costs are investigated resulting from trading-off pump switch and electricity tariff constraints within given set of boundary conditions. In the study, a custom made program is employed that combines genetic algorithm based optimization module with hydraulic network simulation software -EPANET. Developed method is applied on the case study network; N8-3 pressure zone of the Northern Supply of Ankara (Turkey Water Distribution Network. This work offers an efficient method for water authorities aiming to optimize pumping schedules considering expenditures and operational reliability mutually.
Optimal Fair Scheduling in S-TDMA Sensor Networks for Monitoring River Plumes
Miguel-Angel Luque-Nieto
2016-01-01
Full Text Available Underwater wireless sensor networks (UWSNs are a promising technology to provide oceanographers with environmental data in real time. Suitable network topologies to monitor estuaries are formed by strings coming together to a sink node. This network may be understood as an oriented graph. A number of MAC techniques can be used in UWSNs, but Spatial-TDMA is preferred for fixed networks. In this paper, a scheduling procedure to obtain the optimal fair frame is presented, under ideal conditions of synchronization and transmission errors. The main objective is to find the theoretical maximum throughput by overlapping the transmissions of the nodes while keeping a balanced received data rate from each sensor, regardless of its location in the network. The procedure searches for all cliques of the compatibility matrix of the network graph and solves a Multiple-Vector Bin Packing (MVBP problem. This work addresses the optimization problem and provides analytical and numerical results for both the minimum frame length and the maximum achievable throughput.
Utility function based fair data scheduling algorithm for OFDM wireless network
Guo Kunqi; Sun Lixin; Jia Shilou
2007-01-01
A system model is formulated as the maximization of a total utility function to achieve fair downlink data scheduling in multiuser orthogonal frequency division multiplexing (OFDM) wireless networks. A dynamic subcarrier allocation algorithm (DSAA) is proposed, to optimize the system model. The subcarrier allocation decision is made by the proposed DSAA according to the maximum value of total utility function with respect to the queue mean waiting time. Simulation results demonstrate that compared to the conventional algorithms, the proposed algorithm has better delay performance and can provide fairness under different loads by using different utility functions.
Competitive closed-loop supply chain network design with price-dependent demands
Rezapour, Shabnam; Farahani, Reza Zanjirani; Fahimnia, Behnam
2015-01-01
Abstract This paper presents a bi-level model for the strategic reverse network design (upper level) and tactical/operational planning (lower level) of a closed-loop single-period supply chain operating in a competitive environment with price-dependent market demand. An existing supply chain (SC...... for the supply of new and remanufactured products. The performance behaviors of both SCs are evaluated with specific focus placed on investigating the impacts of the strategic facility location decisions of the new SC on the tactical/operational transport and inventory decisions of the overall network. The bi......) is involved in the manufacturing and distribution of new products, while the new (to-be-designed) rival SC can supply both new and remanufactured products. Competitions exist not only externally between the two chains supplying new products to the same market, but also internally in the new chain...
Green Cooperative Spectrum Sensing and Scheduling in Heterogeneous Cognitive Radio Networks
Celik, Abdulkadir
2016-09-12
In this paper, we consider heterogeneous cognitive radio networks (CRNs) comprising primary channels (PCs) with heterogeneous characteristics and secondary users (SUs) with various sensing and reporting qualities for different PCs. We first define the opportunity as the achievable total data rate and its cost as the energy consumption caused from sensing, reporting, and channel switching operations and formulate a joint spectrum discovery and energy efficiency objective to minimize the energy spent per unit of data rate. Then, a mixed integer nonlinear programming problem is formulated to determine: 1) the optimal subset of PCs to be scheduled for sensing; 2) the SU assignment set for each scheduled PC; and 3) sensing durations and detection thresholds of each SU on PCs it is assigned to sense. Thereafter, an equivalent convex framework is developed for specific instances of the above combinatorial problem. For comparison, optimal detection and sensing thresholds are also derived analytically under the homogeneity assumption. Based on these, a prioritized ordering heuristic is developed to order channels under the spectrum, energy, and spectrum-energy limited regimes. After that, a scheduling and assignment heuristic is proposed and is shown to perform very close to the exhaustive optimal solution. Finally, the behavior of the CRN is numerically analyzed under these regimes with respect to different numbers of SUs, PCs, and sensing qualities.
V. Sharma
2011-08-01
Full Text Available This study demonstrates the use of a high-performance feedback neural network optimizer based on a new idea of successive approximation for finding the hourly optimal release schedules of interconnected multi-reservoir power system in such a way to minimize the overall cost of thermal generations spanned over the planning period. The main advantages of the proposed neural network optimizer over the existing neural network optimization models are that no dual variables, penalty parameters or lagrange multipliers are required. This network uses a simple structure with the least number of state variables and has better asymptotic stability. For an arbitrarily chosen initial point, the trajectory of the network converges to an optimal solution of the convex nonlinear programming problem. The proposed optimizer has been tested on a nonlinear practical system consisting of a multi-chain cascade of four linked reservoir type hydro-plants and a number of thermal units represented by a single equivalent thermal power plant and so obtained results have been validated using conventional conjugate gradient method and genetic algorithm based approach.
Energy-Saving Traffic Scheduling in Hybrid Software Defined Wireless Rechargeable Sensor Networks.
Wei, Yunkai; Ma, Xiaohui; Yang, Ning; Chen, Yijin
2017-09-15
Software Defined Wireless Rechargeable Sensor Networks (SDWRSNs) are an inexorable trend for Wireless Sensor Networks (WSNs), including Wireless Rechargeable Sensor Network (WRSNs). However, the traditional network devices cannot be completely substituted in the short term. Hybrid SDWRSNs, where software defined devices and traditional devices coexist, will last for a long time. Hybrid SDWRSNs bring new challenges as well as opportunities for energy saving issues, which is still a key problem considering that the wireless chargers are also exhaustible, especially in some rigid environment out of the main supply. Numerous energy saving schemes for WSNs, or even some works for WRSNs, are no longer suitable for the new features of hybrid SDWRSNs. To solve this problem, this paper puts forward an Energy-saving Traffic Scheduling (ETS) algorithm. The ETS algorithm adequately considers the new characters in hybrid SDWRSNs, and takes advantage of the Software Defined Networking (SDN) controller's direct control ability on SDN nodes and indirect control ability on normal nodes. The simulation results show that, comparing with traditional Minimum Transmission Energy (MTE) protocol, ETS can substantially improve the energy efficiency in hybrid SDWRSNs for up to 20-40% while ensuring feasible data delay.
MULTIPATH VIRTUAL QUEUE MANAGEMENT SYSTEM FOR EFFECTIVE PACKET SCHEDULING IN MPLS NETWORKS
V. Ramachandran
2012-09-01
Full Text Available With the rapid development of communication and networking technologies VOIP has become an alternate to traditional telephony. These applications prefer timeliness in packet delivery. To perform load balancing, link utilization and to minimize the packet loss rate Multipath virtual Queue Management System for Effective Packet Scheduling in MPLS networks is proposed. The VoIP flows are dispersed into multiple available label switched paths to perform load balancing and link utilization. Virtual queues are maintained in all output ports to avoid queuing delay and HOL blocking. The proposed system ensures the arrival order of all the packets and plays back in the order of transmission. The performance of the proposed Virtual queuing system is compared with single path CSFQ queuing system with no virtual queue and Simulation results are proposed to show theefficiency of the proposed system.
Sleep-time sizing and scheduling in green passive optical networks
Elrasad, Amr
2012-08-01
Next-generation passive optical network (PON) has been widely considered as a cost-effective broadband access technology. With the ever-increasing power saving concern, energy efficiency has been an important issue for its operations. In this paper, we present a novel sleep time sizing and scheduling framework that satisfies power efficient bandwidth allocation in PONs. We consider the downstream links from an optical line terminal (OLT) to an optical network unit (ONU). The ONU has two classes of traffic, control and data. Control traffic are delay intolerant with higher priority than the data traffic. Closed form model for average ONU sleeping time and end-to-end data traffic delay are presented and evaluated. Our framework decouples the dependency between ONU sleeping time and the QoS of the traffic.
Monica,; 10.5121/ijcnc.2010.2511
2010-01-01
Rapid progress in microelectromechanical system (MEMS) and radio frequency (RF) design has enabled the development of low-power, inexpensive, and network-enabled microsensors. These sensor nodes are capable of capturing various physical information, such as temperature, pressure, motion of an object, etc as well as mapping such physical characteristics of the environment to quantitative measurements. A typical wireless sensor network (WSN) consists of hundreds to thousands of such sensor nodes linked by a wireless medium. In this paper, we present a comparative investigation of energy consumption for few commercially available chipsets such as TR1001, CC1000 and CC1010 based on different scheduling methods for two types of deployment strategies. We conducted our experiment within the OMNeT++ simulator.
Højgaard-Hansen, Kim; Madsen, Tatiana Kozlova; Schwefel, Hans-Peter
2012-01-01
The performance of wireless communication networks has been shown to have a strong location dependence. Measuring the performance while having accurate location information available makes it possible to generate performance maps. In this paper we propose a framework for the generation and use...... of such performance maps. We demonstrate how the framework can be used to reduce the retransmissions and to better utilise network resources when performing TCP-based file downloads in vehicular M2M communication scenarios. The approach works on top of a standard TCP stack hence has to map identified transmission...... intervals to predicted TCP data volumes. The file download optimisation is evaluated using extensive simulations comparing the TCP scheduling approach to a normal transfer. The performance map is generated by capturing round-trip time measurements and a threshold approach for the mean value for a given area...
Threshold Based Opportunistic Scheduling of Secondary Users in Underlay Cognitive Radio Networks
Song, Yao
2011-12-01
In underlay cognitive radio networks, secondary users can share the spectrum with primary users as long as the interference caused by the secondary users to primary users is below a certain predetermined threshold. It is reasonable to assume that there is always a large pool of secondary users trying to access the channel, which can be occupied by only one secondary user at a given time. As a result, a multi-user scheduling problem arises among the secondary users. In this thesis, by manipulating basic schemes based on selective multi-user diversity, normalized thresholding, transmission power control, and opportunistic round robin, we propose and analyze eight scheduling schemes of secondary users in an underlay cognitive radio set-up. The system performance of these schemes is quantified by using various performance metrics such as the average system capacity, normalized average feedback load, scheduling outage probability, and system fairness of access. In our proposed schemes, the best user out of all the secondary users in the system is picked to transmit at each given time slot in order to maximize the average system capacity. Two thresholds are used in the two rounds of the selection process to determine the best user. The first threshold is raised by the power constraint from the primary user. The second threshold, which can be adjusted by us, is introduced to reduce the feedback load. The overall system performance is therefore dependent on the choice of these two thresholds and the number of users in the system given the channel conditions for all the users. In this thesis, by deriving analytical formulas and presenting numerical examples, we try to provide insights of the relationship between the performance metrics and the involved parameters including two selection thresholds and the number of active users in the system, in an effort to maximize the average system capacity as well as satisfy the requirements of scheduling outage probability and
A Schedule-based Multi-channel MAC Protocol for Wireless Sensor Networks
Ilyoung Chong
2010-10-01
Full Text Available Due to the half-duplex property of the sensor radio and the broadcast nature of wireless medium, limited bandwidth remains a pressing issue for wireless sensor networks (WSNs. The design of multi-channel MAC protocols has attracted the interest of many researchers as a cost effective solution to meet the higher bandwidth demand for the limited bandwidth in WSN. In this paper, we present a scheduled-based multi-channel MAC protocol to improve network performance. In our protocol, each receiving node selects (schedules some timeslot(s, in which it may receive data from the intending sender(s. The timeslot selection is done in a conflict free manner, where a node avoids the slots that are already selected by others in its interference range. To minimize the conflicts during timeslot selection, we propose a unique solution by splitting the neighboring nodes into different groups, where nodes of a group may select the slots allocated to that group only. We demonstrate the effectiveness of our approach thorough simulations in terms of performance parameters such as aggregate throughput, packet delivery ratio, end-to-end delay, and energy consumption.
Low-Complexity Scheduling and Power Adaptation for Coordinated Cloud-Radio Access Networks
Douik, Ahmed
2017-07-17
In practical wireless systems, the successful implementation of resource allocation techniques strongly depends on the algorithmic complexity. Consider a cloud-radio access network (CRAN), where the central cloud is responsible for scheduling devices to the frames’ radio resources blocks (RRBs) of the single-antenna base-stations (BSs), adjusting the transmit power levels, and for synchronizing the transmit frames across the connected BSs. Previous studies show that the jointly coordinated scheduling and power control problem in the considered CRAN can be solved using an approach that scales exponentially with the number of BSs, devices, and RRBs, which makes the practical implementation infeasible for reasonably sized networks. This paper instead proposes a low-complexity solution to the problem, under the constraints that each device cannot be served by more than one BS but can be served by multiple RRBs within each BS frame, and under the practical assumption that the channel is constant during the duration of each frame. The paper utilizes graph-theoretical based techniques and shows that constructing a single power control graph is sufficient to obtain the optimal solution with a complexity that is independent of the number of RRBs. Simulation results reveal the optimality of the proposed solution for slow-varying channels, and show that the solution performs near-optimal for highly correlated channels.
An adaptive random search for short term generation scheduling with network constraints.
Marmolejo, J A; Velasco, Jonás; Selley, Héctor J
2017-01-01
This paper presents an adaptive random search approach to address a short term generation scheduling with network constraints, which determines the startup and shutdown schedules of thermal units over a given planning horizon. In this model, we consider the transmission network through capacity limits and line losses. The mathematical model is stated in the form of a Mixed Integer Non Linear Problem with binary variables. The proposed heuristic is a population-based method that generates a set of new potential solutions via a random search strategy. The random search is based on the Markov Chain Monte Carlo method. The main key of the proposed method is that the noise level of the random search is adaptively controlled in order to exploring and exploiting the entire search space. In order to improve the solutions, we consider coupling a local search into random search process. Several test systems are presented to evaluate the performance of the proposed heuristic. We use a commercial optimizer to compare the quality of the solutions provided by the proposed method. The solution of the proposed algorithm showed a significant reduction in computational effort with respect to the full-scale outer approximation commercial solver. Numerical results show the potential and robustness of our approach.
An Enhanced Feedback-Base Downlink Packet Scheduling Algorithm for Mobile TV in WIMAX Networks
Joseph Oyewale
2013-06-01
Full Text Available With high speed access network technology like WIMAX, there is the need for efficient management of radio resources where the throughput and Qos requirements for Multicasting Broadcasting Services (MBS for example TV are to be met. An enhanced feedback-base downlink Packet scheduling algorithm that can be used in IEEE 802.16d/e networks for mobile TV “one way traffic”(MBS is needed to support many users utilizing multiuser diversity of the broadband of WIMAX systems where a group of users(good/worst channels share allocated resources (bandwidth. This paper proposes a WIMAX framework feedback-base (like a channel-awareness downlink packet scheduling algorithm for Mobile TV traffics in IEEE806.16, in which network Physical Timing Slots (PSs resource blocks are allocated in a dynamic way to mobile TV subscribers based on the Channel State information (CSI feedback, and then considering users with worst channels with the aim of improving system throughput while system coverage is being guaranteed. The algorithm was examined by changing the PSs bandwidth allocation of the users and different number of users of a cell. Simulation results show our proposed algorithm performed better than other algorithms (blind algorithms in terms of improvement in system throughput performance. /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso
Energy efficient distributed cluster head scheduling scheme for two tiered wireless sensor network
G. Kannan
2015-07-01
Full Text Available Wireless Sensor Network (WSN provides a significant contribution in the emerging fields such as ambient intelligence and ubiquitous computing. In WSN, optimization and load balancing of network resources are critical concern to provide the intelligence for long duration. Since clustering the sensor nodes can significantly enhance overall system scalability and energy efficiency this paper presents a distributed cluster head scheduling (DCHS algorithm to achieve the network longevity in WSN. The major novelty of this work is that the network is divided into primary and secondary tiers based on received signal strength indication of sensor nodes from the base station. The proposed DCHS supports for two tier WSN architecture and gives suggestion to elect the cluster head nodes and gateway nodes for both primary and secondary tiers. The DCHS mechanism satisfies an ideal distribution of the cluster head among the sensor nodes and avoids frequent selection of cluster head, based on Received Signal Strength Indication (RSSI and residual energy level of the sensor nodes. Since the RSSI is the key parameter for this paper, the practical experiment was conducted to measure RSSI value by using MSP430F149 processor and CC2500 transceiver. The measured RSSI values were given input to the event based simulator to test the DCHS mechanism. The real time experimental study validated the proposed scheme for various scenarios.
Cui, Laizhong; Lu, Nan; Chen, Fu
2014-01-01
Most large-scale peer-to-peer (P2P) live streaming systems use mesh to organize peers and leverage pull scheduling to transmit packets for providing robustness in dynamic environment. The pull scheduling brings large packet delay. Network coding makes the push scheduling feasible in mesh P2P live streaming and improves the efficiency. However, it may also introduce some extra delays and coding computational overhead. To improve the packet delay, streaming quality, and coding overhead, in this paper are as follows. we propose a QoS driven push scheduling approach. The main contributions of this paper are: (i) We introduce a new network coding method to increase the content diversity and reduce the complexity of scheduling; (ii) we formulate the push scheduling as an optimization problem and transform it to a min-cost flow problem for solving it in polynomial time; (iii) we propose a push scheduling algorithm to reduce the coding overhead and do extensive experiments to validate the effectiveness of our approach. Compared with previous approaches, the simulation results demonstrate that packet delay, continuity index, and coding ratio of our system can be significantly improved, especially in dynamic environments. PMID:25114968
Laizhong Cui
2014-01-01
Full Text Available Most large-scale peer-to-peer (P2P live streaming systems use mesh to organize peers and leverage pull scheduling to transmit packets for providing robustness in dynamic environment. The pull scheduling brings large packet delay. Network coding makes the push scheduling feasible in mesh P2P live streaming and improves the efficiency. However, it may also introduce some extra delays and coding computational overhead. To improve the packet delay, streaming quality, and coding overhead, in this paper are as follows. we propose a QoS driven push scheduling approach. The main contributions of this paper are: (i We introduce a new network coding method to increase the content diversity and reduce the complexity of scheduling; (ii we formulate the push scheduling as an optimization problem and transform it to a min-cost flow problem for solving it in polynomial time; (iii we propose a push scheduling algorithm to reduce the coding overhead and do extensive experiments to validate the effectiveness of our approach. Compared with previous approaches, the simulation results demonstrate that packet delay, continuity index, and coding ratio of our system can be significantly improved, especially in dynamic environments.
Cui, Laizhong; Jiang, Yong; Wu, Jianping; Xia, Shutao
Most large-scale Peer-to-Peer (P2P) live streaming systems are constructed as a mesh structure, which can provide robustness in the dynamic P2P environment. The pull scheduling algorithm is widely used in this mesh structure, which degrades the performance of the entire system. Recently, network coding was introduced in mesh P2P streaming systems to improve the performance, which makes the push strategy feasible. One of the most famous scheduling algorithms based on network coding is R2, with a random push strategy. Although R2 has achieved some success, the push scheduling strategy still lacks a theoretical model and optimal solution. In this paper, we propose a novel optimal pull-push scheduling algorithm based on network coding, which consists of two stages: the initial pull stage and the push stage. The main contributions of this paper are: 1) we put forward a theoretical analysis model that considers the scarcity and timeliness of segments; 2) we formulate the push scheduling problem to be a global optimization problem and decompose it into local optimization problems on individual peers; 3) we introduce some rules to transform the local optimization problem into a classical min-cost optimization problem for solving it; 4) We combine the pull strategy with the push strategy and systematically realize our scheduling algorithm. Simulation results demonstrate that decode delay, decode ratio and redundant fraction of the P2P streaming system with our algorithm can be significantly improved, without losing throughput and increasing overhead.
Yu, Rong; Zhong, Weifeng; Xie, Shengli; Zhang, Yan; Zhang, Yun
2016-02-01
As the next-generation power grid, smart grid will be integrated with a variety of novel communication technologies to support the explosive data traffic and the diverse requirements of quality of service (QoS). Cognitive radio (CR), which has the favorable ability to improve the spectrum utilization, provides an efficient and reliable solution for smart grid communications networks. In this paper, we study the QoS differential scheduling problem in the CR-based smart grid communications networks. The scheduler is responsible for managing the spectrum resources and arranging the data transmissions of smart grid users (SGUs). To guarantee the differential QoS, the SGUs are assigned to have different priorities according to their roles and their current situations in the smart grid. Based on the QoS-aware priority policy, the scheduler adjusts the channels allocation to minimize the transmission delay of SGUs. The entire transmission scheduling problem is formulated as a semi-Markov decision process and solved by the methodology of adaptive dynamic programming. A heuristic dynamic programming (HDP) architecture is established for the scheduling problem. By the online network training, the HDP can learn from the activities of primary users and SGUs, and adjust the scheduling decision to achieve the purpose of transmission delay minimization. Simulation results illustrate that the proposed priority policy ensures the low transmission delay of high priority SGUs. In addition, the emergency data transmission delay is also reduced to a significantly low level, guaranteeing the differential QoS in smart grid.
D'Souza, P
2016-03-01
Tighter national budgets and escalating drug prices continue to present challenges for pharmaceutical market access strategies and societal cost of care. As pharmaceutical companies and medical governmental advisory organizations enter tougher negotiations, hospital trusts and other dispensary firms face barriers to receiving the best medical treatment, and as a result patient access is limited. The 2016 HealthNetwork Communications' Pharma Pricing & Market Access Europe meeting brought together pharmaceutical, medical governmental advisory and stakeholders and market access/pricing consultants, to encourage discussions and negotiations into how to improve the drug pricing system and consequential market access strategies while achieving the respective reimbursement and affordability objectives. Copyright 2016 Prous Science, S.A.U. or its licensors. All rights reserved.
Social Optimization and Pricing Policy in Cognitive Radio Networks with an Energy Saving Strategy
Shunfu Jin
2016-01-01
Full Text Available The rapid growth of wireless application results in an increase in demand for spectrum resource and communication energy. In this paper, we firstly introduce a novel energy saving strategy in cognitive radio networks (CRNs and then propose an appropriate pricing policy for secondary user (SU packets. We analyze the behavior of data packets in a discrete-time single-server priority queue under multiple-vacation discipline. With the help of a Quasi-Birth-Death (QBD process model, we obtain the joint distribution for the number of SU packets and the state of base station (BS via the Matrix-Geometric Solution method. We assess the average latency of SU packets and the energy saving ratio of system. According to a natural reward-cost structure, we study the individually optimal behavior and the socially optimal behavior of the energy saving strategy and use an optimization algorithm based on standard particle swarm optimization (SPSO method to search the socially optimal arrival rate of SU packets. By comparing the individually optimal behavior and the socially optimal behavior, we impose an appropriate admission fee to SU packets. Finally, we present numerical results to show the impacts of system parameters on the system performance and the pricing policy.
Chen, Miawjane; Yan, Shangyao; Wang, Sin-Siang; Liu, Chiu-Lan
2015-02-01
An effective project schedule is essential for enterprises to increase their efficiency of project execution, to maximize profit, and to minimize wastage of resources. Heuristic algorithms have been developed to efficiently solve the complicated multi-mode resource-constrained project scheduling problem with discounted cash flows (MRCPSPDCF) that characterize real problems. However, the solutions obtained in past studies have been approximate and are difficult to evaluate in terms of optimality. In this study, a generalized network flow model, embedded in a time-precedence network, is proposed to formulate the MRCPSPDCF with the payment at activity completion times. Mathematically, the model is formulated as an integer network flow problem with side constraints, which can be efficiently solved for optimality, using existing mathematical programming software. To evaluate the model performance, numerical tests are performed. The test results indicate that the model could be a useful planning tool for project scheduling in the real world.
Multi-Objective Scheduling of Electric Vehicles in Smart Distribution Network
Changhong Deng
2016-11-01
Full Text Available Due to the energy savings and environmental protection they provide, plug-in electric vehicles (PEVs are increasing in number quickly. Rapid development of PEVs brings new opportunities and challenges to the electricity distribution network’s dispatching. A high number of uncoordinated charging PEVs has significant negative impacts on the secure and economic operation of a distribution network. In this paper, a bi-level programming approach that coordinates PEVs’ charging with the network load and electricity price of the open market is presented. The major objective of the upper level model is to minimize the total network costs and the deviation of electric vehicle aggregators’ charging power and the equivalent power. The subsequent objective of the lower level model after the upper level decision is to minimize the dispatching deviation of the sum of PEVs’ charging power and their optimization charging power under the upper level model. An improved particle swarm optimization algorithm is used to solve the bi-level programming. Numerical studies using a modified IEEE 69-bus distribution test system including six electric vehicle aggregators verify the efficiency of the proposed model.
M.F. Sabahi
2013-12-01
Full Text Available In this paper, based on the game theory, an optimized resource management algorithm for cognitive radio networks has been presented. Considering the personal interests, each user selects its own desired utility function and competes for channel and power selection. This non-cooperative approach is controlled through an appropriate pricing method. We have shown that if the profit function in a cooperative potential game is used as the pricing function in a non-cooperative network, the game governing the non-cooperative network will also become potential and will thus converge to Nash equilibrium. If the network is designed based on the cooperation of the users, the existence of selfish users among them will make the network be unstable. Besides, it decreases resource utilization gain. Using the recommended pricing has been shown to equilibrate the network. In simulations, by studying parameters like sum-rate of network and its total interference, it is shown that the resource utilization will be improved. Simulation results show that the equilibrium points also enjoy some optimality criteria such as Pareto optimality.
A Study of Non-Neutral Networks with Usage-based Prices
Altman, E; Caron, S; Kesidis, G; Rojas-Mora, J; Wong, S
2010-01-01
Hahn and Wallsten wrote that network neutrality "usually means that broadband service providers charge consumers only once for Internet access, do not favor one content provider over another, and do not charge content providers for sending information over broadband lines to end users." In this paper we study the implications of non-neutral behaviors under a simple model of linear demand-response to usage-based prices. We take into account advertising revenues and consider both cooperative and non-cooperative scenarios. In particular, we model the impact of side-payments between service and content providers. We also consider the effect of service discrimination by access providers, as well as an extension of our model to non-monopolistic content providers.
A RBF neural network model with GARCH errors: Application to electricity price forecasting
Coelho, Leandro dos Santos [Industrial and Systems Engineering Graduate Program, PPGEPS, Pontifical Catholic University of Parana, Imaculada Conceicao, 1155, Zip code 80215-901, Curitiba, Parana (Brazil); Santos, Andre A.P. [Department of Statistics, Universidad Carlos III de Madrid, C/ Madrid, 126, 28903 Getafe, Madrid (Spain)
2011-01-15
In this article, we propose a nonlinear forecasting model based on radial basis function neural networks (RBF-NNs) with Gaussian activation functions and robust clustering algorithms to model the conditional mean and a parametric generalized autoregressive conditional heteroskedasticity (GARCH) specification to model the conditional volatility. Instead of calibrating the parameters of the RBF-NNs via numerical simulations, we propose an estimation procedure by which the number of basis functions, their corresponding widths and the parameters of the GARCH model are jointly estimated via maximum likelihood along with a genetic algorithm to maximize the likelihood function. We use this model to provide multi-step-ahead point and direction-of-change forecasts of the Spanish electricity pool prices. (author)
A real-time traffic scheduling algorithm in CDMA packet networks
Zan, Lei; Heijenk, Geert; El Zarki, Magda; Gong, K.; Niu, Z.
2003-01-01
The demands for multimedia and packet data services over wireless devices have increased over the past few years. The direct impact on performance makes scheduling for real-time traffic important. This paper presents a novel scheduling algorithm called fair channel-dependent scheduling which schedul
Interference-Aware Scheduling for Connectivity in MIMO Ad Hoc Multicast Networks
Jiang, Feng; Swindlehurst, A Lee
2012-01-01
We consider a multicast scenario involving an ad hoc network of co-channel MIMO nodes in which a source node attempts to share a streaming message with all nodes in the network via some pre-defined multi-hop routing tree. The message is assumed to be broken down into packets, and the transmission is conducted over multiple frames. Each frame is divided into time slots, and each link in the routing tree is assigned one time slot in which to transmit its current packet. We present an algorithm for determining the number of time slots and the scheduling of the links in these time slots in order to optimize the connectivity of the network, which we define to be the probability that all links can achieve the required throughput. In addition to time multiplexing, the MIMO nodes also employ beamforming to manage interference when links are simultaneously active, and the beamformers are designed with the maximum connectivity metric in mind. The effects of outdated channel state information (CSI) are taken into accoun...
Improved Hysteretic Noisy Chaotic Neural Network for Broadcast Scheduling Problem in WMNs
Ming Sun
2013-01-01
Full Text Available It has been proven that the noise-tuning-based hysteretic noisy chaotic neural network (NHNCNN can use the noise tuning factor to improve the optimization performance obviously at lower initial noise levels while can not at initial higher noise levels. In order to improve the optimization performance of the NHNCNN at initial higher noise levels, we introduce a new noise tuning factor into the activation function and propose an improved hysteretic noisy chaotic neural network (IHNCNN model. By regulating the value of the newly introduced noise tuning factor, both noise levels of the activation function and hysteretic dynamics in the IHNCNN can be adjusted to help to improve the global optimization ability as the initial noise amplitude is higher. As a result, the IHNCNN can exhibit better optimization performance at initial higher noise levels. In order to demonstrate the advantage of the IHNCNN over the NHNCNN, the IHNCNN combined with gradual expansion scheme (GES is applied to solve broadcast scheduling problem (BSP in wireless multihop networks (WMNs. The aim of BSP is to design an optimal time-division multiple-access (TDMA frame structure with minimal frame length and maximal channel utilization. Simulation results in BSP show the superiority of the IHNCNN.
Wake-on-a-Schedule: Energy-aware Communication in Wi-Fi Networks
PERKOVIC, T.
2014-02-01
Full Text Available Excessive energy consumption of mobile device Wi-Fi (IEEE 802.11x interface is limiting its operational time on batteries, and impacts total energy consumption of electronic devices. In recent years research community has invested great effort in better efficiency of energy consumption. However, there is still a space for improvement. Wi-Fi devices connected to the single AP (Access Point compete for the medium during data exchange. However, due to the performance anomaly in 802.11 networks, a low data rate device will force all other devices connected to the AP to communicate at low rate, which will increase the total energy consumption of these devices. Wake-on-a-Schedule algorithm is proposed reducing the energy consumption of devices placed in the area with the weaker signal by scheduling the data packets for each client on the server side which will not allow clients to compete for the Wi-Fi medium. Through extensive measurements we show that our algorithm can save up to 60% of energy consumption on the client side.
Performance Guarantee under Longest-Queue-First Schedule in Wireless Networks
Li, Bo; Xia, Ye
2011-01-01
Efficient link scheduling in a wireless network is challenging. Typical optimal algorithms require solving an NP-hard sub-problem. To meet the challenge, one stream of research focuses on finding simpler sub-optimal algorithms that have low complexity but high efficiency in practice. In this paper, we study the performance guarantee of one such scheduling algorithm, the Longest-Queue-First (LQF) algorithm. It is known that the LQF algorithm achieves the full capacity region, $\\Lambda$, when the interference graph satisfies the so-called local pooling condition. For a general graph $G$, LQF achieves (i.e., stabilizes) a part of the capacity region, $\\sigma^*(G) \\Lambda$, where $\\sigma^*(G)$ is the overall local pooling factor of the interference graph $G$ and $\\sigma^*(G) \\leq 1$. It has been shown later that LQF achieves a larger rate region, $\\Sigma^*(G) \\Lambda$, where $\\Sigma^ (G)$ is a diagonal matrix. The contribution of this paper is to describe three new achievable rate regions, which are larger than t...
Packet Scheduling in High-speed Networks Using Improved Weighted Round Robin
Guikai Liu
2014-03-01
Full Text Available A variety of applications with different QoS requirements are supported simultaneously in the high-speed packet-switched networks, packet scheduling algorithms play a critical role in guaranteeing the performance of routing and switching devices. This study presents a simple, fair, efficient and easily implementary scheduling algorithm, called Successive Minimal-weight Round Robin (SMRR. In each round, SMRR provides the same service opportunity, which is equivalent to the minimal weight of the current round, for all active data flows. On the basis of the concept of Latency-Rate (LR servers, we obtain the upper bound on the latency of SMRR and WRR (Weighted Round Robin respectively and the results indicate that SMRR makes a significant improvement on the latency bound in comparison to WRR. We also discuss the fairness and implementation complexity of SMRR and the theoretical analysis shows that SMRR preserves the good implementation complexity of O (1 with respect to the number of flows and has better fairness than WRR.
Modified weighted fair queuing for packet scheduling in mobile WiMAX networks
Satrya, Gandeva B.; Brotoharsono, Tri
2013-03-01
The increase of user mobility and the need for data access anytime also increases the interest in broadband wireless access (BWA). The best available quality of experience for mobile data service users are assured for IEEE 802.16e based users. The main problem of assuring a high QOS value is how to allocate available resources among users in order to meet the QOS requirement for criteria such as delay, throughput, packet loss and fairness. There is no specific standard scheduling mechanism stated by IEEE standards, which leaves it for implementer differentiation. There are five QOS service classes defined by IEEE 802.16: Unsolicited Grant Scheme (UGS), Extended Real Time Polling Service (ertPS), Real Time Polling Service (rtPS), Non Real Time Polling Service (nrtPS) and Best Effort Service (BE). Each class has different QOS parameter requirements for throughput and delay/jitter constraints. This paper proposes Modified Weighted Fair Queuing (MWFQ) scheduling scenario which was based on Weighted Round Robin (WRR) and Weighted Fair Queuing (WFQ). The performance of MWFQ was assessed by using above five QoS criteria. The simulation shows that using the concept of total packet size calculation improves the network's performance.
A Hybrid Neural Network and H-P Filter Model for Short-Term Vegetable Price Forecasting
Youzhu Li
2014-01-01
Full Text Available This paper is concerned with time series data for vegetable prices, which have a great impact on human’s life. An accurate forecasting method for prices and an early-warning system in the vegetable market are an urgent need in people’s daily lives. The time series price data contain both linear and nonlinear patterns. Therefore, neither a current linear forecasting nor a neural network can be adequate for modeling and predicting the time series data. The linear forecasting model cannot deal with nonlinear relationships, while the neural network model alone is not able to handle both linear and nonlinear patterns at the same time. The linear Hodrick-Prescott (H-P filter can extract the trend and cyclical components from time series data. We predict the linear and nonlinear patterns and then combine the two parts linearly to produce a forecast from the original data. This study proposes a structure of a hybrid neural network based on an H-P filter that learns the trend and seasonal patterns separately. The experiment uses vegetable prices data to evaluate the model. Comparisons with the autoregressive integrated moving average method and back propagation artificial neural network methods show that our method has higher accuracy than the others.
Fair data scheduling in OFDM wireless networks based on maximizing utility
无
2007-01-01
This paper proposes a joint layer scheme for fair downlink data scheduling in multiuser OFDM wireless networks. Based on the optimization model formulated as the maximization of total utility function with respect to the mean waiting time of user queue, we present an algorithm with low complexity for dynamic subcarrier allocation (DSA). The decision for subcarrier allocation was made according to delay utility function obtained by the algorithm that instantaneously estimated both channel condition and queue length using an exponentially weighted low-pass time window and pilot signals respectively. The complexity of algorithm was reduced by varying the length of the time window to make use of time diversity, which provided higher throughput ratio.Simulation results demonstrate that compared with the conventional approach, the proposed scheme achieves better performance and can significantly improve fairness among users, with very limited delay performance degradation by using a decreasing concave utility function when the traffic load increases.
Zhang, Cong; Xiong, Zhihua; Ye, Hao
2014-07-01
In system identification, a data set needs to be informative to guarantee that the identification criterion has a unique global minimum asymptotically and the parameter estimation is consistent. In this paper, we study the informativity of the data set in a multiple-input and multiple-output (MIMO) networked control system (NCS), which contains possible network-induced delays, packet dropout, transmission scheduling, or a combination of these factors in network transmission. Moreover, to guarantee the data set of this MIMO NCS to be informative, a group of conditions for network transmission and controller's proportional term are developed. Finally, simulation studies are given to illustrate the result.
Optimal Scheduling of Domestic Appliances via MILP
Zdenek Bradac
2014-12-01
Full Text Available This paper analyzes a consumption scheduling mechanism for domestic appliances within a home area network. The aim of the proposed scheduling is to minimize the total energy price paid by the consumer and to reduce power peaks in order to achieve a balanced daily load schedule. An exact and computationally efficient mixed-integer linear programming (MILP formulation of the problem is presented. This model is verified by several problem instances. Realistic scenarios based on the real price tariffs commercially available in the Czech Republic are calculated. The results obtained by solving the optimization problem are compared with a simulation of the ripple control service currently used by many domestic consumers in the Czech Republic.
Behavioural Responses and Network Effects of Time-varying Road Pricing
Van Amelsfort, D.H.
2009-01-01
Road pricing is a policy measure under consideration by many goverments and road authorities. Although objectives may be different any road pricing measure will impact the behaviour of travellers and the flow of traffic. In this research we specifically looked at the effects of road pricing measures
Thematic Research network for emergency and UnScheduled Treatment (TRUST: scoping the potential
Edwards Adrian
2008-01-01
Full Text Available Abstract Background To identify the benefits of a network in emergency and unscheduled care research, a six week scoping study was undertaken. Objectives were to: draw together stakeholders; identify and prioritise research topics; identify sites for recruitment to studies; and agree a research strategy for a network. Methods A workshop was held to discuss and agree a research strategy based on results from four activities: visits to established research centres in emergency and unscheduled care; a literature overview; interviews with stakeholders in a GP out-of-hours service; and an exploration of the potential for routine data to support research in emergency care. Results Participants attended the workshop from user groups, primary care, the ambulance service, social care, the national telephone based health helpline, the Welsh Assembly Government and the academic sector. Site visits identified opportunities for collaboration. Gaps in knowledge were identified concerning the effectiveness of alternative models of emergency care delivery. Interview data highlighted a lack of evidence related to the quality of out-of-hours provision of primary care. The All Wales Injury Surveillance System (AWISS was found to offer the potential to use routine data to support quantitative studies in emergency care. Three key issues emerged across all activities: working across boundaries; patient involvement; and triage. Conclusion The study included views from patient, provider, policy and academic perspectives and built the case for a research network in emergency care. Now funded, TRUST (Thematic Research network for emergency and UnScheduled Treatment will allow the development of research proposals, building of research teams and recruitment of sites and patients both in Wales and across the UK. It aims to address the imbalance between investment and research in this area and help support provision of 'the right care to the right people at the right time'.
Heping PAN; Imad HAIDAR; Siddhivinayak KULKARNI
2009-01-01
This paper documents a systematic investigation on the predictability of short-term trends of crude oil prices on a daily basis. In stark contrast with longer-term predic-tions of crude oil prices, short-term prediction with time horizons of 1-3 days posits an important problem that is quite different from what has been studied in the litera-ture. The problem of such short-term predicability is tackled through two aspects. The first is to examine the existence of linear or nonlinear dynamic processes in crude oil prices.This sub-problem is addressed with statistical analysis in-volving the Brock-Dechert-Scheinkman test for nonlinearity.The second aspect is to test the capability of artificial neu-ral networks (ANN) for modeling the implicit nonlinearity for prediction. Four experimental models are designed and tested with historical data: (1) using only the lagged returns of filtered crude oil prices as input to predict the returns of the next days; this is used as the benchmark, (2) using only the information set of filtered crude oil futures price as in-put, (3) combining the inputs from the benchmark and sec-ond models, and (4) combing the inputs from the benchmark model and the intermarket information. In order to filter out the noise in the original price data, the moving averages of prices are used for all the experiments. The results provided sufficient evidence to the predictability of crude oil prices using ANN with an out-of-sample hit rate of 80%, 70%, and 61% for each of the next three days' trends.
Train Stop Scheduling in a High-Speed Rail Network by Utilizing a Two-Stage Approach
Huiling Fu
2012-01-01
Full Text Available Among the most commonly used methods of scheduling train stops are practical experience and various “one-step” optimal models. These methods face problems of direct transferability and computational complexity when considering a large-scale high-speed rail (HSR network such as the one in China. This paper introduces a two-stage approach for train stop scheduling with a goal of efficiently organizing passenger traffic into a rational train stop pattern combination while retaining features of regularity, connectivity, and rapidity (RCR. Based on a three-level station classification definition, a mixed integer programming model and a train operating tactics descriptive model along with the computing algorithm are developed and presented for the two stages. A real-world numerical example is presented using the Chinese HSR network as the setting. The performance of the train stop schedule and the applicability of the proposed approach are evaluated from the perspective of maintaining RCR.
David, L.; Percebois, J
2002-09-01
The gas deregulation process implies crucial choices concerning access to transportation networks. These choices deal with the nature, the structure and the level of access fees. This paper proposes an evaluation of different systems implemented both in Europe and North America, in relation to normative pricing references. The rules according to which shippers can buy or sell capacity represent another kind of choice that Regulators have to make. This paper proposes a simple model which demonstrates that secondary market prices should not be subject to a cap and emphasizes the need of a 'use-it-or-lose-it' rule on this market. (authors)
Titus SUCIU
2013-01-01
In individual companies, price is one significant factor in achieving marketing success. In many purchase situations, price can be of great importance to customers. Marketers must establish pricing strategies that are compatible with the rest of the marketing mix. Management should decide whether to charge the same price to all similar buyers of identical quantities of a product (a one-price strategy) or to set different prices (a flexible price strategy). Many organizations, especially retai...
Titus SUCIU
2013-01-01
In individual companies, price is one significant factor in achieving marketing success. In many purchase situations, price can be of great importance to customers. Marketers must establish pricing strategies that are compatible with the rest of the marketing mix. Management should decide whether to charge the same price to all similar buyers of identical quantities of a product (a one-price strategy) or to set different prices (a flexible price strategy). Many organizations, especially retai...
Guiling Wu; Jianping Chen; Xinwang Li; Junfeng Chen
2003-01-01
A scheduling algorithm for the edge nodes of optical burst switching (OBS) networks is proposed to guarantee the delay re quirement of services with different CoS (Class of Service) and provide lower burst loss ratio at the same time. The performance of edge nodes based on the proposed algorithm is presented.
Zand, Pouria; Chatterjea, Supriyo; Ketema, Jeroen; Havinga, Paul
2012-01-01
Current wireless standards and protocols for industrial applications, such as WirelessHART and ISA100.11a, typically use centralized network man-agement for communication scheduling and route establishment. However, due to their centralized nature, these protocols have difficulty coping with dynamic
Shim, Kyusung; Do, Nhu Tri; An, Beongku
2017-01-01
In this paper, we study the physical layer security (PLS) of opportunistic scheduling for uplink scenarios of multiuser multirelay cooperative networks. To this end, we propose a low-complexity, yet comparable secrecy performance source relay selection scheme, called the proposed source relay selection (PSRS) scheme. Specifically, the PSRS scheme first selects the least vulnerable source and then selects the relay that maximizes the system secrecy capacity for the given selected source. Additionally, the maximal ratio combining (MRC) technique and the selection combining (SC) technique are considered at the eavesdropper, respectively. Investigating the system performance in terms of secrecy outage probability (SOP), closed-form expressions of the SOP are derived. The developed analysis is corroborated through Monte Carlo simulation. Numerical results show that the PSRS scheme significantly improves the secure ability of the system compared to that of the random source relay selection scheme, but does not outperform the optimal joint source relay selection (OJSRS) scheme. However, the PSRS scheme drastically reduces the required amount of channel state information (CSI) estimations compared to that required by the OJSRS scheme, specially in dense cooperative networks. PMID:28212286
A new and efficient adaptive scheduling packets for the uplink traffic in WiMAX networks
Teixeira Marcio
2011-01-01
Full Text Available Abstract In this article, an adaptive scheduling packets algorithm for the uplink traffic in WiMAX networks is proposed. The proposed algorithm is designed to be completely dynamic, mainly in networks that use various modulation and coding schemes (MCSs. Using a cross-layer approach and the states of the uplink virtual queues in the base station, it was defined a new deadlines-based scheme, aiming at limiting the maximum delay to the real-time applications. Moreover, a method which interacts with the polling mechanisms of the base station was developed. This method controls the periodicity of sending unicast polling to the real-time and non-real-time service classes, in accordance with the quality of service requirements of the applications. The proposed algorithm was evaluated by means of modeling and simulation in environments where various MCSs were used and also in an environment where only one type of MCS was used. The simulations showed satisfactory results in both environments.
Kyusung Shim
2017-02-01
Full Text Available In this paper, we study the physical layer security (PLS of opportunistic scheduling for uplink scenarios of multiuser multirelay cooperative networks. To this end, we propose a low-complexity, yet comparable secrecy performance source relay selection scheme, called the proposed source relay selection (PSRS scheme. Specifically, the PSRS scheme first selects the least vulnerable source and then selects the relay that maximizes the system secrecy capacity for the given selected source. Additionally, the maximal ratio combining (MRC technique and the selection combining (SC technique are considered at the eavesdropper, respectively. Investigating the system performance in terms of secrecy outage probability (SOP, closed-form expressions of the SOP are derived. The developed analysis is corroborated through Monte Carlo simulation. Numerical results show that the PSRS scheme significantly improves the secure ability of the system compared to that of the random source relay selection scheme, but does not outperform the optimal joint source relay selection (OJSRS scheme. However, the PSRS scheme drastically reduces the required amount of channel state information (CSI estimations compared to that required by the OJSRS scheme, specially in dense cooperative networks.
Shim, Kyusung; Do, Nhu Tri; An, Beongku
2017-02-15
In this paper, we study the physical layer security (PLS) of opportunistic scheduling for uplink scenarios of multiuser multirelay cooperative networks. To this end, we propose a low-complexity, yet comparable secrecy performance source relay selection scheme, called the proposed source relay selection (PSRS) scheme. Specifically, the PSRS scheme first selects the least vulnerable source and then selects the relay that maximizes the system secrecy capacity for the given selected source. Additionally, the maximal ratio combining (MRC) technique and the selection combining (SC) technique are considered at the eavesdropper, respectively. Investigating the system performance in terms of secrecy outage probability (SOP), closed-form expressions of the SOP are derived. The developed analysis is corroborated through Monte Carlo simulation. Numerical results show that the PSRS scheme significantly improves the secure ability of the system compared to that of the random source relay selection scheme, but does not outperform the optimal joint source relay selection (OJSRS) scheme. However, the PSRS scheme drastically reduces the required amount of channel state information (CSI) estimations compared to that required by the OJSRS scheme, specially in dense cooperative networks.
Random and Periodic Sleep Schedules for Target Detection in Sensor Networks
Vaishali P. Sadaphal; Bijendra N. Jain
2008-01-01
We study random and periodic sleep schedules from the point of view of delay in detecting the target. We consider sleep schedules in which a sensor in "inactive" mode wakes up either randomly or periodically to detect presence of the target within its vicinity resulting into two sleep schedules: (a) random wake-up schedule, and (b) periodic wake-up schedule respectively. Specifically, we analyse and obtain for the random wake-up schedule the expected delay in detection, and the delay, such that with probability P, the delay is less than the computed value. For the periodic wake-up schedule we show that there exists an upper bound on the delay. Further we compute the average value of delay. We have shown that the theoretically computed averages and the upper bounds on the delay match with the simulation results for the random wake-up and periodic wake-up schedules.
R.P. Faber (Riemer)
2010-01-01
textabstractThis thesis studies price data and tries to unravel the underlying economic processes of why firms have chosen these prices. It focuses on three aspects of price setting. First, it studies whether the existence of a suggested price has a coordinating effect on the prices of firms. Second
Thien T. T. Le
2016-12-01
Full Text Available Currently, wireless body area networks (WBANs are effectively used for health monitoring services. However, in cases where WBANs are densely deployed, interference among WBANs can cause serious degradation of network performance and reliability. Inter-WBAN interference can be reduced by scheduling the communication links of interfering WBANs. In this paper, we propose an interference-aware traffic-priority-based link scheduling (ITLS algorithm to overcome inter-WBAN interference in densely deployed WBANs. First, we model a network with multiple WBANs as an interference graph where node-level interference and traffic priority are taken into account. Second, we formulate link scheduling for multiple WBANs as an optimization model where the objective is to maximize the throughput of the entire network while ensuring the traffic priority of sensor nodes. Finally, we propose the ITLS algorithm for multiple WBANs on the basis of the optimization model. High spatial reuse is also achieved in the proposed ITLS algorithm. The proposed ITLS achieves high spatial reuse while considering traffic priority, packet length, and the number of interfered sensor nodes. Our simulation results show that the proposed ITLS significantly increases spatial reuse and network throughput with lower delay by mitigating inter-WBAN interference.
Integrated coding-aware intra-ONU scheduling for passive optical networks with inter-ONU traffic
Li, Yan; Dai, Shifang; Wu, Weiwei
2016-12-01
Recently, with the soaring of traffic among optical network units (ONUs), network coding (NC) is becoming an appealing technique for improving the performance of passive optical networks (PONs) with such inter-ONU traffic. However, in the existed NC-based PONs, NC can only be implemented by buffering inter-ONU traffic at the optical line terminal (OLT) to wait for the establishment of coding condition, such passive uncertain waiting severely limits the effect of NC technique. In this paper, we will study integrated coding-aware intra-ONU scheduling in which the scheduling of inter-ONU traffic within each ONU will be undertaken by the OLT to actively facilitate the forming of coding inter-ONU traffic based on the global inter-ONU traffic distribution, and then the performance of PONs with inter-ONU traffic can be significantly improved. We firstly design two report message patterns and an inter-ONU traffic transmission framework as the basis for the integrated coding-aware intra-ONU scheduling. Three specific scheduling strategies are then proposed for adapting diverse global inter-ONU traffic distributions. The effectiveness of the work is finally evaluated by both theoretical analysis and simulations.
Julien Maheut
2013-07-01
Full Text Available Purpose: The purpose of this paper is to present an algorithm that solves the supply network configuration and operations scheduling problem in a mass customization company that faces alternative operations for one specific tool machine order in a multiplant context. Design/methodology/approach: To achieve this objective, the supply chain network configuration and operations scheduling problem is presented. A model based on stroke graphs allows the design of an algorithm that enumerates all the feasible solutions. The algorithm considers the arrival of a new customized order proposal which has to be inserted into a scheduled program. A selection function is then used to choose the solutions to be simulated in a specific simulation tool implemented in a Decision Support System. Findings and Originality/value: The algorithm itself proves efficient to find all feasible solutions when alternative operations must be considered. The stroke structure is successfully used to schedule operations when considering more than one manufacturing and supply option in each step. Research limitations/implications: This paper includes only the algorithm structure for a one-by-one, sequenced introduction of new products into the list of units to be manufactured. Therefore, the lotsizing process is done on a lot-per-lot basis. Moreover, the validation analysis is done through a case study and no generalization can be done without risk. Practical implications: The result of this research would help stakeholders to determine all the feasible and practical solutions for their problem. It would also allow to assessing the total costs and delivery times of each solution. Moreover, the Decision Support System proves useful to assess alternative solutions. Originality/value: This research offers a simple algorithm that helps solve the supply network configuration problem and, simultaneously, the scheduling problem by considering alternative operations. The proposed system
Bocewicz Grzegorz
2017-06-01
Full Text Available The problems of designing supply networks and traffic flow routing and scheduling are the subject of intensive research. The problems encompass the management of the supply of a variety of goods using multi-modal transportation. This research also takes into account the various constraints related to route topology, the parameters of the available fleet of vehicles, order values, delivery due dates, etc. Assuming that the structure of a supply network, constrained by a transport network topology that determines its behavior, we develop a declarative model which would enable the analysis of the relationships between the structure of a supply network and its potential behavior resulting in a set of desired delivery-flows. The problem in question can be reduced to determining sufficient conditions that ensure smooth flow in a transport network with a fractal structure. The proposed approach, which assumes a recursive, fractal network structure, enables the assessment of alternative delivery routes and associated schedules in polynomial time. An illustrative example showing the quantitative and qualitative relationships between the morphological characteristics of the investigated supply networks and the functional parameters of the assumed delivery-flows is provided.
Javier Sandoval
2011-12-01
Full Text Available A review of the representative models of machine learning research applied to the foreign exchange rate and stock price prediction problem is conducted. The article is organized as follows: The first section provides a context on the definitions and importance of foreign exchange rate and stock markets. The second section reviews machine learning models for financial prediction focusing on neural networks, SVM and evolutionary methods. Lastly, the third section draws some conclusions.
A PRIORITY-BASED POLLING SCHEDULING ALGORITHM FOR ARBITRATION POLICY IN NETWORK ON CHIP
Bao Liyong; Zhao Dongfeng; Zhao Yifan
2012-01-01
A solution is imperatively expected to meet the efficient contention resolution schemes for managing simultaneous access requests to the communication resources on the Network on Chip (NoC).Based on the ideas of conflict-free transmission,priority-based service,and dynamic self-adaptation to loading,this paper presents a novel scheduling algorithm for Medium Access Control (MAC) in NoC with the researches of the communication structure features of 2D mesh.The algorithm gives priority to guarantee the Quality of Service (QoS) for local input port as well as dynamic adjustment of the performance of the other ports along with input load change.The theoretical model of this algorithm is established with Markov chain and probability generating function.Mathematical analysis is made on the mean queue length and the mean inquiry cyclic time of the system.Simulated experiments are conducted to test the accuracy of the model.It turns out that the findings from theoretical analysis correspond well with those from simulated experiments.Further more,the analytical findings of the system performance demonstrate that the algorithm enables effectively strengthen the fairness and stability of data transmissions in NoC.
ARQ-Aware Scheduling and Link Adaptation for Video Transmission over Mobile Broadband Networks
Victoria Sgardoni
2012-01-01
Full Text Available This paper studies the effect of ARQ retransmissions on packet error rate, delay, and jitter at the application layer for a real-time video transmission at 1.03 Mbps over a mobile broadband network. The effect of time-correlated channel errors for various Mobile Station (MS velocities is evaluated. In the context of mobile WiMAX, the role of the ARQ Retry Timeout parameter and the maximum number of ARQ retransmissions is taken into account. ARQ-aware and channel-aware scheduling is assumed in order to allocate adequate resources according to the level of packet error rate and the number of ARQ retransmissions required. A novel metric, namely, goodput per frame, is proposed as a measure of transmission efficiency. Results show that to attain quasi error free transmission and low jitter (for real-time video QoS, only QPSK 1/2 can be used at mean channel SNR values between 12 dB and 16 dB, while 16QAM 1/2 can be used below 20 dB at walking speeds. However, these modes are shown to result in low transmission efficiency, attaining, for example, a total goodput of 3 Mbps at an SNR of 14 dB, for a block lifetime of 90 ms. It is shown that ARQ retransmissions are more effective at higher MS speeds.
Hoan, Tran-Nhut-Khai; Hiep, Vu-Van; Koo, In-Soo
2016-03-31
This paper considers cognitive radio networks (CRNs) utilizing multiple time-slotted primary channels in which cognitive users (CUs) are powered by energy harvesters. The CUs are under the consideration that hardware constraints on radio devices only allow them to sense and transmit on one channel at a time. For a scenario where the arrival of harvested energy packets and the battery capacity are finite, we propose a scheme to optimize (i) the channel-sensing schedule (consisting of finding the optimal action (silent or active) and sensing order of channels) and (ii) the optimal transmission energy set corresponding to the channels in the sensing order for the operation of the CU in order to maximize the expected throughput of the CRN over multiple time slots. Frequency-switching delay, energy-switching cost, correlation in spectrum occupancy across time and frequency and errors in spectrum sensing are also considered in this work. The performance of the proposed scheme is evaluated via simulation. The simulation results show that the throughput of the proposed scheme is greatly improved, in comparison to related schemes in the literature. The collision ratio on the primary channels is also investigated.
Rama.S
2017-03-01
Full Text Available Project planning is the important task in many areas like construction, resource allocation and many. A sequence of activities has to be performed to complete one task. Each activity has its unique processing time and all together to identify the critical activities which affect the completion of the project. In this paper the probabilistic and deterministic models to determine the project completion time and also the critical activities are considered. A case study on building construction project has been performed to demonstrate the application of the above said models. The two project scheduling namely PERT and CPM are used to determine numerically the different types of floating times of each activity and hence determined the critical path which plays an important role in the project completion time. Also a linear programing model has been developed to reduce the project completion time which optimize the resource allocation. To apply these techniques numerically the primary data from a housing project company in a metropolitan city has been taken, the network diagram of the activities involved in the building construction project has been drawn and the results are tabulated.
Fattahi, Mohammad; Govindan, Kannan
2017-01-01
with different quality levels are assumed dependent on offered acquisition prices to customer zones. A uniform distribution function defines the expected price of each customer zone for one unit of each used product. Using two-stage stochastic programming, a mixed-integer linear programming model is proposed...
Wong WilliamK
2009-01-01
Full Text Available Designing scheduling algorithms at the medium access control (MAC layer relies on a variety of parameters including quality of service (QoS requirements, resource allocation mechanisms, and link qualities from the corresponding layers. In this paper, we present an efficient cross-layer scheduling scheme, namely, Adaptive Token Bank Fair Queuing (ATBFQ algorithm, which is designed for packet scheduling and resource allocation in the downlink of OFDMA-based wireless 4G networks. This algorithm focuses on the mechanisms of efficiency and fairness in multiuser frequency-selective fading environments. We propose an adaptive method for ATBFQ parameter selection which integrates packet scheduling with resource mapping. The performance of the proposed scheme is compared to that of the round-robin (RR and the score-based (SB schedulers. It is observed from simulation results that the proposed scheme with adaptive parameter selection provides enhanced performance in terms of queuing delay, packet dropping rate, and cell-edge user performance, while the total sector throughput remains comparable. We further analyze and compare achieved fairness of the schemes in terms of different fairness indices available in literature.
2009-03-01
Full Text Available Designing scheduling algorithms at the medium access control (MAC layer relies on a variety of parameters including quality of service (QoS requirements, resource allocation mechanisms, and link qualities from the corresponding layers. In this paper, we present an efficient cross-layer scheduling scheme, namely, Adaptive Token Bank Fair Queuing (ATBFQ algorithm, which is designed for packet scheduling and resource allocation in the downlink of OFDMA-based wireless 4G networks. This algorithm focuses on the mechanisms of efficiency and fairness in multiuser frequency-selective fading environments. We propose an adaptive method for ATBFQ parameter selection which integrates packet scheduling with resource mapping. The performance of the proposed scheme is compared to that of the round-robin (RR and the score-based (SB schedulers. It is observed from simulation results that the proposed scheme with adaptive parameter selection provides enhanced performance in terms of queuing delay, packet dropping rate, and cell-edge user performance, while the total sector throughput remains comparable. We further analyze and compare achieved fairness of the schemes in terms of different fairness indices available in literature.
Hybrid Bandwidth Scheduling for CAN-based Networked Control Systems%CAN型网络化控制系统的混合带宽优化
白涛; 吴智铭
2007-01-01
A hybrid bandwidth scheduling scheme is proposed to improve the quality of service and the bandwidth utilization for the CAN-based networked control systems. It combines rate monotonic and improved round-robin scheme for both the realtime and non-real-time data. Moreover, considering the constraints of control performance and network schedulability, a heuristic branch and bound & genetic algorithm (GA) algorithm is presented for the control data to minimize their bandwidth occupancy and the jitter caused by improper scheduling. The residual bandwidth is allocated to non-real-time data by the proposed scale round-robin scheme such that their network loads are balanced.
Fluctuation of USA Gold Price - Revisited with Chaos-based Complex Network Method
Bhaduri, Susmita; Ghosh, Subhadeep
2016-01-01
We give emphasis on the use of chaos-based rigorous nonlinear technique called Visibility Graph Analysis, to study one economic time series - gold price of USA. This method can offer reliable results with fiinite data. This paper reports the result of such an analysis on the times series depicting the fluctuation of gold price of USA for the span of 25 years(1990 - 2013). This analysis reveals that a quantitative parameter from the theory can explain satisfactorily the real life nature of fluctuation of gold price of USA and hence building a strong database in terms of a quantitative parameter which can eventually be used for forecasting purpose.
Yuqing Yang
2015-09-01
Full Text Available With global conventional energy depletion, as well as environmental pollution, utilizing renewable energy for power supply is the only way for human beings to survive. Currently, distributed generation incorporated into a distribution network has become the new trend, with the advantages of controllability, flexibility and tremendous potential. However, the fluctuation of distributed energy resources (DERs is still the main concern for accurate deployment. Thus, a battery energy storage system (BESS has to be involved to mitigate the bad effects of DERs’ integration. In this paper, optimal scheduling strategies for BESS operation have been proposed, to assist with consuming the renewable energy, reduce the active power loss, alleviate the voltage fluctuation and minimize the electricity cost. Besides, the electric vehicles (EVs considered as the auxiliary technique are also introduced to attenuate the DERs’ influence. Moreover, both day-ahead and real-time operation scheduling strategies were presented under the consideration with the constraints of BESS and the EVs’ operation, and the optimization was tackled by a fuzzy mathematical method and an improved particle swarm optimization (IPSO algorithm. Furthermore, the test system for the proposed strategies is a real distribution network with renewable energy integration. After simulation, the proposed scheduling strategies have been verified to be extremely effective for the enhancement of the distribution network characteristics.
Ahangar, Reza Gharoie; Pournaghshband, Hassan
2010-01-01
In this paper, researchers estimated the stock price of activated companies in Tehran (Iran) stock exchange. It is used Linear Regression and Artificial Neural Network methods and compared these two methods. In Artificial Neural Network, of General Regression Neural Network method (GRNN) for architecture is used. In this paper, first, researchers considered 10 macro economic variables and 30 financial variables and then they obtained seven final variables including 3 macro economic variables and 4 financial variables to estimate the stock price using Independent components Analysis (ICA). So, we presented an equation for two methods and compared their results which shown that artificial neural network method is more efficient than linear regression method.
Al-Eryani, Yasser F.
2017-07-20
In this paper, the performance of two-way relaying (TWR) multiuser mixed radio frequency/free space optical (RF/FSO) relay networks with opportunistic user scheduling and asymmetric channel fading is studied. First, closed-form expressions for the exact outage probability, asymptotic (high signal-to-noise ration (SNR)) outage probability, and average ergodic channel capacity are derived assuming heterodyne detection (HD) scheme. Additionally, impacts of several system parameters including number of users, pointing errors, and atmospheric turbulence conditions on the overall network performance are investigated. All the theoretical results are validated by Monte-Carlo simulations. The results show that the TWR scheme almost doubles the network ergodic capacity compared to that of one-way relaying (OWR) scheme with the same outage performance. Additionally, the overall diversity order of the network is shown to be affected not only by the number of users, but it is also a function of the pointing error and atmospheric turbulence conditions.
Retail Pricing and Day-Ahead Demand Response in Smart Distribution Networks
GholamReza Yousefi
2014-03-01
Full Text Available This paper focuses on day-ahead (DA retailing for fixed and Time-of-Use (TOU price taker customers and DA real time pricing for active customers who participate in short-term markets. Customers’ response to the offered hourly prices are modeled using an hourly acceptance function which includes decreasing linear probability density functions based on the hourly minimum and maximum retail prices allowed by market regulators. Furthermore, the retailer offers to its active customers to participate in the DA demand response program and voluntary reduce their real time consumption for offered incentives. Numerical studies represent the effect of implementing demand response programs on the total benefit of retailing.
Marketing Planning, Pricing strategies, and The Use of Online Social Networks for Marketing in A SME
Bruno, Andrea
2013-01-01
The objectives of this dissertation are threefold. The dissertation is firstly aimed at recommending a practically useful marketing plan for Betterlanguages, a Nottingham based SME operating in the language services market. The recommendations for the internal and external analysis of the company are based on the academic tools outlined in the literature review. Second, the dissertation aims at offering suggestions concerning pricing strategy for Betterlanguages, by exploring the pricing l...
R. Avudaiammal
2009-01-01
Full Text Available Problem statement: An explosive growth of multimedia applications in internet has stressed the performance of routers. Hence managing Quality of Service (QoS enhancement of real-time multimedia applications over IP is a significant and demanding challenge. Approach: To address this issue, Bandwidth Adaptive Stratified Round Robin (BASRR packet scheduling algorithm has been proposed in this paper for enhancing quality of service of real-time multimedia applications. Embedded Network Processors (NP have recently emerged with flexibility and speed to reduce the stress of the router by effectively processing the packets. The main objective of this study was to implement the proposed packet scheduling algorithm in a Network Processor (NP based router for enhancing quality of service of real-time multimedia applications Results: The effectiveness of the BASRR algorithm has been verified by simulations using Intels IXP 2400 network processor. The results show that BASRR achieves about 71.25% reduction in jitter compared to SRR when the traffic has uniform distribution of real-time flows and non real-time flows. The reduction in average queuing delay is about 30% compared to SRR for all the types of traffic. Conclusion: The QoS for multimedia applications has been achieved by the proposed non-preemptive Bandwidth Adaptive Stratified Round Robin (BASRR scheduling algorithm and outperforms the three well-known scheduling algorithms including DRR, WDRR and SRR. The results showed that BASRR is efficient with per packet complexity of O(1 and provides better fairness and reduced delay.
Hitoshi FURUTA; Ken ISHIBASHI; Koichiro NAKATSU; Shun HOTTA
2008-01-01
The purpose of this research is to propose an early restoration for lifeline systems after earthquake disasters. The previous researches show that the optimization of the restoration schedule by using genetic algorithm (GA) is powerful. However, those are not considering the uncertain environment after earthquake disasters. The circumstances of the damage at devastated areas are very changeable due to the aftershock,fire disaster and bad weather. In addition, the restoring works may delay by unexpected accidents. Therefore,it is necessary to obtain the restoration schedule which has robustness, because the actual restoring works could not progress smoothly under the uncertain environment. GA considering uncertainty (GACU) can treat various uncertainties involved, but it is difficult to obtain the robust schedule. In this study, an attempt is made to develop a decision support system of the optimal restoration scheduling by using the improved GACU.
Sleep/wake scheduling scheme for minimizing end-to-end delay in multi-hop wireless sensor networks
Madani Sajjad
2011-01-01
Full Text Available Abstract We present a sleep/wake schedule protocol for minimizing end-to-end delay for event driven multi-hop wireless sensor networks. In contrast to generic sleep/wake scheduling schemes, our proposed algorithm performs scheduling that is dependent on traffic loads. Nodes adapt their sleep/wake schedule based on traffic loads in response to three important factors, (a the distance of the node from the sink node, (b the importance of the node's location from connectivity's perspective, and (c if the node is in the proximity where an event occurs. Using these heuristics, the proposed scheme reduces end-to-end delay and maximizes the throughput by minimizing the congestion at nodes having heavy traffic load. Simulations are carried out to evaluate the performance of the proposed protocol, by comparing its performance with S-MAC and Anycast protocols. Simulation results demonstrate that the proposed protocol has significantly reduced the end-to-end delay, as well as has improved the other QoS parameters, like average energy per packet, average delay, packet loss ratio, throughput, and coverage lifetime.
Shi, Binbin; Wei, Wei; Wang, Yihuai; Shu, Wanneng
2016-10-14
In high-density sensor networks, scheduling some sensor nodes to be in the sleep mode while other sensor nodes remain active for monitoring or forwarding packets is an effective control scheme to conserve energy. In this paper, a Coverage-Preserving Control Scheduling Scheme (CPCSS) based on a cloud model and redundancy degree in sensor networks is proposed. Firstly, the normal cloud model is adopted for calculating the similarity degree between the sensor nodes in terms of their historical data, and then all nodes in each grid of the target area can be classified into several categories. Secondly, the redundancy degree of a node is calculated according to its sensing area being covered by the neighboring sensors. Finally, a centralized approximation algorithm based on the partition of the target area is designed to obtain the approximate minimum set of nodes, which can retain the sufficient coverage of the target region and ensure the connectivity of the network at the same time. The simulation results show that the proposed CPCSS can balance the energy consumption and optimize the coverage performance of the sensor network.
Sefuba, Maria; Walingo, Tom; Takawira, Fambirai
2015-09-18
This paper presents an Energy Efficient Medium Access Control (MAC) protocol for clustered wireless sensor networks that aims to improve energy efficiency and delay performance. The proposed protocol employs an adaptive cross-layer intra-cluster scheduling and an inter-cluster relay selection diversity. The scheduling is based on available data packets and remaining energy level of the source node (SN). This helps to minimize idle listening on nodes without data to transmit as well as reducing control packet overhead. The relay selection diversity is carried out between clusters, by the cluster head (CH), and the base station (BS). The diversity helps to improve network reliability and prolong the network lifetime. Relay selection is determined based on the communication distance, the remaining energy and the channel quality indicator (CQI) for the relay cluster head (RCH). An analytical framework for energy consumption and transmission delay for the proposed MAC protocol is presented in this work. The performance of the proposed MAC protocol is evaluated based on transmission delay, energy consumption, and network lifetime. The results obtained indicate that the proposed MAC protocol provides improved performance than traditional cluster based MAC protocols.
Latif M.
2016-01-01
Full Text Available Forecasting crude oil prices is very difficult to do because it has nonlinear and nonstationary characteristics. This research proposes a crude oil prices forecasting using a combination of EEMD and neural network. EEMD was used to decompose the price of crude oil into several IMFs and one residue. Before the training and testing was processed using FNN, EEMD output is normalized to fulfill network activation function. Data pattern of neural network was determined based on the results of normalization. The Learning method of neural network was based on Polak-Ribiére Conjugate Gradient algorithm. The output of neural networks on each component IMFs and the residue was aggregated using Adaline. The last process is denormalization of the Adaline output. Output of denormalization is the end result of the crude oil price forecasting. After forecasting results has been known, it then compared with the results of several neural networks learning algorithm. The result shows that the proposed method has better forecasting ability. This is indicated by the error value which was smaller than other forecasting algorithms for crude oil price forecasting.
Hossain, Md Jahangir
2010-07-01
In our earlier works, we proposed rate adaptive hierarchical modulation-assisted two-best user opportunistic scheduling (TBS) and hybrid two-user scheduling (HTS) schemes. The proposed schemes are innovative in the sense that they include a second user in the transmission opportunistically using hierarchical modulations. As such the frequency of information access of the users increases without any degradation of the system spectral efficiency (SSE) compared to the classical opportunistic scheduling scheme. In this paper, we analyze channel access delay of an incoming packet at the base station (BS) buffer when our proposed TBS and HTS schemes are employed at the BS. Specifically, using a queuing analytic model we derive channel access delay as well as buffer distribution of the packets that wait at BS buffer for down-link (DL) transmission. We compare performance of the TBS and HTS schemes with that of the classical single user opportunistic schemes namely, absolute carrier-to-noise ratio (CNR)-based single user scheduling (ASS) and normalized CNR-based single user scheduling (NSS). For an independent and identically distributed (i.i.d.) fading environment, our proposed scheme can improve packet\\'s access delay performance compared to the ASS. Selected numerical results in an independent but non-identically distributed (i.n.d.) fading environment show that our proposed HTS achieves overall good channel access delay performance. © 2010 IEEE.
A Scheduling Approach with Processor and Network Heterogeneity for Grid Environment
Dr. Vinay Kumar
2014-01-01
Full Text Available Processor heterogeneity is an important issue in grid environment. In this paper, a list based task scheduling algorithm, called “critical path scheduling with t-level” (CPST for grid computing system is proposed. There are no. of scheduling algorithms such as HEFT [1] use mean execution time based b-level for task priority and SHCP [2] use task priority based on simple critical path. In CPST, a critical path based task sequence is generated with t-level value of tasks, where variance based computation and communication cost is used. The experimental results show that CPST algorithm performs better than HEFT, SHCP and HHS algorithm in grid environment for task graphs.
Uplink Scheduling for Supporting Real Time Voice Traffic in IEEE 802.16 Backhaul Networks
Lizhong Dai; Dongmei Zhao
2008-01-01
In this paper we propose simple enhancements to the bandwidth (BW) request messages in IEEE 802.16 for supporting real-time packet voice traffic. Three different BW request formats are proposed, each requiring a different amount of latency information about the buffered packets at the SS. On this basis, packet scheduling schemes are proposed for the BS to make resource allocations for real-time traffic. Our results show that the proposed BW request and scheduling schemes achieve significantly lower packet loss probability than the standard IEEE 802.16 BW request with round robin scheduling.The results further show that there is an optimum point about how much delay information the SS should report to the BS in order to best utilize the uplink resources while the SS provides satisfactory real-time performance for the voice traffic.
Fairness Time-Slot Allocation and Scheduling with QoS Guarantees in Multihop WiMAX Mesh Networks
Chien-Yu Wu
2013-01-01
Full Text Available The WiMAX technology has been defined to provide high throughput over long distance communications and support the quality of service (QoS control applied on different applications. This paper studies the fairness time-slot allocation and scheduling problem for enhancing throughput and guaranteeing QoS in multihop WiMAX mesh networks. For allocating time slots to multiple subscribe stations (SSs, fairness is a key concern. The notion of max-min fairness is applied as our metric to define the QoS-based max-min fair scheduling problem for maximizing the minimum satisfaction ratio of each SS. We formulate an integer linear programming (ILP model to provide an optimal solution on small-scale networks. For large-scale networks, several heuristic algorithms are proposed for better running time and scalability. The performance of heuristic algorithms is compared with previous methods in the literatures. Experimental results show that the proposed algorithms are better in terms of QoS satisfaction ratio and throughput.
Modelling the locational determinants of house prices: neural network and value tree approaches
Kauko, Tom Johannes
2002-01-01
Tom Kauko's book comprises an analysis of the locational element in house prices. Locational features can increase or decrease the value of a house compared with a similar one elsewhere. So far, the problem of isolating this element has been well documented in the literatures on spatial housing mark
Jafarian, Matin; Scherpen, Jacquelien M.A.; Aiello, Marco
2016-01-01
We present a price-based approach to deal with the challenges of the electrical power distribution systems with renewable generations. In specific, we address the power loss minimization and voltage regulation taking into account the actual grid capacity. Analogously, the cost function is reformulat
Distributed TDMA-Base Scheduling in Multi-hop Wireless Sensor Network
Hojjat Farshadinia
2016-05-01
Full Text Available In most wireless sensor networks applications, charging the nodes batteries is impossible, so the protocols designed for these networks should save the energy as much as possible and decrease the overhead caused by sending data, thus energy consumption and wave interferences between the nodes. Shortage of resources and disturbance in network functionality, are another topics discussed in wireless sensor networks. In wireless sensor networks, the information nature and the quality of their exchange in the network have a special property which will lead to using special techniques and methods that are only ideally efficient in such networks. In this thesis, using several protocols in medium accession layer control and combining them for appropriate timing and better management of network structure, a method is proposed to best utilize sources and reducing network disturbances than the previous proposed methods.
Summary of Pricing Strategy for Suzhou Rail Transit Network%苏州轨道交通线网收费策略综述
周明保; 陈莹; 施毅; 张宁
2011-01-01
为最大程度地发挥轨道交通的社会和经济效益,系统研究轨道交通收费策略.阐述苏州轨道交通线网收费策略的研究思路,在收费原则和运营阶段划分的基础上,详细分析票制、票种、票价等具体收费方法,建立轨道交通线网收费策略的理论体系.就收费策略对城市交通的影响进行研究,以期指导和不断调整收费策略.%In order to bring social and economic benefits of rail transit into full play, systematic research on its pricing strategy is imperative. This paper elaborates the guiding thoughts of pricing strategy for Suzhou rail transit network, analyzes the detailed pricing methods such as fare collection pattern, ticket type, price, etc. in line with pricing principles and operation stages, and establishes the theoretical system of the pricing strategy for rail transit network. The influence of the pricing strategy on urban traffic is also analyzed in order to guide and adjust the strategy constantly.
Effects of Interference Mitigation and Scheduling on Dense Small Cell Networks
Lopez, Victor Fernandez; Pedersen, Klaus I.; Soret, Beatriz
2014-01-01
that intra-cell scheduling can provide a 22% throughput gain in a narrow traffic load region, while the plausible gains from an ideal inter-cell resource management mechanism can be greater than 50% for a wider range of traffic loads, reaching 300% for some of the cases. The results from this research...
HURON (HUman and Robotic Optimization Network) Multi-Agent Temporal Activity Planner/Scheduler
Hua, Hook; Mrozinski, Joseph J.; Elfes, Alberto; Adumitroaie, Virgil; Shelton, Kacie E.; Smith, Jeffrey H.; Lincoln, William P.; Weisbin, Charles R.
2012-01-01
HURON solves the problem of how to optimize a plan and schedule for assigning multiple agents to a temporal sequence of actions (e.g., science tasks). Developed as a generic planning and scheduling tool, HURON has been used to optimize space mission surface operations. The tool has also been used to analyze lunar architectures for a variety of surface operational scenarios in order to maximize return on investment and productivity. These scenarios include numerous science activities performed by a diverse set of agents: humans, teleoperated rovers, and autonomous rovers. Once given a set of agents, activities, resources, resource constraints, temporal constraints, and de pendencies, HURON computes an optimal schedule that meets a specified goal (e.g., maximum productivity or minimum time), subject to the constraints. HURON performs planning and scheduling optimization as a graph search in state-space with forward progression. Each node in the graph contains a state instance. Starting with the initial node, a graph is automatically constructed with new successive nodes of each new state to explore. The optimization uses a set of pre-conditions and post-conditions to create the children states. The Python language was adopted to not only enable more agile development, but to also allow the domain experts to easily define their optimization models. A graphical user interface was also developed to facilitate real-time search information feedback and interaction by the operator in the search optimization process. The HURON package has many potential uses in the fields of Operations Research and Management Science where this technology applies to many commercial domains requiring optimization to reduce costs. For example, optimizing a fleet of transportation truck routes, aircraft flight scheduling, and other route-planning scenarios involving multiple agent task optimization would all benefit by using HURON.
Hossain, Md Jahangir
2010-03-01
Our contribution, in this paper, is two-fold. First, we analyze the performance of a hierarchical modulation-assisted two-best user opportunistic scheduling (TBS) scheme, which was proposed by the authors, in a fading environment where different users have different average link gains. Specifically, we present a new expression for the spectral efficiency (SE) of the users and using this expression, we compare the degrees of fairness (DOF) of the TBS scheme with that of classical single user opportunistic scheduling schemes, namely, absolute carrier-to-noise ratio (CNR) based single-best user scheduling (SBS) and normalized CNR based proportional fair scheduling (PFS) schemes. The second contribution is that we propose a new hybrid two-user opportunistic scheduling (HTS) scheme based on our earlier proposed TBS scheme. This HTS scheme selects the first user based on the largest absolute CNR value among all the users while the second user is selected based on the ratios of the absolute CNRs to the corresponding average CNRs of the remaining users. The total transmission rate i.e., the constellation size is selected according to the absolute CNR of the first best user. The total transmission rate is then allocated among these selected users by joint consideration of their absolute CNRs and allocated number of information bit(s) are transmitted to them using hierarchical modulations. Numerical results are presented for a fading environment where different users experience independent but non-identical (i.n.d.) channel fading. These selected numerical results show that the proposed HTS scheme can considerably increase the system\\'s fairness without any degradation of the link spectral efficiency (LSE) i.e., the multiuser diversity gain compared to the classical SBS scheme. These results also show that the proposed HTS scheme has a lower fairness in comparison to the PFS scheme which suffers from a considerable degradation in LSE. © 2010 IEEE.
Gholamreza Norouzi
2015-01-01
Full Text Available In project management context, time management is one of the most important factors affecting project success. This paper proposes a new method to solve research project scheduling problems (RPSP containing Fuzzy Graphical Evaluation and Review Technique (FGERT networks. Through the deliverables of this method, a proper estimation of project completion time (PCT and success probability can be achieved. So algorithms were developed to cover all features of the problem based on three main parameters “duration, occurrence probability, and success probability.” These developed algorithms were known as PR-FGERT (Parallel and Reversible-Fuzzy GERT networks. The main provided framework includes simplifying the network of project and taking regular steps to determine PCT and success probability. Simplifications include (1 equivalent making of parallel and series branches in fuzzy network considering the concepts of probabilistic nodes, (2 equivalent making of delay or reversible-to-itself branches and impact of changing the parameters of time and probability based on removing related branches, (3 equivalent making of simple and complex loops, and (4 an algorithm that was provided to resolve no-loop fuzzy network, after equivalent making. Finally, the performance of models was compared with existing methods. The results showed proper and real performance of models in comparison with existing methods.
Capitalization of BRT Network Expansions Effects into Prices of Non-expansion Areas
2009-01-01
A before and after hedonic model is used to determine the property value impacts on properties already served by the transit system caused by extensions to Bogota's bus rapid transit system. Asking prices of residential properties belonging to an intervention area (N = 1,407 before, 1,570 after) or a control area (N = 267 before, 732 after) and offered for sale between 2001 and 2006 are used to determine capitalization of the enhanced regional access provided by the extension. Properties offe...
A Branch-and-Price Approach to the Feeder Network Design Problem
Santini, Alberto; Plum, Christian Edinger Munk; Røpke, Stefan
2017-01-01
transit times. Realistic instances are generated from the LinerLib benchmark suite. The problem is solved with a branch-and-price algorithm, which can solve most instances to optimality within one hour. The results also provide insights on the cost structure and desirable features of optimal routes....... These insights were obtained by means of an analysis where scenarios are generated varying internal and external conditions, such as fuel costs and port demands....
Gurudeo Anand Tularam
2012-01-01
Full Text Available House price prediction continues to be important for government agencies insurance companies and real estate industry. This study investigates the performance of house sales price models based on linear and non-linear approaches to study the effects of selected variables. Linear stepwise Multivariate Regression (MR and nonlinear models of Neural Network (NN and Adaptive Neuro-Fuzzy (ANFIS are developed and compared. The GIS methods are used to integrate the data for the study area (Bathurst, Australia. While it was expected that the nonlinear methods would be much better the analysis shows NN and ANFIS are only slightly better than MR suggesting questions about high R2 often found in the literature. While structural data and macro-finance variables may contribute to higher R2 performance comparison was the goal of this study and besides the Australian data lacked structural elements. The results show that MR model could be improved. Also, the land value and location explained at best about 45% of the sale price variation. The analysis of price forecasts (within the 10% range of the actual prediction on average revealed that the non-linear models performed slightly better (29% than the linear (26%. The inclusion of social data improves the MR prediction in most of the suburbs. The suburbs analysis shows the importance of socially based locations and also variance due to types of housing dominant. In general terms of R2, the NN model (0.45 performed only slightly better than ANFIS 0.39 and better than MR (0.37; but the linear MRsoc performed better (0.42. In suburb level, the NN model (7/15 performed better than ANFIS (3/15 but the linear MR (5/15 was better than ANFIS. The improved linear MR (6/15 performed nearly as well as the non-linear NN. Linear methods appear to just as precise as the the more time consuming non linear methods in most cases for accounting for the differences and variation. However, when a much more in depth analysis is
Internet resource pricing models
Xu, Ke; He, Huan
2013-01-01
This brief guides the reader through three basic Internet resource pricing models using an Internet cost analysis. Addressing the evolution of service types, it presents several corresponding mechanisms which can ensure pricing implementation and resource allocation. The authors discuss utility optimization of network pricing methods in economics and underline two classes of pricing methods including system optimization and entities' strategic optimization. The brief closes with two examples of the newly proposed pricing strategy helping to solve the profit distribution problem brought by P2P
Large deviations for Gaussian queues modelling communication networks
Mandjes, Michel
2007-01-01
Michel Mandjes, Centre for Mathematics and Computer Science (CWI) Amsterdam, The Netherlands, and Professor, Faculty of Engineering, University of Twente. At CWI Mandjes is a senior researcher and Director of the Advanced Communications Network group. He has published for 60 papers on queuing theory, networks, scheduling, and pricing of networks.
Improving energy efficiency in wireless sensor networks through scheduling and routing
R, Rathna; 10.5121/ijassn.2012.2103
2012-01-01
This paper is about the wireless sensor network in environmental monitoring applications. A Wireless Sensor Network consists of many sensor nodes and a base station. The number and type of sensor nodes and the design protocols for any wireless sensor network is application specific. The sensor data in this application may be light intensity, temperature, pressure, humidity and their variations .Clustering and routing are the two areas which are given more attention in this paper.
Sousa, Tiago; Ghazvini, Mohammad Ali Fotouhi; Morais, Hugo
2015-01-01
The integration of renewable sources and electric vehicles will introduce new uncertainties to the optimal resource scheduling, namely at the distribution level. These uncertainties are mainly originated by the power generated by renewables sources and by the electric vehicles charge requirements....... This paper proposes a two-state stochastic programming approach to solve the day-ahead optimal resource scheduling problem. The case study considers a 33-bus distribution network with 66 distributed generation units and 1000 electric vehicles....
Chakchai So-In
2010-10-01
Full Text Available Deficit Round Robin (DRR is a fair packet-based scheduling discipline commonly used in wired networks where link capacities do not change with time. However, in wireless networks, especially wireless broadband networks, i.e., IEEE 802.16e Mobile WiMAX, there are two main considerations violate the packet-based service concept for DRR. First, the resources are allocated per Mobile WiMAX frame. To achieve full frame utilization, Mobile WiMAX allows packets to be fragmented. Second, due to a high variation in wireless channel conditions, the link/channel capacity can change over time and location. Therefore, we introduce a Deficit Round Robin with Fragmentation (DRRF to allocate resources per Mobile WiMAX frame in a fair manner by allowing for varying link capacity and for transmitting fragmented packets. Similar to DRR and Generalized Processor Sharing (GPS, DRRF achieves perfect fairness. DRRF results in a higher throughput than DRR (80% improvement while causing less overhead than GPS (8 times less than GPS. In addition, in Mobile WiMAX, the quality of service (QoS offered by service providers is associated with the price paid. This is similar to a cellular phone system; the users may be required to pay air-time charges. Hence, we have also formalized a Generalized Weighted Fairness (GWF criterion which equalizes a weighted sum of service time units or slots, called temporal fairness, and transmitted bytes, called throughput fairness, for customers who are located in a poor channel condition or at a further distance versus for those who are near the base stations, or have a good channel condition. We use DRRF to demonstrate the application of GWF. These fairness criteria are used to satisfy basic requirements for resource allocation, especially for non real-time traffic. Therefore, we also extend DRRF to support other QoS requirements, such as minimum reserved traffic rate, maximum sustained traffic rate, and traffic priority. For real
Yu Zhang
2014-01-01
Full Text Available We consider an ad hoc Floyd-A∗ algorithm to determine the a priori least-time itinerary from an origin to a destination given an initial time in an urban scheduled public transport (USPT network. The network is bimodal (i.e., USPT lines and walking and time dependent. The modified USPT network model results in more reasonable itinerary results. An itinerary is connected through a sequence of time-label arcs. The proposed Floyd-A∗ algorithm is composed of two procedures designated as Itinerary Finder and Cost Estimator. The A∗-based Itinerary Finder determines the time-dependent, least-time itinerary in real time, aided by the heuristic information precomputed by the Floyd-based Cost Estimator, where a strategy is formed to preestimate the time-dependent arc travel time as an associated static lower bound. The Floyd-A∗ algorithm is proven to guarantee optimality in theory and, demonstrated through a real-world example in Shenyang City USPT network to be more efficient than previous procedures. The computational experiments also reveal the time-dependent nature of the least-time itinerary. In the premise that lines run punctually, “just boarding” and “just missing” cases are identified.
Meuffels, W.J.M.; Fleuren, H.A.; Cruijssen, F.C.A.M.; van Dam, E.R.
2009-01-01
Express service carriers provide time-guaranteed deliveries of parcels via a network consisting of nodes and hubs. In this, nodes take care of the collection and delivery of parcels, and hubs have the function to consolidate parcels in between the nodes. The tactical network design problem assigns n
Meuffels, W.J.M.; Fleuren, H.A.; Cruijssen, F.C.A.M.; Dam, E.R.
2010-01-01
Express service carriers provide time-guaranteed deliveries of parcels via a network consisting of nodes and hubs. In this, nodes take care of the collection and delivery of parcels, and hubs have the function to consolidate parcels in between the nodes. The tactical network design problem assigns n
van Hoesel, L.F.W.
2007-01-01
Wireless sensor networks make the previously unobservable, observable. The basic idea behind these networks is straightforward: all wires are cut in traditional sensing systems and the sensors are equipped with batteries and radio's to virtually restore the cut wires. The resulting sensors can be pl
Hoesel, van Lodewijk Frans Willem
2007-01-01
Wireless sensor networks make the previously unobservable, observable. The basic idea behind these networks is straightforward: all wires are cut in traditional sensing systems and the sensors are equipped with batteries and radio’s to virtually restore the cut wires. The resulting sensors can be pl
Boschetto, Suelen N.; Felizari, Luiz C.; Magatao, Leandro; Stebel, Sergio L.; Neves Junior, Flavio; Lueders, Ricardo; Arruda, Lucia V.R. de [Universidade Tecnologica Federal do Parana (UTFPR), Curitiba, PR (Brazil); Ribas, Paulo Cesar; Bernardo, Luiz F.J. [PETROBRAS S.A., Rio de Janeiro, RJ (Brazil). Centro de Pesquisas (CENPES)
2008-07-01
This work develops an optimization structure to aid the operational decision-making of scheduling activities in a real world pipeline network. The proposed approach is based on a decomposition method to address complex problems with high computational burden. The Pre-analysis makes a previous evaluation of a batch sequencing, getting information to be entered into optimization block. The continuous time Mixed Integer Linear Program (MILP) model gets such information and calculates the scheduling. The models are applied to a pipeline network that connects different areas including refineries, terminals, and final clients. Many oil derivatives (e.g. gasoline, liquefied petroleum gas, naphtha) can be sent or received in this network. The computational burden to determine a short-term scheduling within the considered scenario is a relevant issue. Many insights have been derived from the obtained solutions, which are given in a reduced computational time for oil industrial-size scenarios. (author)
Li, Wenkai; Goh, Mark
2015-01-01
Maximizing reader insights into the challenges facing maritime supply chains and container port logistics service providers in Asia, this book highlights their innovative responses to these challenges through real-world case studies. With a focus on mathematical modeling, simulation and heuristics approaches, this book provides academics, engineers, container terminal operators, students in logistics and supply chain management with the latest approaches that can be used to address the planning and scheduling problem in large container terminal yards. This book can be used on a self-contained basis as teaching cases in an undergraduate or specialist class setting, or on techniques applied to maritime container operations for port operations.
Fair Virtual Clock Queueing Scheduling Algorithm for High-Speed Packet Switched Network
WANG Chonggang; LONG Keping; GONG Xiangyang; CHENG Shiduan
2001-01-01
In this paper,we present an effectivescheduling algorithm based on virtual clock (VC) al-gorithm.Whereas the traditional VC algorithm lacksof fairness properties,our algorithm exhibits fairnessproperties similar to WFQ and keeps the same delayproperties as VC using a system potential functionwith O(1) complexity.So,we call it Fair Virtual Clock(FVC) scheduling algorithm.In FVC,computationof system potential function does not require such di-vision or multiplication operations as in MD-SCFQ.Compared with MD-SCFQ,FVC has lower complexityand can be easily implemented in chips.We verify theeffectivity of proposed FVC through strict theoreticalanalysis.
A SCHEDULING ALGORITHM USING COMPENSATING ROUND ROBIN IN PACKET—SWTICHING BROADBAND NETWORKS
LanJulong; WangBinqiang; 等
2002-01-01
A new approximation of fair queuing called Comensating Round Robin(CRR)ia presented in this paper.The algorithm uses packet-by-packet scheduler with a compensating measure.It achieves good fairness in terms of throrghput ,requires onlyO(1)time complexity to process a packet ,and is simple enough to be implemented in hardware.After the performances are analyzed ,the fairness and is simple enough to be implemented in hardware.After the performances are that the CRR can effectively isolate the effects of contending sources.
A SCHEDULING ALGORITHM USING COMPENSATING ROUND ROBIN IN PACKET-SWTICHING BROADBAND NETWORKS
Lan Julong; Wang Binqiang; Li Ou; Wu Jiangxing
2002-01-01
A new approximation of fair queuing called Compensating Round Robin (CRR)is presented in this paper. The algorithm uses packet-by-packet scheduler with a compensating measure. It achieves good fairness in terms of throughput, requires only O(1) time complexity to process a packet, and is simple enough to be implemented in hardware. After the performances are analyzed, the fairness and packet loss rate of the algorithm are simulated. Simulation results show that the CRR can effectively isolate the effects of contending sources.
Yamamoto, Lia; Arruda, Lucia Valeria Ramos de; Libert, Nikolas [Universidade Tecnologica Federal do Parana (UTFPR), Curitiba, PR (Brazil)
2008-07-01
This work presents the VNS heuristic technique applied on batches ordering in a real network of petroleum derivatives distribution. These ordering have great influence in operational scheduling of a pipeline network. The operational scheduling purposes the efficient utilization of the resources, resulting on a better performance. Due to the great complexity of the real network problem and the necessity of its resolution in little computational time, it was adopted a problem subdivision in assignment of resources, sequencing and timing. In the resources assignment stage, it is considered the production/consumption functions and the products tankages to determine the total batches, including its volume, flow rate and the time-windows to satisfy the demand. These data are used in the sequencing stage, where a VNS based model determines the batches ordering. In a final step, the last block, realize the temporisation considering the network operational constraints. This work shows the results from the optimization of the sequencing stage which aims the improvement of the solution quality of scheduling. (author)
Zhao, Yongli; Li, Yajie; Wang, Xinbo; Chen, Bowen; Zhang, Jie
2016-09-01
A hierarchical software-defined networking (SDN) control architecture is designed for multi-domain optical networks with the Open Daylight (ODL) controller. The OpenFlow-based Control Virtual Network Interface (CVNI) protocol is deployed between the network orchestrator and the domain controllers. Then, a dynamic bandwidth on demand (BoD) provisioning solution is proposed based on time scheduling in software-defined multi-domain optical networks (SD-MDON). Shared Risk Link Groups (SRLG)-disjoint routing schemes are adopted to separate each tenant for reliability. The SD-MDON testbed is built based on the proposed hierarchical control architecture. Then the proposed time scheduling-based BoD (Ts-BoD) solution is experimentally demonstrated on the testbed. The performance of the Ts-BoD solution is evaluated with respect to blocking probability, resource utilization, and lightpath setup latency.
Approximate Sorting of Packet-Scheduling in High-Speed Networks
WANG Youcheng; YU Shengsheng; ZHA Hui; ZHOU Jingli
2001-01-01
Fairness, latency and computational complexity are three important factors in evaluating the performance of a scheduling algorithm. Fairness must be satisfied so that service can be distributed according to the reserved rate. Only when latency is irrelevant to the number of connections, is it possible to minimize the end-to-end delay through controlling the reserved rate. Among existing scheduling algorithms, Round Robin is the least complex. However, conventional Round Robin is unable to ensure fairness, and the improved round robin algorithms like Deficit Round Robin, Weighted Round Robin and Virtual Round Robin are unable to ensure that their latencies are irrelevant to the number of connections although they guarantee fairness. Potential Round Robin developed for analysis of fairness and latency reduction is thus proposed. It is based on the introduction of a new concept, Round Potential Function. The function splits service time into a number of service round periods to guarantee fairness regardless of the serving process used in the period.In the analysis of latency, service round periods are re-split into multiple scanning cycles for further service distribution with approximate sorting between scanning cycles. As a result, latency is no longer relevant to the number of connections while the low complexity of round robin is kept.
Dynamic Key-Scheduling and Authentication Scheme for Distributed Wireless Network
T.Surya Prakash Reddy; T. Sunil Kumar Reddy
2010-01-01
A self-protection technique is suggested for adhoc network fall short of the objective of data privacy, data integrity, and authentication. Various security standards such as IEEE 802.11i, WPA, IEEE 802.1X were suggested to enhance the security issues in 802.11.Despite their efficiency, these standards does not provide any security approach for monitoring of these authentication in a distributed architecture. For the efficient monitoring of the authentication issue in adhoc network, in thi...
Subhrakanti Dey
2007-08-01
Full Text Available We consider a joint rate and power control problem in a wireless data traffic relay network with fading channels. The optimization problem is formulated in terms of power and rate selection, and link transmission scheduling. The objective is to seek high aggregate utility of the relay node when taking into account buffer load management and power constraints. The optimal solution for a single transmitting source is computed by a two-layer dynamic programming algorithm which leads to optimal power, rate, and transmission time allocation at the wireless links. We further consider an optimal power allocation problem for multiple transmitting sources in the same framework. Performances of the resource allocation algorithms including the effect of buffer load control are illustrated via extensive simulation studies.
Dey Subhrakanti
2007-01-01
Full Text Available We consider a joint rate and power control problem in a wireless data traffic relay network with fading channels. The optimization problem is formulated in terms of power and rate selection, and link transmission scheduling. The objective is to seek high aggregate utility of the relay node when taking into account buffer load management and power constraints. The optimal solution for a single transmitting source is computed by a two-layer dynamic programming algorithm which leads to optimal power, rate, and transmission time allocation at the wireless links. We further consider an optimal power allocation problem for multiple transmitting sources in the same framework. Performances of the resource allocation algorithms including the effect of buffer load control are illustrated via extensive simulation studies.
A Routing Priority Scheduling Algorithm for MAC Layer in Wireless Sensor Networks
Liyong Bao
2011-03-01
Full Text Available Based on the ideas of conflict-free transmission, priority to guarantee transmission quality for communication between the different clusters , this article proposes a scheduling Algorithm fit for the MAC scheme of WSNs, which has made it possible for the polling service capable of differentiating services of the cluster head node of two priority levels. The high-priority service of the cluster head is responsible for routing between the different clusters, via exhaustive service policy, while the low-priority services of the cluster head node, for communication within the cluster through limited service policy with good fairness. The theoretical model of this scheme is established through Markov chain and probability generating function. Mathematical analysis is made on the mean queue length, the mean inquiry cyclic time and the mean delay time. It turns out that the findings from theoretical analysis correspond well with those from simulated experiments.
MELO JR., A.
2013-06-01
Full Text Available The Proportional Differentiation Model (PDM is currently one of the main service proposals for the Next Generation Internet. This paper presents a new packet scheduling algorithm for implementing the PDM model using measurement windows and a mechanism of dynamic adjustment of packet delay estimation. Window Based Waiting-Time Priority Plus (WBWTP+, the proposed algorithm, is an evolution of the WBWTP algorithm that adjusts dynamically the relative weights of transmitted and waiting for transmission packets according to the current state of the system. The WBWTP+ delay estimator makes possible to accelerate or to delay the transmission of backlogged packets. Simulations performed to asses the performance of the WBWTP+ show that it presents significant improvement in the attendance of the PDM objective in relation to WBWTP in most scenarios, excepted when the link utilization rate is 100%. Even in that case the performance of WBWTP+ was better than that of WTP and PAD algorithms.
Organic Chemicals Remain High Prices
无
2007-01-01
@@ Phenol In early April 2007, China's phenol price remained bullish, and with the restart of phenol/acetone units in Sinopec Beijing Yanhua Petrochemical being ahead of schedule, there were few trading actions in the market, and the price of phenol dropped considerably afterwards.
Dynamic Key-Scheduling and Authentication Scheme for Distributed Wireless Network
T.Surya Prakash Reddy
2010-07-01
Full Text Available A self-protection technique is suggested for adhoc network fall short of the objective of data privacy, data integrity, and authentication. Various security standards such as IEEE 802.11i, WPA, IEEE 802.1X were suggested to enhance the security issues in 802.11.Despite their efficiency, these standards does not provide any security approach for monitoring of these authentication in a distributed architecture. For the efficient monitoring of the authentication issue in adhoc network, in this paper we present a self monitored security approach for self-monitoring of key authentication for security protocol in adhoc networks. The processing overhead for the suggested approach is evaluated for a threshold based cryptographic approach.
Scheduling multiprocessor job with resource and timing constraints using neural networks.
Huang, Y M; Chen, R M
1999-01-01
The Hopfield neural network is extensively applied to obtaining an optimal/feasible solution in many different applications such as the traveling salesman problem (TSP), a typical discrete combinatorial problem. Although providing rapid convergence to the solution, TSP frequently converges to a local minimum. Stochastic simulated annealing is a highly effective means of obtaining an optimal solution capable of preventing the local minimum. This important feature is embedded into a Hopfield neural network to derive a new technique, i.e., mean field annealing. This work applies the Hopfield neural network and the normalized mean field annealing technique, respectively, to resolve a multiprocessor problem (known to be a NP-hard problem) with no process migration, constrained times (execution time and deadline) and limited resources. Simulation results demonstrate that the derived energy function works effectively for this class of problems.
Costanzo, Giuseppe Tommaso; Bernstein, Andrey; Chamorro, Lorenzo Reyes
2015-01-01
This paper presents a systematic approach for abstracting the flexibility of a building space heating system and using it within a composable framework for real-time explicit power control of microgrids and, more in general, active distribution networks. In particular, the proposed approach...... is developed within the context of a previously defined microgrid control framework, called COMMELEC, conceived for the explicit and real-time control of these specific networks. The designed control algorithm is totally independent from the need of a building model and allows exploiting the intrinsic thermal...
Højgaard-Hansen, Kim; Madsen, Tatiana Kozlova; Schwefel, Hans-Peter
2012-01-01
The performance of wireless communication networks has been shown to have a strong location dependence. Measuring the performance while having accurate location information available makes it possible to generate performance maps. In this paper we propose a framework for the generation and use...... of such performance maps. We demonstrate how the framework can be used to reduce the retransmissions and to better utilise network resources when performing TCP-based file downloads in vehicular M2M communication scenarios. The approach works on top of a standard TCP stack hence has to map identified transmission...
Kleunen, van Wouter Anne Pieter
2014-01-01
Wireless Sensor Networks (WSNs) caused a shift in the way things are monitored. While traditional monitoring was coarse-grained and offline, using WSNs allows fine-grained and real-time monitoring. While radio-based WSNs are growing out of the stage of research to commercialization and widespread a
Martins, F V C; Carrano, E G; Wanner, E F; Takahashi, R H C; Mateus, G R; Nakamura, F G
2014-01-01
Recent works raised the hypothesis that the assignment of a geometry to the decision variable space of a combinatorial problem could be useful both for providing meaningful descriptions of the fitness landscape and for supporting the systematic construction of evolutionary operators (the geometric operators) that make a consistent usage of the space geometric properties in the search for problem optima. This paper introduces some new geometric operators that constitute the realization of searches along the combinatorial space versions of the geometric entities descent directions and subspaces. The new geometric operators are stated in the specific context of the wireless sensor network dynamic coverage and connectivity problem (WSN-DCCP). A genetic algorithm (GA) is developed for the WSN-DCCP using the proposed operators, being compared with a formulation based on integer linear programming (ILP) which is solved with exact methods. That ILP formulation adopts a proxy objective function based on the minimization of energy consumption in the network, in order to approximate the objective of network lifetime maximization, and a greedy approach for dealing with the system's dynamics. To the authors' knowledge, the proposed GA is the first algorithm to outperform the lifetime of networks as synthesized by the ILP formulation, also running in much smaller computational times for large instances.
Scheduled MAC in Beacon Overlay Networks for Underwater Localization and Time-Synchronization
van Kleunen, W.A.P.; Meratnia, Nirvana; Havinga, Paul J.M.
2011-01-01
In this article we introduce a MAC protocol designed for underwater localization and time-synchronisation. The MAC protocol assumes a network of static reference nodes and allows blind nodes to be localized by listening-only to the beacon messages. Such a system is known to be very scalable. We show
A Statically Scheduled Time-Division-Multiplexed Network-on-Chip for Real-Time Systems
Schoeberl, Martin; Brandner, Florian; Sparsø, Jens
2012-01-01
This paper explores the design of a circuit-switched network-on-chip (NoC) based on time-division-multiplexing (TDM) for use in hard real-time systems. Previous work has primarily considered application-specific systems. The work presented here targets general-purpose hardware platforms. We...
Distributed Topology Organization and Transmission Scheduling in Wireless Ad Hoc Networks
2004-01-01
Establishment . . . . . . . . . . . . . . . 40 2.4.4 Leader election termination . . . . . . . . . . . . . . . . . . . 41 2.5 Experiments...symmetric mechanism to the case of several nodes. BTCP is based on a distributed leader election process where proximity information is discovered in a...is not known, each node uses a timeout to assume leader election termination. The timeout introduces a correctness- delay tradeoff in the network
Integration of wireless sensor networks into automatic irrigation scheduling of a center pivot
A six-span center pivot system was used as a platform for testing two wireless sensor networks (WSN) of infrared thermometers. The cropped field was a semi-circle, divided into six pie shaped sections of which three were irrigated manually and three were irrigated automatically based on the time tem...
Design of Scheduler in High Speed Packet Switching Networks%高速分组交换网络中调度器的设计
魏艳艳; 孟李林
2012-01-01
The rapid development of internet business puts forward higher request for the quality of service in the network, the queue scheduler of the high speed packet switching network can effectively provide the higher quality of service in the network. It uses hierarchical scheduling and four queue scheduling algorithms to realize the design of queue scheduler. What's more,it compares and analyses deeply advantages and disadvantages among kinds of scheduling algorithms in the queue scheduler, especially, improves and optimizes DRR scheduling algorithm. At last, It completes the simulation verification and circuit synthesis for the circuit design, and the results show that the scheduler can satisfy the higher quality of service of the network and can be applied to scheduler design of high speed packet switching network.%为了满足迅猛发展的网络业务对网络服务质量提出的更高要求,使用高速分组网络交换机中的队列调度器可以有效地提供高质量的网络服务.通过采用分级式队列调度和四种队列调度算法有效地实现了队列调度器的设计.并且深入地比较和分析了队列调度器中多种队列调度算法的优缺点,尤其是对DRR调度算法进行了优化和改进.最后,对所设计的电路进行了仿真验证和电路综合,结果表明该调度器可以满足网络对服务质量的更高要求,并且能够应用到高速分组交换网络的调度器设计中.
Pricing and distributed QoS control for elastic network traffic
J.L. van den Berg (Hans); M.R.H. Mandjes (Michel); R. Núñez Queija (Rudesindo (Sindo))
2006-01-01
textabstractWeb measurements have shown that TCP flow sizes vary over several orders of magnitude. If network resources are shared fairly, the performance of short TCP flows is seriously degraded by long flows. This motivates prioritization of short over long flows, leading to significant
Prices and Network Externalities in Two-Sided Markets: The Belgian Newspaper Industry
van Cayseele, P.; Vanormelingen, S.
2007-01-01
This paper discusses the newspaper industry in Belgium from a two-sided market perspective. The reader and advertizing market for printed media are closely interlinked with each other by bilateral network externalities. This requires a specific structural model to estimate demand parameters for both
Prices and network effects in two-sided markets: the Belgian newspaper industry
Van Cayseele, P.; Vanormelingen, S.
2009-01-01
This paper investigates the two-sided nature of the newspaper industry. We explicitly take into account cross network effects that exist between advertisers and newspaper readers. On one side, advertisers' demand for publicity space depends on the number of newspaper readers and their
Prices and network effects in two-sided markets: the Belgian newspaper industry
Van Cayseele, P.; Vanormelingen, S.
2009-01-01
This paper investigates the two-sided nature of the newspaper industry. We explicitly take into account cross network effects that exist between advertisers and newspaper readers. On one side, advertisers' demand for publicity space depends on the number of newspaper readers and their characteristic
Price Competition in Two-Sided Markets with Heterogeneous Consumers and Network Effects
Filistrucchi, L.; Klein, T.J.
2013-01-01
We model a two-sided market with heterogeneous customers and two heterogeneous network effects. In our model, customers on each market side care differently about both the number and the type of customers on the other side. Examples of two-sided markets are online platforms or daily newspapers. In t
Synthesis and Scheduling of Optimal Batch Water-recycle Networks%最佳间歇水循环网络的合成和时序安排
A.H.Rabie; M.M.El-Halwagi
2008-01-01
This work develops an optimization-based methodology for the design and scheduling of batch water recycle networks. This task requires the identification of network configuration, fresh-water usage, recycle assignments from sources to sinks, wastewater discharge, and a scheduling scheme. A new source-tank-sink representation is developed to allow for storage and dispatch tanks. The problem is solved in stages by first eliminating scheduling constraints and determining minimum usage of fresh water and wastewater discharge. An iterative procedure is formulated to minimize the total annual cost of the system by trading off capital versus operating costs. The work overcomes limitations in previous literature work including restricted recycle within the same cycle, lumped balances that may not lead to feasible solutions, and unrealistic objective functions. A case study is solved to illustrate the usefulness of the devised procedure.
Xavier Fageda; Juan Luis Jiménez; Jordi Perdiguero
2010-01-01
Competition in airline markets may be tough. In this context, network carriers have two alternative strategies to compete with low-cost carriers. First, they may establish a low-cost subsidiary. Second, they may try to reduce costs using the main brand. This paper examines a successful strategy of the first type implemented by Iberia in the Spanish domestic market. Our analysis of data and the estimation of a pricing equation show that Iberia has been able to charge lower prices than rivals w...
Tadahiro Taniguchi
2015-07-01
Full Text Available A linear function submission-based double auction (LFS-DA mechanism for a regional electricity network is proposed in this paper. Each agent in the network is equipped with a battery and a generator. Each agent simultaneously becomes a producer and consumer of electricity, i.e., a prosumer, and trades electricity in the regional market at a variable price. In the LFS-DA, each agent uses linear demand and supply functions when they submit bids and asks to an auctioneer in the regional market. The LFS-DA can achieve an exact balance between electricity demand and supply for each time slot throughout the learning phase and was shown capable of solving the primal problem of maximizing the social welfare of the network without any central price setter, e.g., a utility or a large electricity company, in contrast with conventional real-time pricing (RTP. This paper presents a clarification of the relationship between the RTP algorithm derived on the basis of a dual decomposition framework and LFS-DA. Specifically, we proved that the changes in the price profile of the LFS-DA mechanism are equal to those achieved by the RTP mechanism derived from the dual decomposition framework, except for a constant factor.
Transition from monopoly pricing to competitive pricing
Perera, L. [Eastern Energy Ltd., Melbourne, VIC (Australia)
1995-12-31
The Victorian Government has embarked on a program to restructure the State electricity supply industry, that will be the precursor to reform throughout the whole of Australia. The Government is depending on competition to drive efficiency improvements to both generation and distribution businesses. Retail pricing will be the key determinant to a future assessment of the success or failure of these reforms. The paper examines electricity pricing before and after the restructuring from the viewpoint of a practitioner at the cutting edge of the reform process. Economic rationale is put forward why the Value Proposition will replace the Cost Recovery basis previously used in electricity pricing. It is concluded that limitations of interstate links will temper intestate competition unless innovative solution can be found. The current method of setting market prices based on a `Pool System` is only efficient if the generators bid their marginal price on a regular basis. In essence the pool replaces the `merit order` previously used to load generators and is basically a scheduling mechanism. Serious consideration needs to be given to the question whether this mechanism should be also setting the price of electricity. (author). 5 tabs.
Routing and scheduling problems
Reinhardt, Line Blander
be that the objects routed have an availability time window and a delivery time window or that locations on the path have a service time window. When routing moving transportation objects such as vehicles and vessels schedules are made in connection with the routing. Such schedules represent the time for the presence...... to a destination on a predefined network, the routing and scheduling of vessels in a liner shipping network given a demand forecast to be covered, the routing of manpower and vehicles transporting disabled passengers in an airport and the vehicle routing with time windows where one version studied includes edge...... of a connection between two locations. This could be an urban bus schedule where busses are routed and this routing creates a bus schedule which the passengers between locations use. In this thesis various routing and scheduling problems will be presented. The topics covered will be routing from an origin...
Optimal Energy-Efficient Downlink Transmission Scheduling for Real-Time Wireless Networks
Miao, Lei; Mao, Jianfeng; Cassandras, Christos G.
2016-01-01
It has been shown that using appropriate channel coding schemes in wireless environments, transmission energy can be significantly reduced by controlling the packet transmission rate. This paper seeks optimal solutions for downlink transmission control problems, motivated by this observation and by the need to minimize energy consumption in real-time wireless networks. Our problem formulation deals with a more general setting than the paper authored by Gamal et. al., in which the MoveRight al...
Availability and Network-Aware MapReduce Task Scheduling over the Internet
Tang, Bing; Xie, Qi; He, Haiwu; Fedak, Gilles
2015-01-01
International audience; MapReduce offers an ease-of-use programming paradigm for processing large datasets. In our previous work, we have designed a MapReduce framework called BitDew-MapReduce for desktop grid and volunteer computing environment, that allows nonexpert users to run data-intensive MapReduce jobs on top of volunteer resources over the Internet. However, network distance and resource availability have great impact on MapReduce applications running over the Internet. To address th...
Abdollahi, Yadollah; Sairi, Nor Asrina; Said, Suhana Binti Mohd; Abouzari-lotf, Ebrahim; Zakaria, Azmi; Sabri, Mohd Faizul Bin Mohd; Islam, Aminul; Alias, Yatimah
2015-11-05
It is believe that 80% industrial of carbon dioxide can be controlled by separation and storage technologies which use the blended ionic liquids absorber. Among the blended absorbers, the mixture of water, N-methyldiethanolamine (MDEA) and guanidinium trifluoromethane sulfonate (gua) has presented the superior stripping qualities. However, the blended solution has illustrated high viscosity that affects the cost of separation process. In this work, the blended fabrication was scheduled with is the process arranging, controlling and optimizing. Therefore, the blend's components and operating temperature were modeled and optimized as input effective variables to minimize its viscosity as the final output by using back-propagation artificial neural network (ANN). The modeling was carried out by four mathematical algorithms with individual experimental design to obtain the optimum topology using root mean squared error (RMSE), R-squared (R(2)) and absolute average deviation (AAD). As a result, the final model (QP-4-8-1) with minimum RMSE and AAD as well as the highest R(2) was selected to navigate the fabrication of the blended solution. Therefore, the model was applied to obtain the optimum initial level of the input variables which were included temperature 303-323 K, x[gua], 0-0.033, x[MDAE], 0.3-0.4, and x[H2O], 0.7-1.0. Moreover, the model has obtained the relative importance ordered of the variables which included x[gua]>temperature>x[MDEA]>x[H2O]. Therefore, none of the variables was negligible in the fabrication. Furthermore, the model predicted the optimum points of the variables to minimize the viscosity which was validated by further experiments. The validated results confirmed the model schedulability. Accordingly, ANN succeeds to model the initial components of the blended solutions as absorber of CO2 capture in separation technologies that is able to industries scale up.
Stochastic Sensor Scheduling for Energy Constrained Estimation in Multi-Hop Wireless Sensor Networks
Mo, Yilin; Casavola, Alessandro; Sinopoli, Bruno
2011-01-01
Wireless Sensor Networks (WSNs) enable a wealth of new applications where remote estimation is essential. Individual sensors simultaneously sense a dynamic process and transmit measured information over a shared channel to a central fusion center. The fusion center computes an estimate of the process state by means of a Kalman filter. In this paper we assume that the WSN admits a tree topology with fusion center at the root. At each time step only a subset of sensors can be selected to transmit observations to the fusion center due to a limited energy budget. We propose a stochastic sensor selection algorithm that randomly selects a subset of sensors according to certain probability distribution, which is opportunely designed to minimize the asymptotic expected estimation error covariance matrix. We show that the optimal stochastic sensor selection problem can be relaxed into a convex optimization problem and thus solved efficiently. We also provide a possible implementation of our algorithm which does not in...
Salim Lahmiri
2014-07-01
Full Text Available This paper presents a forecasting model that integrates the discrete wavelet transform (DWT and backpropagation neural networks (BPNN for predicting financial time series. The presented model first uses the DWT to decompose the financial time series data. Then, the obtained approximation (low-frequency and detail (high-frequency components after decomposition of the original time series are used as input variables to forecast future stock prices. Indeed, while high-frequency components can capture discontinuities, ruptures and singularities in the original data, low-frequency components characterize the coarse structure of the data, to identify the long-term trends in the original data. As a result, high-frequency components act as a complementary part of low-frequency components. The model was applied to seven datasets. For all of the datasets, accuracy measures showed that the presented model outperforms a conventional model that uses only low-frequency components. In addition, the presented model outperforms both the well-known auto-regressive moving-average (ARMA model and the random walk (RW process.
Clement, Bradley; Johnston, Mark; Wax, Allan; Chouinard, Caroline
2008-01-01
The DSN (Deep Space Network) Scheduling Engine targets all space missions that use DSN services. It allows clients to issue scheduling, conflict identification, conflict resolution, and status requests in XML over a Java Message Service interface. The scheduling requests may include new requirements that represent a set of tracks to be scheduled under some constraints. This program uses a heuristic local search to schedule a variety of schedule requirements, and is being infused into the Service Scheduling Assembly, a mixed-initiative scheduling application. The engine resolves conflicting schedules of resource allocation according to a range of existing and possible requirement specifications, including optional antennas; start of track and track duration ranges; periodic tracks; locks on track start, duration, and allocated antenna; MSPA (multiple spacecraft per aperture); arraying/VLBI (very long baseline interferometry)/delta DOR (differential one-way ranging); continuous tracks; segmented tracks; gap-to-track ratio; and override or block-out of requirements. The scheduling models now include conflict identification for SOA(start of activity), BOT (beginning of track), RFI (radio frequency interference), and equipment constraints. This software will search through all possible allocations while providing a best-effort solution at any time. The engine reschedules to accommodate individual emergency tracks in 0.2 second, and emergency antenna downtime in 0.2 second. The software handles doubling of one mission's track requests over one week (to 42 total) in 2.7 seconds. Further tests will be performed in the context of actual schedules.
Node Scheduling Strategies for Achieving Full-View Area Coverage in Camera Sensor Networks
Peng-Fei Wu
2017-06-01
Full Text Available Unlike conventional scalar sensors, camera sensors at different positions can capture a variety of views of an object. Based on this intrinsic property, a novel model called full-view coverage was proposed. We study the problem that how to select the minimum number of sensors to guarantee the full-view coverage for the given region of interest (ROI. To tackle this issue, we derive the constraint condition of the sensor positions for full-view neighborhood coverage with the minimum number of nodes around the point. Next, we prove that the full-view area coverage can be approximately guaranteed, as long as the regular hexagons decided by the virtual grid are seamlessly stitched. Then we present two solutions for camera sensor networks in two different deployment strategies. By computing the theoretically optimal length of the virtual grids, we put forward the deployment pattern algorithm (DPA in the deterministic implementation. To reduce the redundancy in random deployment, we come up with a local neighboring-optimal selection algorithm (LNSA for achieving the full-view coverage. Finally, extensive simulation results show the feasibility of our proposed solutions.
Cognitive Self-Scheduled Mechanism for Access Control in Noisy Vehicular Ad Hoc Networks
Mario Manzano
2015-01-01
Full Text Available Within the challenging environment of intelligent transportation systems (ITS, networked control systems such as platooning guidance of autonomous vehicles require innovative mechanisms to provide real-time communications. Although several proposals are currently under discussion, the design of a rapid, efficient, flexible, and reliable medium access control mechanism which meets the specific constraints of such real-time communications applications remains unsolved in this highly dynamic environment. However, cognitive radio (CR combines the capacity to sense the radio spectrum with the flexibility to adapt to transmission parameters in order to maximize system performance and has thus become an effective approach for the design of dynamic spectrum access (DSA mechanisms. This paper presents the enhanced noncooperative cognitive division multiple access (ENCCMA proposal combining time division multiple access (TDMA and frequency division multiple access (FDMA schemes with CR techniques to obtain a mechanism fulfilling the requirements of real-time communications. The analysis presented here considers the IEEE WAVE and 802.11p as reference standards; however, the proposed medium access control (MAC mechanism can be adapted to operate on the physical layer of different standards. The mechanism also offers the advantage of avoiding signaling, thus enhancing system autonomy as well as behavior in adverse scenarios.
Nonlinear prediction of gold prices based on BP neural network%基于 BP神经网络的黄金价格非线性预测
张延利
2013-01-01
针对黄金价格的非线性特征和神经网络的自身特点，利用BP神经网络建立了黄金价格的非线性预测模型。实证研究结果表明，BP神经网络模型具有较好的预测精度，可以为黄金投资和宏观经济决策提供一定的参考依据。%According to the neural network nonlinear characteristics of gold price and its own characteristics ,using BP neural network nonlinear prediction model was set up for the price of gold .The results show that the BP prediction has good accuracy and is available to provide references for the gold investment and macroeconomic decisions .
Montri Inthachot
2016-01-01
Full Text Available This study investigated the use of Artificial Neural Network (ANN and Genetic Algorithm (GA for prediction of Thailand’s SET50 index trend. ANN is a widely accepted machine learning method that uses past data to predict future trend, while GA is an algorithm that can find better subsets of input variables for importing into ANN, hence enabling more accurate prediction by its efficient feature selection. The imported data were chosen technical indicators highly regarded by stock analysts, each represented by 4 input variables that were based on past time spans of 4 different lengths: 3-, 5-, 10-, and 15-day spans before the day of prediction. This import undertaking generated a big set of diverse input variables with an exponentially higher number of possible subsets that GA culled down to a manageable number of more effective ones. SET50 index data of the past 6 years, from 2009 to 2014, were used to evaluate this hybrid intelligence prediction accuracy, and the hybrid’s prediction results were found to be more accurate than those made by a method using only one input variable for one fixed length of past time span.
Iwasaki, Hirotoshi; Sega, Shinichiro; Hiraishi, Hironori; Mizoguchi, Fumio
In recent years, lots of music content can be stored in mobile computing devices, such as a portable digital music player and a car navigation system. Moreover, various information content like news or traffic information can be acquired always anywhere by a cellular communication and a wireless LAN. However, usability issues arise from the simple interfaces of mobile computing devices. Moreover, retrieving and selecting such content poses safety issues, especially while driving. Thus, it is important for the mobile system to recommend content automatically adapted to user's preference and situation. In this paper, we present the user-adapted program scheduling that generates sequences of content (Program) suiting user's preference and situation based on the Bayesian network and the Constraint Satisfaction Problem (CSP) technique. We also describe the design and evaluation of its realization system, the Personal Program Producer (P3). First, preference such as a genre ratio of content in a program is learned as a Bayesian network model using simple operations such as a skip behavior. A model including each content tends to become large-scale. In order to make it small, we present the model separation method that carries out losslessly compression of the model. Using the model, probabilistic distributions of preference to generate constraints are inferred. Finally satisfying the constraints, a program is produced. This kind of CSP has an issue of which the number of variables is not fixedness. In order to make it variable, we propose a method using metavariables. To evaluate the above methods, we applied them to P3 on a car navigation system. User evaluations helped us clarify that the P3 can produce the program that a user prefers and adapt it to the user.
Núñez Tabales, Julia M.
2013-01-01
Full Text Available Econometric models, in the estimation of real estate prices, are a useful and realistic approach for buyers and for local and fiscal authorities. From the classical hedonic models to more data driven procedures, based on Artificial Neural Networks (ANN, many papers have appeared in economic literature trying to compare the results attained with both approaches. We insist on the use of ANN, when there is enough statistical information, and will detail some comparisons to hedonic modeling, in a medium size city in the South of Spain, with an extensive set of data spanning over several years, collected before the actual downturn of the market. Exogenous variables include each dwelling's external and internal data (both numerical and qualitative, and data from the building in which it is located and its surroundings. Alternative models are estimated for several time intervals, and enabling the comparison of the effects of the rising prices during the bull market over the last decade. || Los modelos econométricos en la valoración de precios inmobiliarios constituyen una herramienta útil tanto para los compradores como para las autoridades locales y fiscales. Desde los modelos hedónicos clásicos hasta los planteamientos actuales a través de redes neuronales artificiales (RNA, han tenido lugar numerosas aportaciones en la literatura económica que tratan de comparar los resultados de ambos métodos. Insistimos en el empleo de RNA en el caso de disponer de suficiente información estadística. En este trabajo se aplica dicha metodología en una ciudad de tamaño medio situada en el sur de España, utilizando una extensa muestra de datos que comprende varios años precedentes a la crisis actual. Las variables utilizadas -tanto cuantitativas como cualitativas- incluyen datos externos e internos de la vivienda, del edificio en el que está localizada, así como de su entorno. Se construyen varios modelos alternativos para distintos intervalos de
Rajkumar Ragunathan
2005-01-01
Full Text Available Energy efficiency is imperative to enable the deployment of ad hoc networks. Conventional power management focuses independently on the physical or MAC layer and approaches differ depending on the abstraction level. At the physical layer, the fundamental tradeoff between transmission rate and energy is exploited, which leads to transmit as slow as possible. At MAC level, power reduction techniques aim to transmit as fast as possible to maximize the radios power-off interval. The two approaches seem conflicting and it is not obvious which one is the most appropriate. We propose a transmission strategy that optimally mixes both techniques in a multiuser context. We present a cross-layer solution considering the transceiver power characteristics, the varying system load, and the dynamic channel constraints. Based on this, we derive a low-complexity online scheduling algorithm. Results considering an -ary quadrature amplitude modulation radio show that for a range of scenarios a large power reduction is achieved, compared to the case where only scaling or shutdown is considered.
Karumbu, Premkumar
2011-01-01
We consider the problem of quickest event detection with sleep-wake scheduling in small extent wireless sensor networks in which, at each time slot, each sensor node in the awake state observes a sample and communicates the information to the fusion centre. The sensor nodes in the sleep state do not sample or communicate any information to the fusion centre (FC), thereby conserving energy. At each time slot, the FC, after having received the samples from the sensor nodes in the wake state, makes a decision to stop (and thus declare that the event has occurred) or to continue observing. If it decides to continue, the FC also makes the decision of choosing the number of sensor nodes to be in the wake state in the next time slot. We consider three alternative approaches to the problem of choosing the number of sensor nodes to be in the wake state in time slot k+1, based on the information available at time slot k, namely, 1. optimal control of M_{k+1}, the number of sensor nodes to be in the awake state in time ...
Chowdhury, Prasun; Sanyal, Salil K
2012-01-01
In this paper, a new technique for cross layer design, based on present Eb/N0 (bit energy per noise density) ratio of the connections and target values of the Quality of Service (QoS) information parameters from MAC layer, is proposed to dynamically select the Modulation and Coding Scheme (MCS) at the PHY layer for WiMAX Broadband Wireless Access (BWA) networks. The QoS information parameter includes New Connection Blocking Probability (NCBP), Hand off Connection Dropping Probability (HCDP) and Connection Outage Probability (COP). In addition, a Signal to Interference plus Noise Ratio (SINR) based Call Admission Control (CAC) algorithm and Queue based Scheduling algorithm are integrated for the cross layer design. An analytical model using the Continuous Time Markov Chain (CTMC) is developed for performance evaluation of the algorithms under various MCS. The effect of Eb/No is observed for QoS information parameters in order to determine its optimum range. Simulation results show that the integrated CAC and p...
Gang Li
2016-09-01
Full Text Available The spatial–temporal correlation is an important feature of sensor data in wireless sensor networks (WSNs. Most of the existing works based on the spatial–temporal correlation can be divided into two parts: redundancy reduction and anomaly detection. These two parts are pursued separately in existing works. In this work, the combination of temporal data-driven sleep scheduling (TDSS and spatial data-driven anomaly detection is proposed, where TDSS can reduce data redundancy. The TDSS model is inspired by transmission control protocol (TCP congestion control. Based on long and linear cluster structure in the tunnel monitoring system, cooperative TDSS and spatial data-driven anomaly detection are then proposed. To realize synchronous acquisition in the same ring for analyzing the situation of every ring, TDSS is implemented in a cooperative way in the cluster. To keep the precision of sensor data, spatial data-driven anomaly detection based on the spatial correlation and Kriging method is realized to generate an anomaly indicator. The experiment results show that cooperative TDSS can realize non-uniform sensing effectively to reduce the energy consumption. In addition, spatial data-driven anomaly detection is quite significant for maintaining and improving the precision of sensor data.
El-Malek, Ahmed H. Abd
2016-05-24
In this paper, we study the performance of multiuser single-input multiple-output mixed radio frequency (RF)/free space optical (FSO) relay network with opportunistic user scheduling. The considered system includes multiple users, one amplify-and-forward relay, one destination, and a multiple-antenna eavesdropper. The users are connected with the relay node through RF links and the relay is connected with the destination through an FSO link. Both maximum ratio combining and selection combining schemes are used at the multiple-antenna relay to combine the signal received from the best user on different antennas. The RF/FSO channels models are assumed to follow Nakagami-m/gamma-gamma fading models with pointing errors. Closed-form expressions are derived for the outage probability, average symbol error probability, and ergodic channel capacity. Then, the power of the selected best user is determined to minimize the system asymptotic outage probability under the dominant RF or FSO link. Then, the considered system secrecy performance is investigated, where the closed-form expressions for the intercept probability are derived. Finally, we propose a new cooperative jamming model in which the worst user is selected by the authorized system to jam the existing eavesdropper. Monte-Carlo simulations are provided to validate the achieved exact and asymptotic results.
Stand for the Network Repeated Game Task Scheduling Algorithm%容忍网络中基于重复博弈的任务调度算法
杨馨
2013-01-01
延迟容忍网络环境具有动态性、异构性等特点，导致传统网格任务调度算法收敛速度慢、局部最优等缺陷，使网格任务调度效率低。为了提高网格任务调度效率，提出一种基于重复博弈的任务调度算法。算法根据任务调度原理和博弈论的特点，建立了网格任务调度模型和性能指标的数学模型，然后采用重复博弈算法对该模型进行优化，提高资源利用率和任务执行效率。仿真实验结果表明，该算法的任务调度策略是可行有效的，提高了任务调度的速度和效率，很好地解决网络任务调度中存在的难题。%Delay tolerance network environment has the dynamic, heterogeneous characteristics, leading to the traditional grid task scheduling algorithm convergence speed is slow, the local superior defect, make the grid task scheduling effi-ciency low. In order to improve the grid task scheduling efficiency, this paper puts forward a repeated game based on the task scheduling algorithm. Task scheduling algorithm according to the principle and the characteristics of game theory, the establishment of a grid task scheduling model and mathematical model of the performance, then the repeated game algorithm to optimize the model, raise the utilization ratio of resource and task performance. The simulation results show that the algorithm of task scheduling strategy is feasible and effective, and improve the speed and efficiency of task scheduling, a very good solution to solve the network scheduling problem existing in.
Joint rate control and scheduling for wireless uplink video streaming
HUANG Jian-wei; LI Zhu; CHIANG Mung; KATSAGGELOS Aggelos K.
2006-01-01
We solve the problem of uplink video streaming in CDMA cellular networks by jointly designing the rate control and scheduling algorithms. In the pricing-based distributed rate control algorithm, the base station announces a price for the per unit average rate it can support, and the mobile devices choose their desired average transmission rates by balancing their video quality and cost of transmission. Each mobile device then determines the specific video frames to transmit by a video summarization process. In the time-division-multiplexing (TDM) scheduling algorithm, the base station collects the information on frames to be transmitted from all devices within the current time window, sorts them in increasing order of deadlines, and schedules the transmissions in a TDM fashion. This joint algorithm takes advantage of the multi-user content diversity, and maximizes the network total utility (i.e., minimize the network total distortion), while satisfying the delivery deadline constraints. Simulations showed that the proposed algorithm significantly outperforms the constant rate provision algorithm.
Microcomputer-based vehicle routing and scheduling: An overview
Klein, A.J.
1987-08-01
Commercially available vehicle-routing and scheduling packages were surveyed to assess capabilities, categorize key characteristics, compare individual packages, and select candidate software for additional testing. Among the key characteristics addressed were backhauling, distance and vehicle travel-time calculation, geocoding, speed zones, natural barriers, time-window constraints, vehicle/stop matching constraints, and other constraints such as vehicle/driver operating costs. The survey included review of vendor literature, telephone interviews, site visits to review software, and the testing of demonstration packages on a set of sample distribution networks. Thirteen packages were reviewed; these were categorized by price and performance as follows; (1) inexpensive packages (costing $2000 or less), which solve the basic vehicle-routing problem but are somewhat limited in their ability to handle large numbers of vehicles and stops; (2) medium-priced systems (from $5000 to $20,000), which offer more capability to handle constraints such as multiple pickup and delivery, time windows, and multiple depots and provide manual intervention capability and enhanced graphics; (3) very expensive systems (from $50,000 to about $150,000), which can handle real-time situations in scheduling last-minute route changes and employ sophisticated graphics tools to change route schedules interactively. Out of the 13 packages, four demonstration vehicle-routing packages were obtained for testing of 4 sample networks; two of the packages were found to be capable of solving most vehicle-routing problem constraints for two versions of 21-city and 30-city networks.
Hedonic Housing Price Model Via BP Neural Network%Hedonic住宅特征价格模型的BP神经网络方法
司继文; 韩莹莹; 罗希
2012-01-01
In this paper, hedonic pricing model is used to assess the housing price in Washington, USA. For the pricing model, in this paper, the crime variables around the house are included. The model is built by hedonic pricing method through using traditional OLS method and neural network to simulate and with data modified by Box-cox transformation. The result shows the change in criminal rate makes the housing price change, and as the distance of crime to the housing and the types of crimes changes, the house price changes from -5. 78% to 2. 08%. In July of 2007 and the whole 2008, the influences of crime on housing price are different. It also shows that neural network is more accurate than the traditional OLS method with 5. 74% higher degree of approximation, and shows better features.%房地产在金融市场中占有举足轻重的地位,其价格变化对整个金融市场有着显著的影响.采用特征价格模型,对美国一线城市2007年6月及2008年的房价进行了相关定价研究.对传统特征价格模型的属性因子进行了扩充,加入房产周边犯罪率因子进行模拟；在数值方法计算方面,首先对数据进行了Box-cox变换,分别采用BP神经网络及传统的最小二乘法进行数值模拟分析,结果表明,房价随犯罪事件类型及发生距离房地产的远近有—5.78％～2.08％的变化；在2008年与2007年6月的不同时段内,犯罪率的变化对房价的影响有所不同.BP神经网络模拟的价格与实际交易价格曲线比传统最小二乘模拟的价格曲线精度高出5.74个百分点.
网络运维中现场作业任务调度的研究%A Research on Field Job Scheduling in Network Operation and Maintenance
许青林; 徐峰; 肖红; 刘沧生; 熊梦琪; 王志
2016-01-01
Due to the scheduling inefficiency in a large number of job requests for the network operation and maintenance of field operations and the jobs being unable to change adjustment issue, an on-site job scheduling algorithm based on improved genetic algorithm for network operation and maintenance is estab-lished. The algorithm is based on job-indirect encoding resources, combined with network operation and maintenance of on-site job resource scheduling features, by setting the upper limit of the number of jobs for each maintenance personnel to avoid excessive burden on maintenance staff, thus helping to improve the quality of service and resource utilization. The simulation results show that the use of genetic algo-rithms is effective in solving the network operation and maintenance resource scheduling.%针对网络运维现场作业调度中大量作业任务请求时效率低下、作业任务有所改变时无法自行调整等问题，提出基于改进遗传算法的网络运维中现场作业调度算法。该算法基于作业任务-资源的间接编码方式，结合网络运维中现场作业资源调度的特点，通过对每个维护人员设置作业任务数量的上限，避免某个维护人员负担任务数量过多，有利于提高服务质量以及资源的利用率。经过仿真实验，结果表明使用遗传算法可有效解决网络运维中资源调度问题。
Zhilong Wang
2014-01-01
Full Text Available In the electricity market, the electricity price plays an inevitable role. Nevertheless, accurate price forecasting, a vital factor affecting both government regulatory agencies and public power companies, remains a huge challenge and a critical problem. Determining how to address the accurate forecasting problem becomes an even more significant task in an era in which electricity is increasingly important. Based on the chaos particle swarm optimization (CPSO, the backpropagation artificial neural network (BPANN, and the idea of bivariate division, this paper proposes a bivariate division BPANN (BD-BPANN method and the CPSO-BD-BPANN method for forecasting electricity price. The former method creatively transforms the electricity demand and price to be a new variable, named DV, which is calculated using the division principle, to forecast the day-ahead electricity by multiplying the forecasted values of the DVs and forecasted values of the demand. Next, to improve the accuracy of BD-BPANN, chaos particle swarm optimization and BD-BPANN are synthesized to form a novel model, CPSO-BD-BPANN. In this study, CPSO is utilized to optimize the initial parameters of BD-BPANN to make its output more stable than the original model. Finally, two forecasting strategies are proposed regarding different situations.
Armstrong, Mark
2008-01-01
This paper surveys recent economic research on price discrimination, both in monopoly and oligopoly markets. Topics include static and dynamic forms of price discrimination, and both final and input markets are considered. Potential antitrust aspects of price discrimination are highlighted throughout the paper. The paper argues that the informational requirements to make accurate policy are very great, and with most forms of price discrimination a laissez-faire policy may be the best availabl...
Nielsen, Søren Bo
2014-01-01
Against a background of rather mixed evidence about transfer pricing practices in multinational enterprises (MNEs) and varying attitudes on the part of tax authorities, this paper explores how multiple aims in transfer pricing can be pursued across four different transfer pricing regimes. A MNE h...
Network Externalities and Behavior-Based Price Discrimination%网络外部性与基于行为的区别定价
董亮; 任剑新
2012-01-01
近年来,基于行为的区别定价成为区别定价领域研究的热点,但是这方面的文献却鲜有涉及到市场中存在着网络外部性的情形。在理性预期的假设下,本文通过一个两阶段双寡头博弈模型分析了网络外部性与基于行为的区别定价对子博弈精炼纳什均衡的影响。在成熟市场上,网络外部性会对具有不同初始市场份额的厂商产生不同影响;在新兴市场上,无论厂商采取何种定价策略,网络外部性都会加剧市场上的竞争,导致厂商利润下降。与统一定价下的子博弈精炼纳什均衡相比,基于行为的区别定价会加剧竞争从而导致厂商利润的下降,但是会造成较多社会福利的无谓损失。%Behavior-based price discrimination has received much attention in the recent economic literatures, but the literatures of this topic rarely deal with status of market with network externalities. Under the assumption of rational expectation, this paper studies the effect of network externalities and behavior - based price discrimination to the subgame perfect Nash equilibrium by using a two - period duopoly model. In a mature market, network externalities would exert varying influences on different firms depending on their initial market share. In a new market,network externalities would increase competition and reduce firms＇ profits no matter what kind of pricing strategy the firms take. Compared with the SPE of uniform pricing, behavior - based price discrimination would increase competition and reduce firms＇ profits,but it also creates more dead -weight loss to the society.
G. INDUMATHI
2011-06-01
Full Text Available Orthogonal Frequency Division Multiplexing (OFDM systems are the major cellular platforms for supporting ubiquitous high-speed mobile applications. However, a number of research challenges remain to be tackled. One of the most important challenges is the design of a judicious packet scheduler that will make efficient use of the spectrum bandwidth. Due to the multicarrier nature of the OFDM systems, the applicability and performance of traditional wireless packet scheduling algorithms, which are designed usually for single-carrier systems, are largely unknown. In this paper we present a new scheduler which includes packet scheduling and resource mapping which takes. The proposed algorithm is based on a cross-layer design in that the scheduler is aware of both the channel at the physical layer and the queue state at the data link layer information to achieve proportional fairness while maximizing each user’s packet level QoS performance. The performance of the proposed work is compared to that of the round-robin and weighted fair queuing schedulers. It is observed that from the simulation that the proposed scheduling with adaptive parameter selection provides enhanced performance in terms of queuing delay and spectral efficiency. Also we analyze the achieved fairness of the schemes in terms of different fairness indices available in literature.
气象网络控制系统（NCS）的调度算法分析%Analysis of Scheduling Algorithm of Meteorological Network Control System
梁心雄; 黎德波; 罗胜平
2015-01-01
网络控制系统非固定执行时间的调度策略是基于先进控制理论的反馈调度策略，其策略是并行计算减少算法的执行时间来获得更高的计算效率，解决更复杂的问题并加快求解过程。文中着重从NCS调度数据分类、优先级、系统调度分析、方法四个角度进行分析，得出气象业务网络系统性能的优化映射为较低层次的系统参数优化、网络控制系统的稳定运行是准确做出天气预报并及时服务的基本保证，网络的开放性和共享性在方便人们使用的同时，气象信息网络调度应尽量避免信息的冲突和拥塞现象的发生，力求达到系统设计与网络实现的总体性能优化的目标。%Network control system scheduling strategy of fixed execution time is a feedback scheduling strategy based on the theory of the advanced control,adopting parallel computing to reduce algorithm execution time gains higher computational efficiency to solve the more complex problem and the solution is to speed up the process. In this paper,emphatically from NCS scheduling data classification,priority, system scheduling analysis and methods,conduct an analysis and get that the system parameter optimization of lower levels of meteoro-logical operational network system performance optimization mapping and the stable operation of the network control system is the basic guarantee to accurately make a weather forecasting and the timely service,network’ s openness and sharing in convenience for the people, at the same time,the meteorological information network scheduling should try to avoid conflict and congestion,reaching the goal of over-all performance optimization of the system design and network realization.
银行卡网络交换费差别定价模型研究%Interchange Fee Discrimination Pricing Model of a Bankcard Network
孙毅坤; 胡祥培
2011-01-01
The pricing of card payments' service is a difficult and challenging issue to research, which is closely related to the stability and prosperity of card payments' market. In consideration of the fact that the interchange fee lies in the center of the pricing system of a bankcard network, which is normally used to adjust the benefits between the issuers and the acquirers. The interchange fee pricing principle was given first on the basis of the price discrimination theories, in which the statistical and mathematical methods were combined with the specific characteristics and the demand of card payments development. And then the interchange fee discrimination pricing model for the card consumption payments across different banks was constructed under the processes of optimizing the classification of the merchants, introducing the level-pricing method and adopting the two-part pricing way. By data analysis, a new merchants' classification method and dynamic adjustment mechanism based on the transactions characteristics, a specific level pricing method and detail two-part pricing standards were given finally. The research results indicate that this paper contributed by exploring the interchange fee discrimination method and submitting the relative optimal paths based on current situations, which is not only helpful for commercial banks and regulation departments to make pricing decisions or to make relative policies, but also useful to push the deeper research of the electronic payments and pricing theories further.%银行卡支付服务定价是金融领域富有挑战性的研究难题,它事关银行卡交易市场的稳定和繁荣.交换费是银行卡网络价格体系的核心,对发卡机构与收单机构的利益关系具有重要的调节作用.结合中国银行卡市场的特殊性以及发展需求,基于差别定价理论,采用数量分析方法,提出优化商户分类、引入层级定价与二部制定价相结合的交换费优化思路,建立基
无线Mesh网络中的自适应队列调度算法研究%Research on Adaptive Queue Scheduling Algorithm in Wireless Mesh Networks
夏汉铸; 王志刚
2014-01-01
针对无线mesh网络的网络特性，分析了无线网络中的队列调度算法，提出了一种自适应的队列调度算法AQSM，详细讨论了该算法的具体实现过程及参数变化规则，通过仿真验证了该算法在提高网络性能的同时还可以实现对不同业务流的业务区分。%Wireless Mesh networks (WMNs) have emerged as a key technology for next-generation wireless networking. Queue scheduling algorithm is an important research area in wireless mesh network. In order to improve the performance of WMN and realize DiffServ between different traffic flows, an adaptive queue scheduling algorithm(AQSM)is presented, and the specific implementation process and parameter variation rules are discussed in detail. The analysis and simulation results show that the AQSM algorithm can increase the performance of the wireless Mesh networks and realize the service division of different service flows.
Towards Providing Low-Risk and Economically Feasible Network Data Transfer Services
Andreica, Mugurel Ionut; Tipa, Stelian
2010-01-01
In the first part of this paper we present the first steps towards providing low-risk and economically feasible network data transfer services. We introduce three types of data transfer services and present general guidelines and algorithms for managing service prices, risks and schedules. In the second part of the paper we solve two packet scheduling cost optimization problems and present efficient algorithms for identifying maximum weight (k-level-) caterpillar subtrees in tree networks.
Physician Fee Schedule Carrier Specific Files
U.S. Department of Health & Human Services — The Centers for Medicare and Medicaid Services (CMS) has condensed all 56 Physician Fee Schedule (PFS) carrier specific pricing files into one zip file. It is...
Estimating exponential scheduling preferences
Hjorth, Katrine; Börjesson, Maria; Engelson, Leonid
2015-01-01
Different assumptions about travelers' scheduling preferences yield different measures of the cost of travel time variability. Only few forms of scheduling preferences provide non-trivial measures which are additive over links in transport networks where link travel times are arbitrarily...... of car drivers' route and mode choice under uncertain travel times. Our analysis exposes some important methodological issues related to complex non-linear scheduling models: One issue is identifying the point in time where the marginal utility of being at the destination becomes larger than the marginal...
Sensor Scheduling for Target Tracking in Networks of Active Sensors%有源传感网络中目标跟踪的传感器调度方法
肖文栋; 吴健康; 谢立华; 董梁
2006-01-01
Wireless sensor network (WSN) of active sensors suffers from serious inter-sensor interference (ISI) and imposes new design and implementation challenges. In this paper, based on the ultrasonic sensor network, two time-division based distributed sensor scheduling schemes are proposed to deal with ISI by scheduling sensors periodically and adaptively respectively. Extended Kalman filter (EKF) is used as the tracking algorithm in distributed manner. Simulation results show that the adaptive sensor scheduling scheme can achieve superior tracking accuracy with faster tracking convergence speed.
Lara, Guilherme R.; Polli, Helton L.; Esser, Eduardo M.; Lueders, Ricardo; Neves Junior, Flavio; Magatao, Leandro; Stebel, Sergio L. [Universidade Tecnologica Federal do Parana (UTFPR), Curitiba, PR (Brazil); Ribas, Paulo C. [PETROBRAS S.A., Rio de Janeiro, RJ (Brazil). Centro de Pesquisas (CENPES)
2008-07-01
This paper addresses the development and the architecture of a corporative package to aid the operational decision-making of the scheduling activities in a real-world pipeline network for oil derivatives. The system was developed based on a service-oriented architecture, allowing the development of Web applications to define the network scheduling, as well as graphic display of the movements. The solution of the scheduling is generated by an optimization block as a service of this application. However, this paper emphasizes the description of the architecture and its functionalities, which was defined with the help of experienced programmers. (author)
Magalhaes, Marcus V.; Fraga, Eder T. [PETROBRAS, Rio de Janeiro, RJ (Brazil); Shah, Nilay [Imperial College, London (United Kingdom)
2004-07-01
This work addresses the refinery scheduling problem using mathematical programming techniques. The solution adopted was to decompose the entire refinery model into a crude oil scheduling and a product scheduling problem. The envelope for the crude oil scheduling problem is composed of a terminal, a pipeline and the crude area of a refinery, including the crude distillation units. The solution method adopted includes a decomposition technique based on the topology of the system. The envelope for the product scheduling comprises all tanks, process units and products found in a refinery. Once crude scheduling decisions are Also available the product scheduling is solved using a rolling horizon algorithm. All models were tested with real data from PETROBRAS' REFAP refinery, located in Canoas, Southern Brazil. (author)
Huang, Zixiong; Liu, Huixin; Wang, Yizeng; Zhang, Chunfang; Xu, Tao
2017-08-01
To figure out optimal bacillus Calmette-Guerin (BCG) maintenance schedules for non-muscle-invasive bladder cancer (NMIBC) patients by comparing different schedules in a systematic review using conventional and network meta-analysis. Literature was searched in the databases of Medline, Embase, Cochrane library, Clinicaltrials.gov, Wanfang, CNKI and SinoMed in April 2016 and 9 randomized clinical trials comparing intravesical BCG maintenance therapy with BCG induction-only therapy or comparing different BCG maintenance schedules (induction-only, 1 year, 1.5 year, 2 year, 3 year maintenance) in NMIBC patients were included. Conventional and network meta-analyses within a Bayesian framework were performed to calculate odds ratios of tumor recurrence, progression and side effects (cystitis, hematuria, general malaise and fever). The surface under the cumulative ranking curve (SUCRA) mean ranking was used to obtain schedule hierarchy. Data from 1951 patients showed that longer-term maintenance BCG therapy does not significantly decrease tumor recurrence and progression rate of NMIBC compared to shorter-term maintenance BCG therapy. However, longer-maintenance therapy does not increase side effect incidence compared to induction-only therapy. According to SUCRA results, induction-only therapy has the highest probability of recurrence and progression but least probability of side effects. Longer BCG maintenance therapy (such as 3 years) is not superior to shorter maintenance therapy (such as 1 year). But maintenance therapy overall is better than induction-only BCG therapy while not increasing side effects. Though further evidence and clinical practice with balanced confounding factors (risk stratification and BCG strain) are wished for, the current study suggests the common use of 1 year intravesical BCG instillation for NMIBC patients.
Bisheng He
2014-01-01
Full Text Available A time-space network based optimization method is designed for high-speed rail train timetabling problem to improve the service level of the high-speed rail. The general time-space path cost is presented which considers both the train travel time and the high-speed rail operation requirements: (1 service frequency requirement; (2 stopping plan adjustment; and (3 priority of train types. Train timetabling problem based on time-space path aims to minimize the total general time-space path cost of all trains. An improved branch-and-price algorithm is applied to solve the large scale integer programming problem. When dealing with the algorithm, a rapid branching and node selection for branch-and-price tree and a heuristic train time-space path generation for column generation are adopted to speed up the algorithm computation time. The computational results of a set of experiments on China’s high-speed rail system are presented with the discussions about the model validation, the effectiveness of the general time-space path cost, and the improved branch-and-price algorithm.
A Dynamic Scheduling Algorithm Based on UWB in Wearable Network%一种基于UWB穿戴式网络的调度算法
夏兵; 李光耀
2014-01-01
Wearable computer is a hot research topic in recent years;however multiple nodes communication between each other in weara-ble network has been the important impact of the development of wearable computer. So it is necessary to improve the wearable network communication. The wearable computers and wearable network are introduced,discussing several kinds of network technologies which are frequently used in the wearable network. And then introduced the UWB ( Ultra-Wide Band) structure model,and UWB communication mechanism,and a dynamic scheduling algorithm based on UWB in wearable network is introduced which has priority in the scheduling al-gorithm. This scheduling algorithm can improve the performance between each nodes in wearable network and help promote the develop-ment of wearable computer.%可穿戴式计算机是近几年的一个研究热点，穿戴式网络多个节点之间的协调通信一直是影响穿戴式计算机发展的一个重要原因，因此有必要对穿戴式网络通信进行优化。文中介绍了可穿戴式计算机以及穿戴式网络。论述了穿戴式网络中常用的几种网络技术的优缺点。然后重点解析了UWB(Ultra-Wide Band)的结构模型，以及UWB通信机制，在UWB通信机制的基础上引入了动态调度的思想，由此引出具有优先级的动态UWB网络调度算法。此调度算法能够很好地协调穿戴式网络节点之前的通信，有利于推进可穿戴式计算机的发展。
Store-Forward and its implications for Proportional Scheduling
Walton, N.S.
2014-01-01
The Proportional Scheduler was recently proposed as a scheduling algorithm for multi-hop switch networks. For these networks, the BackPressure scheduler is the classical benchmark. For networks with fixed routing, the Proportional Scheduler is maximum stable, myopic and, furthermore, will alleviate
Juan D Velásquez
2008-12-01
Full Text Available Una red neuronal autorregresiva es estimada para el precio mensual brasileño de corto plazo de la electricidad, la cual describe mejor la dinámica de los precios que un modelo lineal autorregresivo y que un perceptrón multicapa clásico que usan las mismas entradas y neuronas en la capa oculta. El modelo propuesto es especificado usando un procedimiento estadístico basado en el contraste del radio de verosimilitud. El modelo pasa una batería de pruebas de diagnóstico. El procedimiento de especificación propuesto permite seleccionar el número de unidades en la capa oculta y las entradas a la red neuronal, usando pruebas estadísticas que tienen en cuenta la cantidad de los datos y el ajuste del modelo a la serie de precios. La especificación del modelo final demuestra que el precio para el próximo mes es una función no lineal del precio actual, de la energía afluente actual y de la energía almacenada en el embalse equivalente en el mes actual y dos meses atrás.An autoregressive neural network model is estimated for the monthly Brazilian electricity spot price, which describes the prices dynamics better than a linear autoregressive model and a classical multilayer perceptron using the same input and neurons in the hidden layer. The proposed model is specified using a statistical procedure based on a likelihood ratio test. The model passes a battery of diagnostic tests. The proposed specification procedure allows us to select the number of units in hidden layer and the inputs to the neural network based on statistical tests, taking into account the number of data and the model fitting to the price time series. The final model specification demonstrates that the price for the next month is a nonlinear function of the current price, the current energy inflow, and the energy saved in the equivalent reservoir in the current month and two months ago.
Network Resources Optimization Scheduling Model in Cloud Computing%云计算中网络资源配比优化调度模型仿真
孟湘来; 马小雨
2015-01-01
Cloud computing server environment is different, once appear congestion network resources, the regional using different forms of network resource scheduling. The single way of network resource scheduling is difficult to meet the requirements of cloud computing network complexity. Put forward a kind of based on supply and demand equilibrium mechanism of cloud computing network planning model, quadratic weighted average method was used to construct network planning model limitation of cloud computing model to adjust the number assigned to the stretch of road network resources, USES the AGV control network congestion evaluation problems, analysis of cloud computing network equipment requirements and the balance between supply and demand mechanism, the number of nodes oriented, cost, and congestion degree three factors clear cloud computing network congestion intensity evaluation index system, determine the time limits and pressing for resources distribution. Experimental results show that, under this kind of model of cloud computing congestion relief efficiency, cost and utility degree is superior to the traditional model, has higher application value.%云计算服务器的环境不同，一旦出现网络资源拥塞，各区域采用的网络资源调度形式也不同。当前单一的网络资源调度方式很难满足云计算网络复杂性的要求。提出一种基于需求和供给均衡机制的云计算网络规划模型，采用二次加权平均方法构建云计算时效网络规划模型，模型不断调整已分配到路段上的网络资源数量，采用AGV控制网络堵塞评估问题，分析云计算网络设备需求的确定和供需平衡机制，面向节点数、成本以及拥塞程度三个因素明确云计算网络拥塞强度的评估指标体系，确定资源配送的时限要求和紧迫程度。实验结果说明，该种模型下的云计算拥塞救助效率、成本以及效用度都优于传统模型，具有较高的应用价值。
Internet Resource Pricing Models, Mechanisms, and Methods
He, Huan; Liu, Ying
2011-01-01
With the fast development of video and voice network applications, CDN (Content Distribution Networks) and P2P (Peer-to-Peer) content distribution technologies have gradually matured. How to effectively use Internet resources thus has attracted more and more attentions. For the study of resource pricing, a whole pricing strategy containing pricing models, mechanisms and methods covers all the related topics. We first introduce three basic Internet resource pricing models through an Internet cost analysis. Then, with the evolution of service types, we introduce several corresponding mechanisms which can ensure pricing implementation and resource allocation. On network resource pricing methods, we discuss the utility optimization in economics, and emphasize two classes of pricing methods (including system optimization and entities' strategic optimizations). Finally, we conclude the paper and forecast the research direction on pricing strategy which is applicable to novel service situation in the near future.
Nonlinear Pricing in Energy and Environmental Markets
Ito, Koichiro
This dissertation consists of three empirical studies on nonlinear pricing in energy and environmental markets. The first investigates how consumers respond to multi-tier nonlinear price schedules for residential electricity. Chapter 2 asks a similar research question for residential water pricing. Finally, I examine the effect of nonlinear financial rewards for energy conservation by applying a regression discontinuity design to a large-scale electricity rebate program that was implemented in California. Economic theory generally assumes that consumers respond to marginal prices when making economic decisions, but this assumption may not hold for complex price schedules. The chapter "Do Consumers Respond to Marginal or Average Price? Evidence from Nonlinear Electricity Pricing" provides empirical evidence that consumers respond to average price rather than marginal price when faced with nonlinear electricity price schedules. Nonlinear price schedules, such as progressive income tax rates and multi-tier electricity prices, complicate economic decisions by creating multiple marginal prices for the same good. Evidence from laboratory experiments suggests that consumers facing such price schedules may respond to average price as a heuristic. I empirically test this prediction using field data by exploiting price variation across a spatial discontinuity in electric utility service areas. The territory border of two electric utilities lies within several city boundaries in southern California. As a result, nearly identical households experience substantially different nonlinear electricity price schedules. Using monthly household-level panel data from 1999 to 2008, I find strong evidence that consumers respond to average price rather than marginal or expected marginal price. I show that even though this sub-optimizing behavior has a minimal impact on individual welfare, it can critically alter the policy implications of nonlinear pricing. The second chapter " How Do