Bandwidth Allocation Considering Priorities among Multimedia Components in Mobile Networks

OpenAIRE

Shigeki, Shiokawa; Shuji, Tasaka

2001-01-01

This paper proposes a bandwidth allocation scheme which improves degradation of communication quality due to handoffs in mobile multimedia networks. In general, a multimedia call consists of several component calls. For example, a video phone call consists of a voice call and a video call. In realistic environments, each component call included in one multimedia call may have different requirements for quality-of-service (QoS) from each other, and priorities among these component calls often ...

Bandwidth auction for SVC streaming in dynamic multi-overlay

Science.gov (United States)

Xiong, Yanting; Zou, Junni; Xiong, Hongkai

2010-07-01

In this paper, we study the optimal bandwidth allocation for scalable video coding (SVC) streaming in multiple overlays. We model the whole bandwidth request and distribution process as a set of decentralized auction games between the competing peers. For the upstream peer, a bandwidth allocation mechanism is introduced to maximize the aggregate revenue. For the downstream peer, a dynamic bidding strategy is proposed. It achieves maximum utility and efficient resource usage by collaborating with a content-aware layer dropping/adding strategy. Also, the convergence of the proposed auction games is theoretically proved. Experimental results show that the auction strategies can adapt to dynamic join of competing peers and video layers.

A multiprocessor computer simulation model employing a feedback scheduler/allocator for memory space and bandwidth matching and TMR processing

Science.gov (United States)

Bradley, D. B.; Irwin, J. D.

1974-01-01

A computer simulation model for a multiprocessor computer is developed that is useful for studying the problem of matching multiprocessor's memory space, memory bandwidth and numbers and speeds of processors with aggregate job set characteristics. The model assumes an input work load of a set of recurrent jobs. The model includes a feedback scheduler/allocator which attempts to improve system performance through higher memory bandwidth utilization by matching individual job requirements for space and bandwidth with space availability and estimates of bandwidth availability at the times of memory allocation. The simulation model includes provisions for specifying precedence relations among the jobs in a job set, and provisions for specifying precedence execution of TMR (Triple Modular Redundant and SIMPLEX (non redundant) jobs.

Cluster Formation and Joint Power-Bandwidth Allocation for Imperfect NOMA in DL-HetNets

KAUST Repository

Celik, Abdulkadir; Al-Qahtani, Fawaz; Radaydeh, Redha; Alouini, Mohamed-Slim

2017-01-01

and estimation errors. Then, a generic cluster formation (CF) and Power-Bandwidth Allocation (PBA) is formulated as a mixed-integer non-linear programming (MINLP) problem for downlink (DL) heterogeneous networks (HetNets). After dividing the MINLP problem

Bandwidth Optimization in Centralized WLANs for Different Traffic Types

Directory of Open Access Journals (Sweden)

Haines RJ

2007-01-01

Full Text Available Allocating bandwidth between different forms of coexisting traffic (such as web-browsing, streaming, and telephony within a wireless LAN is a challenging and interesting problem. Centralized coordination functions in wireless LANs offer several advantages over distributed approaches, having the benefit of a system overview at the controller, but obtaining a stable configuration of bandwidth allocation for the system is nontrivial. We present, review, and compare different mechanisms to achieve this end, and a number of different means of obtaining the configurations themselves. We describe an analytical model of the system under consideration and present two mathematical approaches to derive solutions for any system configuration and deployment, along with an adaptive feedback-based solution. We also describe a comprehensive simulation-based model for the problem, and a prototype that allows comparison of these approaches. Our investigations demonstrate that a self-adaptive dynamic approach far outperforms any static scheme, and that using a mathematical model to produce the configurations themselves confers several advantages.

A mechanism design approach to bandwidth allocation in tactical data networks

Science.gov (United States)

Mour, Ankur

The defense sector is undergoing a phase of rapid technological advancement, in the pursuit of its goal of information superiority. This goal depends on a large network of complex interconnected systems - sensors, weapons, soldiers - linked through a maze of heterogeneous networks. The sheer scale and size of these networks prompt behaviors that go beyond conglomerations of systems or `system-of-systems'. The lack of a central locus and disjointed, competing interests among large clusters of systems makes this characteristic of an Ultra Large Scale (ULS) system. These traits of ULS systems challenge and undermine the fundamental assumptions of today's software and system engineering approaches. In the absence of a centralized controller it is likely that system users may behave opportunistically to meet their local mission requirements, rather than the objectives of the system as a whole. In these settings, methods and tools based on economics and game theory (like Mechanism Design) are likely to play an important role in achieving globally optimal behavior, when the participants behave selfishly. Against this background, this thesis explores the potential of using computational mechanisms to govern the behavior of ultra-large-scale systems and achieve an optimal allocation of constrained computational resources Our research focusses on improving the quality and accuracy of the common operating picture through the efficient allocation of bandwidth in tactical data networks among self-interested actors, who may resort to strategic behavior dictated by self-interest. This research problem presents the kind of challenges we anticipate when we have to deal with ULS systems and, by addressing this problem, we hope to develop a methodology which will be applicable for ULS system of the future. We build upon the previous works which investigate the application of auction-based mechanism design to dynamic, performance-critical and resource-constrained systems of interest

Energy-efficient orthogonal frequency division multiplexing-based passive optical network based on adaptive sleep-mode control and dynamic bandwidth allocation

Science.gov (United States)

Zhang, Chongfu; Xiao, Nengwu; Chen, Chen; Yuan, Weicheng; Qiu, Kun

2016-02-01

We propose an energy-efficient orthogonal frequency division multiplexing-based passive optical network (OFDM-PON) using adaptive sleep-mode control and dynamic bandwidth allocation. In this scheme, a bidirectional-centralized algorithm named the receiver and transmitter accurate sleep control and dynamic bandwidth allocation (RTASC-DBA), which has an overall bandwidth scheduling policy, is employed to enhance the energy efficiency of the OFDM-PON. The RTASC-DBA algorithm is used in an optical line terminal (OLT) to control the sleep mode of an optical network unit (ONU) sleep and guarantee the quality of service of different services of the OFDM-PON. The obtained results show that, by using the proposed scheme, the average power consumption of the ONU is reduced by ˜40% when the normalized ONU load is less than 80%, compared with the average power consumption without using the proposed scheme.

Average Bandwidth Allocation Model of WFQ

Directory of Open Access Journals (Sweden)

Tomáš Balogh

2012-01-01

Full Text Available We present a new iterative method for the calculation of average bandwidth assignment to traffic flows using a WFQ scheduler in IP based NGN networks. The bandwidth assignment calculation is based on the link speed, assigned weights, arrival rate, and average packet length or input rate of the traffic flows. We prove the model outcome with examples and simulation results using NS2 simulator.

A Bandwidth-Optimized Multi-Core Architecture for Irregular Applications

Energy Technology Data Exchange (ETDEWEB)

Secchi, Simone; Tumeo, Antonino; Villa, Oreste

2012-05-31

This paper presents an architecture template for next-generation high performance computing systems specifically targeted to irregular applications. We start our work by considering that future generation interconnection and memory bandwidth full-system numbers are expected to grow by a factor of 10. In order to keep up with such a communication capacity, while still resorting to fine-grained multithreading as the main way to tolerate unpredictable memory access latencies of irregular applications, we show how overall performance scaling can benefit from the multi-core paradigm. At the same time, we also show how such an architecture template must be coupled with specific techniques in order to optimize bandwidth utilization and achieve the maximum scalability. We propose a technique based on memory references aggregation, together with the related hardware implementation, as one of such optimization techniques. We explore the proposed architecture template by focusing on the Cray XMT architecture and, using a dedicated simulation infrastructure, validate the performance of our template with two typical irregular applications. Our experimental results prove the benefits provided by both the multi-core approach and the bandwidth optimization reference aggregation technique.

Resource Allocation for the Multiband Relay Channel: A Building Block for Hybrid Wireless Networks

Directory of Open Access Journals (Sweden)

Kyounghwan Lee

2010-01-01

Full Text Available We investigate optimal resource allocation for the multiband relay channel. We find the optimal power and bandwidth allocation strategies that maximize the bounds on the capacity, by solving the corresponding max-min optimization problem. We provide sufficient conditions under which the associated max-min problem is equivalent to a supporting plane problem, which renders the solution for an arbitrary number of bands tractable. In addition, the sufficient conditions derived are general enough so that a class of utility functions can be accommodated with this formulation. As an example, we concentrate on the case where the source has two bands and the relay has a single band available and find the optimal resource allocation. We observe that joint power and bandwidth optimization always yields higher achievable rates than power optimization alone, establishing the merit of bandwidth sharing. Motivated by our analytical results, we examine a simple scenario where new channels become available for a transmitter to communicate; that is, new source to relay bands are added to a frequency division relay network. Given the channel conditions of the network, we establish the guidelines on how to allocate resources in order to achieve higher rates, depending on the relative quality of the available links.

Optimization of Quantum-Dot Molecular Beam Epitaxy for Broad Spectral Bandwidth Devices

KAUST Repository

Majid, Mohammed Abdul

2012-12-01

The optimization of the key growth parameters for broad spectral bandwidth devices based on quantum dots is reported. A combination of atomic force microscopy, photoluminescence of test samples, and optoelectronic characterization of superluminescent diodes (SLDs) is used to optimize the growth conditions to obtain high-quality devices with large spectral bandwidth, radiative efficiency (due to a reduced defective-dot density), and thus output power. The defective-dot density is highlighted as being responsible for the degradation of device performance. An SLD device with 160 nm of bandwidth centered at 1230 nm is demonstrated.

Optimization of Quantum-Dot Molecular Beam Epitaxy for Broad Spectral Bandwidth Devices

KAUST Repository

Majid, Mohammed Abdul; Hugues, M.; Vézian, S.; Childs, D. T. D.; Hogg, R. A.

2012-01-01

The optimization of the key growth parameters for broad spectral bandwidth devices based on quantum dots is reported. A combination of atomic force microscopy, photoluminescence of test samples, and optoelectronic characterization of superluminescent diodes (SLDs) is used to optimize the growth conditions to obtain high-quality devices with large spectral bandwidth, radiative efficiency (due to a reduced defective-dot density), and thus output power. The defective-dot density is highlighted as being responsible for the degradation of device performance. An SLD device with 160 nm of bandwidth centered at 1230 nm is demonstrated.

Optimal resource allocation for distributed video communication

CERN Document Server

He, Yifeng

2013-01-01

While most books on the subject focus on resource allocation in just one type of network, this book is the first to examine the common characteristics of multiple distributed video communication systems. Comprehensive and systematic, Optimal Resource Allocation for Distributed Video Communication presents a unified optimization framework for resource allocation across these systems. The book examines the techniques required for optimal resource allocation over Internet, wireless cellular networks, wireless ad hoc networks, and wireless sensor networks. It provides you with the required foundat

Low and Expensive Bandwidth Remains Key Bottleneck for ...

African Journals Online (AJOL)

These bottlenecks have dwarfed the expectations of the citizens to fully participate in the new world economic order galvanized by e-commerce and world trade. It is estimated that M.I.T in Boston USA has bandwidth allocation that surpasses all the bandwidth allocated to Nigeria put together. Low bandwidth has been found ...

Bandwidth Management in Wireless Home Networks for IPTV Solutions

Directory of Open Access Journals (Sweden)

Tamás Jursonovics

2013-01-01

Full Text Available The optimal allocation of the retransmission bandwidth is essential for IPTV service providers to ensure maximal service quality. This paper highlights the relevance of the wireless transport in today’s IPTV solution and discusses how this new media affects the existing broadcast technologies. A new Markovian channel model is developed to address the optimization issues of the retransmission throughput, and a new method is presented which is evaluated by empirical measurements followed by mathematical analysis.

Optimal Computing Budget Allocation for Particle Swarm Optimization in Stochastic Optimization.

Science.gov (United States)

Zhang, Si; Xu, Jie; Lee, Loo Hay; Chew, Ek Peng; Wong, Wai Peng; Chen, Chun-Hung

2017-04-01

Particle Swarm Optimization (PSO) is a popular metaheuristic for deterministic optimization. Originated in the interpretations of the movement of individuals in a bird flock or fish school, PSO introduces the concept of personal best and global best to simulate the pattern of searching for food by flocking and successfully translate the natural phenomena to the optimization of complex functions. Many real-life applications of PSO cope with stochastic problems. To solve a stochastic problem using PSO, a straightforward approach is to equally allocate computational effort among all particles and obtain the same number of samples of fitness values. This is not an efficient use of computational budget and leaves considerable room for improvement. This paper proposes a seamless integration of the concept of optimal computing budget allocation (OCBA) into PSO to improve the computational efficiency of PSO for stochastic optimization problems. We derive an asymptotically optimal allocation rule to intelligently determine the number of samples for all particles such that the PSO algorithm can efficiently select the personal best and global best when there is stochastic estimation noise in fitness values. We also propose an easy-to-implement sequential procedure. Numerical tests show that our new approach can obtain much better results using the same amount of computational effort.

Optimal defense resource allocation in scale-free networks

Science.gov (United States)

Zhang, Xuejun; Xu, Guoqiang; Xia, Yongxiang

2018-02-01

The robustness research of networked systems has drawn widespread attention in the past decade, and one of the central topics is to protect the network from external attacks through allocating appropriate defense resource to different nodes. In this paper, we apply a specific particle swarm optimization (PSO) algorithm to optimize the defense resource allocation in scale-free networks. Results reveal that PSO based resource allocation shows a higher robustness than other resource allocation strategies such as uniform, degree-proportional, and betweenness-proportional allocation strategies. Furthermore, we find that assigning less resource to middle-degree nodes under small-scale attack while more resource to low-degree nodes under large-scale attack is conductive to improving the network robustness. Our work provides an insight into the optimal defense resource allocation pattern in scale-free networks and is helpful for designing a more robust network.

Optimization of Gain, Impedance, and Bandwidth of Yagi-Uda Array Using Particle Swarm Optimization

Directory of Open Access Journals (Sweden)

Munish Rattan

2008-01-01

Full Text Available Particle swarm optimization (PSO is a new, high-performance evolutionary technique, which has recently been used for optimization problems in antennas and electromagnetics. It is a global optimization technique-like genetic algorithm (GA but has less computational cost compared to GA. In this paper, PSO has been used to optimize the gain, impedance, and bandwidth of Yagi-Uda array. To evaluate the performance of designs, a method of moments code NEC2 has been used. The results are comparable to those obtained using GA.

Bandwidth Optimization of Normal Equation Matrix in Bundle Block Adjustment in Multi-baseline Rotational Photography

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WANG Xiang

2016-02-01

Full Text Available A new bandwidth optimization method of normal equation matrix in bundle block adjustment in multi-baseline rotational close range photography by image index re-sorting is proposed. The equivalent exposure station of each image is calculated by its object space coverage and the relationship with other adjacent images. Then, according to the coordinate relations between equivalent exposure stations, new logical indices of all images are computed, based on which, the optimized bandwidth value can be obtained. Experimental results show that the bandwidth determined by our proposed method is significantly better than its original value, thus the operational efficiency, as well as the memory consumption of multi-baseline rotational close range photography in real-data applications, is optimized to a certain extent.

Optimal allocation of resources in systems

International Nuclear Information System (INIS)

Derman, C.; Lieberman, G.J.; Ross, S.M.

1975-01-01

In the design of a new system, or the maintenance of an old system, allocation of resources is of prime consideration. In allocating resources it is often beneficial to develop a solution that yields an optimal value of the system measure of desirability. In the context of the problems considered in this paper the resources to be allocated are components already produced (assembly problems) and money (allocation in the construction or repair of systems). The measure of desirability for system assembly will usually be maximizing the expected number of systems that perform satisfactorily and the measure in the allocation context will be maximizing the system reliability. Results are presented for these two types of general problems in both a sequential (when appropriate) and non-sequential context

Optimal International Asset Allocation with Time-varying Risk

OpenAIRE

Flavin, Thomas; Wickens, M.R.

2006-01-01

This paper examines the optimal allocation each period of an internationally diversified portfolio from the different points of view of a UK and a US investor. We find that investor location affects optimal asset allocation. The presence of exchange rate risk causes the markets to appear not fully integrated and creates a preference for home assets. Domestic equity is the dominant asset in the optimal portfolio for both investors, but the US investor bears less risk than the UK...

Optimizing 4DCBCT projection allocation to respiratory bins

International Nuclear Information System (INIS)

O’Brien, Ricky T; Kipritidis, John; Shieh, Chun-Chien; Keall, Paul J

2014-01-01

4D cone beam computed tomography (4DCBCT) is an emerging image guidance strategy used in radiotherapy where projections acquired during a scan are sorted into respiratory bins based on the respiratory phase or displacement. 4DCBCT reduces the motion blur caused by respiratory motion but increases streaking artefacts due to projection under-sampling as a result of the irregular nature of patient breathing and the binning algorithms used. For displacement binning the streak artefacts are so severe that displacement binning is rarely used clinically. The purpose of this study is to investigate if sharing projections between respiratory bins and adjusting the location of respiratory bins in an optimal manner can reduce or eliminate streak artefacts in 4DCBCT images. We introduce a mathematical optimization framework and a heuristic solution method, which we will call the optimized projection allocation algorithm, to determine where to position the respiratory bins and which projections to source from neighbouring respiratory bins. Five 4DCBCT datasets from three patients were used to reconstruct 4DCBCT images. Projections were sorted into respiratory bins using equispaced, equal density and optimized projection allocation. The standard deviation of the angular separation between projections was used to assess streaking and the consistency of the segmented volume of a fiducial gold marker was used to assess motion blur. The standard deviation of the angular separation between projections using displacement binning and optimized projection allocation was 30%–50% smaller than conventional phase based binning and 59%–76% smaller than conventional displacement binning indicating more uniformly spaced projections and fewer streaking artefacts. The standard deviation in the marker volume was 20%–90% smaller when using optimized projection allocation than using conventional phase based binning suggesting more uniform marker segmentation and less motion blur. Images

Auction-Based Resource Allocation for Cooperative Video Transmission Protocols over Wireless Networks

Directory of Open Access Journals (Sweden)

Zhu Han

2009-01-01

Full Text Available Cooperative transmission has been proposed as a novel transmission strategy that takes advantage of broadcast nature of wireless networks, forms virtual MIMO system, and provides diversity gains. In this paper, wireless video transmission protocols are proposed, in which the spectrum resources are first allocated for the source side to broadcast video packets to the relay and destination, and then for the relay side to transmit side information generated from the received packets. The proposed protocols are optimized to minimize the end-to-end expected distortion via choosing bandwidth/power allocation, configuration of side information, subject to bandwidth and power constraints. For multiuser cases, most of current resource allocation approaches cannot be naturally extended and applied to the networks with relay nodes for video transmission. This paper extends the share auction approach into the cooperative video communication scenarios and provides a near-optimal solution for resource allocation. Experimental results have demonstrated that the proposed approach has significant advantage of up to 4 dB gain in single user case and 1.3 dB gain in multiuser case over the reference systems in terms of peak-to-signal-noise ratio. In addition, it reduces the formidable computational complexity of the optimal solution to linear complexity with performance degradation of less than 0.3 dB.

Optimal allocation of sensors for state estimation of distributed parameter systems

International Nuclear Information System (INIS)

Sunahara, Yoshifumi; Ohsumi, Akira; Mogami, Yoshio.

1978-01-01

The purpose of this paper is to present a method for finding the optimal allocation of sensors for state estimation of linear distributed parameter systems. This method is based on the criterion that the error covariance associated with the state estimate becomes minimal with respect to the allocation of the sensors. A theorem is established, giving the sufficient condition for optimizing the allocation of sensors to make minimal the error covariance approximated by a modal expansion. The remainder of this paper is devoted to illustrate important phases of the general theory of the optimal measurement allocation problem. To do this, several examples are demonstrated, including extensive discussions on the mutual relation between the optimal allocation and the dynamics of sensors. (author)

An Ameliorative Whale Optimization Algorithm for Multi-Objective Optimal Allocation of Water Resources in Handan, China

Directory of Open Access Journals (Sweden)

Zhihong Yan

2018-01-01

Full Text Available With the deepening discrepancy between water supply and demand caused by water shortages, alleviating water shortages by optimizing water resource allocation has received extensive attention. How to allocate water resources optimally, rapidly, and effectively has become a challenging problem. Thus, this study employs a meta-heuristic swarm-based algorithm, the whale optimization algorithm (WOA. To overcome drawbacks like relatively low convergence precision and convergence rates, when applying the WOA algorithm to complex optimization problems, logistic mapping is used to initialize swarm location, and inertia weighting is employed to improve the algorithm. The resulting ameliorative whale optimization algorithm (AWOA shows substantially enhanced convergence rates and precision than the WOA and particle swarm optimization algorithms, demonstrating relatively high reliability and applicability. A water resource allocation optimization model with optimal economic efficiency and least total water shortage volume is established for Handan, China, and solved by the AWOA. The allocation results better reflect actual water usage in Handan. In 2030, the p = 50% total water shortage is forecast as 404.34 × 106 m3 or 14.8%. The shortage is mainly in the primary agricultural sector. The allocation results provide a reference for regional water resources management.

Macroeconomic influences on optimal asset allocation

OpenAIRE

Flavin, Thomas; Wickens, M.R.

2003-01-01

We develop a tactical asset allocation strategy that incorporates the effects of macroeconomic variables. The joint distribution of financial asset returns and the macroeconomic variables is modelled using a VAR with a multivariate GARCH (M-GARCH) error structure. As a result, the portfolio frontier is time varying and subject to contagion from the macroeconomic variable. Optimal asset allocation requires that this be taken into account. We illustrate how to do this using three ri...

Optimal design of similariton fiber lasers without gain-bandwidth limitation.

Science.gov (United States)

Li, Xingliang; Zhang, Shumin; Yang, Zhenjun

2017-07-24

We have numerically investigated broadband high-energy similariton fiber lasers, demonstrated that the self-similar evolution of pulses can locate in a segment of photonic crystal fiber without gain-bandwidth limitation. The effects of various parameters, including the cavity length, the spectral filter bandwidth, the pump power, the length of the photonic crystal fiber and the output coupling ratio have also been studied in detail. Using the optimal parameters, a single pulse with spectral width of 186.6 nm, pulse energy of 23.8 nJ, dechirped pulse duration of 22.5 fs and dechirped pulse peak power of 1.26 MW was obtained. We believe that this detailed analysis of the behaviour of pulses in the similariton regime may have major implications in the development of broadband high-energy fiber lasers.

Optimal power allocation for SM-OFDM systems with imperfect channel estimation

International Nuclear Information System (INIS)

Yu, Feng; Song, Lijun; Lei, Xia; Xiao, Yue; Jiang, Zhao Xiang; Jin, Maozhu

2016-01-01

This paper analyses the bit error rate (BER) of the spatial modulation orthogonal frequency division multiplex (SM-OFDM) system and derives the optimal power allocation between the data and the pilot symbols by minimizing the upper bound for the BER operating with imperfect channel estimation. Furthermore, we prove the proposed optimal power allocation scheme applies to all generalized linear interpolation techniques with the minimum mean square error (MMSE) channel estimation . Simulation results show that employing the proposed optimal power allocation provides a substantial gain in terms of the average BER performance for the SM-OFDM system compared to its equal-power-allocation counterpart.

Electricity Portfolio Management: Optimal Peak / Off-Peak Allocations

OpenAIRE

Huisman, Ronald; Mahieu, Ronald; Schlichter, Felix

2007-01-01

textabstractElectricity purchasers manage a portfolio of contracts in order to purchase the expected future electricity consumption profile of a company or a pool of clients. This paper proposes a mean-variance framework to address the concept of structuring the portfolio and focuses on how to allocate optimal positions in peak and off-peak forward contracts. It is shown that the optimal allocations are based on the difference in risk premiums per unit of day-ahead risk as a measure of relati...

The Wireless Craze, The Unlimited Bandwidth Myth, The Spectrum Auction Faux Pas, and the Punchline to Ronald Coase's 'Big Joke': An Essay on Airwave Allocation Policy

OpenAIRE

Hazlett, Thomas W.

2001-01-01

In 1959 the Federal Communications Commission invited economist Ronald Coase to testify about his proposal for market allocation of radio spectrum rights. The FCC's first question: 'Is this all a big joke'' Today, however, leading policy makers, including the current FCC Chair, decry the 'spectrum drought' produced by administrative allocation and call for the creation of private bandwidth markets. This essay examines marketplace trends driving regulators' change of humor, and considers the p...

Optimal Resource Allocation in Library Systems

Science.gov (United States)

Rouse, William B.

1975-01-01

Queueing theory is used to model processes as either waiting or balking processes. The optimal allocation of resources to these processes is defined as that which maximizes the expected value of the decision-maker's utility function. (Author)

Optimization of Power Allocation for Multiusers in Multi-Spot-Beam Satellite Communication Systems

Directory of Open Access Journals (Sweden)

Heng Wang

2014-01-01

Full Text Available In recent years, multi-spot-beam satellite communication systems have played a key role in global seamless communication. However, satellite power resources are scarce and expensive, due to the limitations of satellite platform. Therefore, this paper proposes optimizing the power allocation of each user in order to improve the power utilization efficiency. Initially the capacity allocated to each user is calculated according to the satellite link budget equations, which can be achieved in the practical satellite communication systems. The problem of power allocation is then formulated as a convex optimization, taking account of a trade-off between the maximization of the total system capacity and the fairness of power allocation amongst the users. Finally, an iterative algorithm based on the duality theory is proposed to obtain the optimal solution to the optimization. Compared with the traditional uniform resource allocation or proportional resource allocation algorithms, the proposed optimal power allocation algorithm improves the fairness of power allocation amongst the users. Moreover, the computational complexity of the proposed algorithm is linear with both the numbers of the spot beams and users. As a result, the proposed power allocation algorithm is easy to be implemented in practice.

An Indirect Simulation-Optimization Model for Determining Optimal TMDL Allocation under Uncertainty

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Feng Zhou

2015-11-01

Full Text Available An indirect simulation-optimization model framework with enhanced computational efficiency and risk-based decision-making capability was developed to determine optimal total maximum daily load (TMDL allocation under uncertainty. To convert the traditional direct simulation-optimization model into our indirect equivalent model framework, we proposed a two-step strategy: (1 application of interval regression equations derived by a Bayesian recursive regression tree (BRRT v2 algorithm, which approximates the original hydrodynamic and water-quality simulation models and accurately quantifies the inherent nonlinear relationship between nutrient load reductions and the credible interval of algal biomass with a given confidence interval; and (2 incorporation of the calibrated interval regression equations into an uncertain optimization framework, which is further converted to our indirect equivalent framework by the enhanced-interval linear programming (EILP method and provides approximate-optimal solutions at various risk levels. The proposed strategy was applied to the Swift Creek Reservoir’s nutrient TMDL allocation (Chesterfield County, VA to identify the minimum nutrient load allocations required from eight sub-watersheds to ensure compliance with user-specified chlorophyll criteria. Our results indicated that the BRRT-EILP model could identify critical sub-watersheds faster than the traditional one and requires lower reduction of nutrient loadings compared to traditional stochastic simulation and trial-and-error (TAE approaches. This suggests that our proposed framework performs better in optimal TMDL development compared to the traditional simulation-optimization models and provides extreme and non-extreme tradeoff analysis under uncertainty for risk-based decision making.

A game-theoretical pricing mechanism for multiuser rate allocation for video over WiMAX

Science.gov (United States)

Chen, Chao-An; Lo, Chi-Wen; Lin, Chia-Wen; Chen, Yung-Chang

2010-07-01

In multiuser rate allocation in a wireless network, strategic users can bias the rate allocation by misrepresenting their bandwidth demands to a base station, leading to an unfair allocation. Game-theoretical approaches have been proposed to address the unfair allocation problems caused by the strategic users. However, existing approaches rely on a timeconsuming iterative negotiation process. Besides, they cannot completely prevent unfair allocations caused by inconsistent strategic behaviors. To address these problems, we propose a Search Based Pricing Mechanism to reduce the communication time and to capture a user's strategic behavior. Our simulation results show that the proposed method significantly reduce the communication time as well as converges stably to an optimal allocation.

Optimal kernel shape and bandwidth for atomistic support of continuum stress

International Nuclear Information System (INIS)

Ulz, Manfred H; Moran, Sean J

2013-01-01

The treatment of atomistic scale interactions via molecular dynamics simulations has recently found favour for multiscale modelling within engineering. The estimation of stress at a continuum point on the atomistic scale requires a pre-defined kernel function. This kernel function derives the stress at a continuum point by averaging the contribution from atoms within a region surrounding the continuum point. This averaging volume, and therefore the associated stress at a continuum point, is highly dependent on the bandwidth and shape of the kernel. In this paper we propose an effective and entirely data-driven strategy for simultaneously computing the optimal shape and bandwidth for the kernel. We thoroughly evaluate our proposed approach on copper using three classical elasticity problems. Our evaluation yields three key findings: firstly, our technique can provide a physically meaningful estimation of kernel bandwidth; secondly, we show that a uniform kernel is preferred, thereby justifying the default selection of this kernel shape in future work; and thirdly, we can reliably estimate both of these attributes in a data-driven manner, obtaining values that lead to an accurate estimation of the stress at a continuum point. (paper)

Energy efficiency in elastic-bandwidth optical networks

DEFF Research Database (Denmark)

Vizcaino, Jorge Lopez; Ye, Yabin; Tafur Monroy, Idelfonso

2011-01-01

of elastic bandwidth allocation, opens new horizons in the operation of optical networks. In this paper, we compare the network planning problem in an elastic bandwidth CO-OFDM-based network and a fixed-grid WDM network. We highlight the benefits that bandwidth elasticity and the selection of different......The forecasted growth in the Internet traffic has made the operators and industry to be concerned about the power consumption of the networks, and to become interested in alternatives to plan and operate the networks in a more energy efficient manner. The introduction of OFDM, and its property...

Dynamic Subcarrier Allocation for Real-Time Traffic over Multiuser OFDM Systems

Directory of Open Access Journals (Sweden)

Li VictorOK

2009-01-01

Full Text Available A dynamic resource allocation algorithm to satisfy the packet delay requirements for real-time services, while maximizing the system capacity in multiuser orthogonal frequency division multiplexing (OFDM systems is introduced. Our proposed cross-layer algorithm, called Dynamic Subcarrier Allocation algorithm for Real-time Traffic (DSA-RT, consists of two interactive components. In the medium access control (MAC layer, the users' expected transmission rates in terms of the number of subcarriers per symbol and their corresponding transmission priorities are evaluated. With the above MAC-layer information and the detected subcarriers' channel gains, in the physical (PHY layer, a modified Kuhn-Munkres algorithm is developed to minimize the system power for a certain subcarrier allocation, then a PHY-layer resource allocation scheme is proposed to optimally allocate the subcarriers under the system signal-to-noise ratio (SNR and power constraints. In a system where the number of mobile users changes dynamically, our developed MAC-layer access control and removal schemes can guarantee the quality of service (QoS of the existing users in the system and fully utilize the bandwidth resource. The numerical results show that DSA-RT significantly improves the system performance in terms of the bandwidth efficiency and delay performance for real-time services.

modeling the effect of bandwidth allocation on network performance

African Journals Online (AJOL)

Using MATLAB, simulations were then .... of the network resource. Network bandwidth design, simulation, and management ... encoder processes longer signal data blocks, which entails longer ... c is the modulated signal carrier. However, the ...

Analytical optimization of active bandwidth and quality factor for TOCSY experiments in NMR spectroscopy

Energy Technology Data Exchange (ETDEWEB)

Coote, Paul, E-mail: paul-coote@hms.harvard.edu [Harvard Medical School (United States); Bermel, Wolfgang [Bruker BioSpin GmbH (Germany); Wagner, Gerhard; Arthanari, Haribabu, E-mail: hari@hms.harvard.edu [Harvard Medical School (United States)

2016-09-15

Active bandwidth and global quality factor are the two main metrics used to quantitatively compare the performance of TOCSY mixing sequences. Active bandwidth refers to the spectral region over which at least 50 % of the magnetization is transferred via a coupling. Global quality factor scores mixing sequences according to the worst-case transfer over a range of possible mixing times and chemical shifts. Both metrics reward high transfer efficiency away from the main diagonal of a two-dimensional spectrum. They can therefore be used to design mixing sequences that will function favorably in experiments. Here, we develop optimization methods tailored to these two metrics, including precise control of off-diagonal cross peak buildup rates. These methods produce square shaped transfer efficiency profiles, directly matching the desirable properties that the metrics are intended to measure. The optimization methods are analytical, rather than numerical. The two resultant shaped pulses have significantly higher active bandwidth and quality factor, respectively, than all other known sequences. They are therefore highly suitable for use in NMR spectroscopy. We include experimental verification of these improved waveforms on small molecule and protein samples.

Optimal Allocation of Renewable Energy Sources for Energy Loss Minimization

Directory of Open Access Journals (Sweden)

Vaiju Kalkhambkar

2017-03-01

Full Text Available Optimal allocation of renewable distributed generation (RDG, i.e., solar and the wind in a distribution system becomes challenging due to intermittent generation and uncertainty of loads. This paper proposes an optimal allocation methodology for single and hybrid RDGs for energy loss minimization. The deterministic generation-load model integrated with optimal power flow provides optimal solutions for single and hybrid RDG. Considering the complexity of the proposed nonlinear, constrained optimization problem, it is solved by a robust and high performance meta-heuristic, Symbiotic Organisms Search (SOS algorithm. Results obtained from SOS algorithm offer optimal solutions than Genetic Algorithm (GA, Particle Swarm Optimization (PSO and Firefly Algorithm (FFA. Economic analysis is carried out to quantify the economic benefits of energy loss minimization over the life span of RDGs.

Fuzzy Simulation-Optimization Model for Waste Load Allocation

Directory of Open Access Journals (Sweden)

Motahhare Saadatpour

2006-01-01

Full Text Available This paper present simulation-optimization models for waste load allocation from multiple point sources which include uncertainty due to vagueness of the parameters and goals. This model employs fuzzy sets with appropriate membership functions to deal with uncertainties due to vagueness. The fuzzy waste load allocation model (FWLAM incorporate QUAL2E as a water quality simulation model and Genetic Algorithm (GA as an optimization tool to find the optimal combination of the fraction removal level to the dischargers and pollution control agency (PCA. Penalty functions are employed to control the violations in the system.  The results demonstrate that the goal of PCA to achieve the best water quality and the goal of the dischargers to use the full assimilative capacity of the river have not been satisfied completely and a compromise solution between these goals is provided. This fuzzy optimization model with genetic algorithm has been used for a hypothetical problem. Results demonstrate a very suitable convergence of proposed optimization algorithm to the global optima.

Bandwidth-sharing in LHCONE, an analysis of the problem

Science.gov (United States)

Wildish, T.

2015-12-01

The LHC experiments have traditionally regarded the network as an unreliable resource, one which was expected to be a major source of errors and inefficiency at the time their original computing models were derived. Now, however, the network is seen as much more capable and reliable. Data are routinely transferred with high efficiency and low latency to wherever computing or storage resources are available to use or manage them. Although there was sufficient network bandwidth for the experiments’ needs during Run-1, they cannot rely on ever-increasing bandwidth as a solution to their data-transfer needs in the future. Sooner or later they need to consider the network as a finite resource that they interact with to manage their traffic, in much the same way as they manage their use of disk and CPU resources. There are several possible ways for the experiments to integrate management of the network in their software stacks, such as the use of virtual circuits with hard bandwidth guarantees or soft real-time flow-control, with somewhat less firm guarantees. Abstractly, these can all be considered as the users (the experiments, or groups of users within the experiment) expressing a request for a given bandwidth between two points for a given duration of time. The network fabric then grants some allocation to each user, dependent on the sum of all requests and the sum of available resources, and attempts to ensure the requirements are met (either deterministically or statistically). An unresolved question at this time is how to convert the users’ requests into an allocation. Simply put, how do we decide what fraction of a network's bandwidth to allocate to each user when the sum of requests exceeds the available bandwidth? The usual problems of any resourcescheduling system arise here, namely how to ensure the resource is used efficiently and fairly, while still satisfying the needs of the users. Simply fixing quotas on network paths for each user is likely to lead

Cross-Layer Optimal Rate Allocation for Heterogeneous Wireless Multicast

Directory of Open Access Journals (Sweden)

Amr Mohamed

2009-01-01

Full Text Available Heterogeneous multicast is an efficient communication scheme especially for multimedia applications running over multihop networks. The term heterogeneous refers to the phenomenon when multicast receivers in the same session require service at different rates commensurate with their capabilities. In this paper, we address the problem of resource allocation for a set of heterogeneous multicast sessions over multihop wireless networks. We propose an iterative algorithm that achieves the optimal rates for a set of heterogeneous multicast sessions such that the aggregate utility for all sessions is maximized. We present the formulation of the multicast resource allocation problem as a nonlinear optimization model and highlight the cross-layer framework that can solve this problem in a distributed ad hoc network environment with asynchronous computations. Our simulations show that the algorithm achieves optimal resource utilization, guarantees fairness among multicast sessions, provides flexibility in allocating rates over different parts of the multicast sessions, and adapts to changing conditions such as dynamic channel capacity and node mobility. Our results show that the proposed algorithm not only provides flexibility in allocating resources across multicast sessions, but also increases the aggregate system utility and improves the overall system throughput by almost 30% compared to homogeneous multicast.

Hybrid digital-analog coding with bandwidth expansion for correlated Gaussian sources under Rayleigh fading

Science.gov (United States)

Yahampath, Pradeepa

2017-12-01

Consider communicating a correlated Gaussian source over a Rayleigh fading channel with no knowledge of the channel signal-to-noise ratio (CSNR) at the transmitter. In this case, a digital system cannot be optimal for a range of CSNRs. Analog transmission however is optimal at all CSNRs, if the source and channel are memoryless and bandwidth matched. This paper presents new hybrid digital-analog (HDA) systems for sources with memory and channels with bandwidth expansion, which outperform both digital-only and analog-only systems over a wide range of CSNRs. The digital part is either a predictive quantizer or a transform code, used to achieve a coding gain. Analog part uses linear encoding to transmit the quantization error which improves the performance under CSNR variations. The hybrid encoder is optimized to achieve the minimum AMMSE (average minimum mean square error) over the CSNR distribution. To this end, analytical expressions are derived for the AMMSE of asymptotically optimal systems. It is shown that the outage CSNR of the channel code and the analog-digital power allocation must be jointly optimized to achieve the minimum AMMSE. In the case of HDA predictive quantization, a simple algorithm is presented to solve the optimization problem. Experimental results are presented for both Gauss-Markov sources and speech signals.

Optimal allocation and adaptive VAR control of PV-DG in distribution networks

International Nuclear Information System (INIS)

Fu, Xueqian; Chen, Haoyong; Cai, Runqing; Yang, Ping

2015-01-01

Highlights: • A methodology for optimal PV-DG allocation based on a combination of algorithms. • Dealing with the randomicity of solar power energy using CCSP. • Presenting a VAR control strategy to balance the technical demands. • Finding the Pareto solutions using MOPSO and SVM. • Evaluating the Pareto solutions using WRSR. - Abstract: The development of distributed generation (DG) has brought new challenges to power networks. One of them that catches extensive attention is the voltage regulation problem of distribution networks caused by DG. Optimal allocation of DG in distribution networks is another well-known problem being widely investigated. This paper proposes a new method for the optimal allocation of photovoltaic distributed generation (PV-DG) considering the non-dispatchable characteristics of PV units. An adaptive reactive power control model is introduced in PV-DG allocation as to balance the trade-off between the improvement of voltage quality and the minimization of power loss in a distribution network integrated with PV-DG units. The optimal allocation problem is formulated as a chance-constrained stochastic programming (CCSP) model for dealing with the randomness of solar power energy. A novel algorithm combining the multi-objective particle swarm optimization (MOPSO) with support vector machines (SVM) is proposed to find the Pareto front consisting of a set of possible solutions. The Pareto solutions are further evaluated using the weighted rank sum ratio (WRSR) method to help the decision-maker obtain the desired solution. Simulation results on a 33-bus radial distribution system show that the optimal allocation method can fully take into account the time-variant characteristics and probability distribution of PV-DG, and obtain the best allocation scheme

Optimally Joint Subcarrier Matching and Power Allocation in OFDM Multihop System

Directory of Open Access Journals (Sweden)

Shuyuan Yang

2008-04-01

Full Text Available Orthogonal frequency division multiplexing (OFDM multihop system is a promising way to increase capacity and coverage. In this paper, we propose an optimally joint subcarrier matching and power allocation scheme to further maximize the total channel capacity with the constrained total system power. First, the problem is formulated as a mixed binary integer programming problem, which is prohibitive to find the global optimum in terms of complexity. Second, by making use of the equivalent channel power gain for any matched subcarrier pair, a low complexity scheme is proposed. The optimal subcarrier matching is to match subcarriers by the order of the channel power gains. The optimal power allocation among the matched subcarrier pairs is water-filling. An analytical argument is given to prove that the two steps achieve the optimally joint subcarrier matching and power allocation. The simulation results show that the proposed scheme achieves the largest total channel capacity as compared to the other schemes, where there is no subcarrier matching or no power allocation.

Optimally Joint Subcarrier Matching and Power Allocation in OFDM Multihop System

Directory of Open Access Journals (Sweden)

Wang Wenyi

2008-01-01

Full Text Available Orthogonal frequency division multiplexing (OFDM multihop system is a promising way to increase capacity and coverage. In this paper, we propose an optimally joint subcarrier matching and power allocation scheme to further maximize the total channel capacity with the constrained total system power. First, the problem is formulated as a mixed binary integer programming problem, which is prohibitive to find the global optimum in terms of complexity. Second, by making use of the equivalent channel power gain for any matched subcarrier pair, a low complexity scheme is proposed. The optimal subcarrier matching is to match subcarriers by the order of the channel power gains. The optimal power allocation among the matched subcarrier pairs is water-filling. An analytical argument is given to prove that the two steps achieve the optimally joint subcarrier matching and power allocation. The simulation results show that the proposed scheme achieves the largest total channel capacity as compared to the other schemes, where there is no subcarrier matching or no power allocation.

Optimized Power Allocation and Relay Location Selection in Cooperative Relay Networks

Directory of Open Access Journals (Sweden)

Jianrong Bao

2017-01-01

Full Text Available An incremental selection hybrid decode-amplify forward (ISHDAF scheme for the two-hop single relay systems and a relay selection strategy based on the hybrid decode-amplify-and-forward (HDAF scheme for the multirelay systems are proposed along with an optimized power allocation for the Internet of Thing (IoT. Given total power as the constraint and outage probability as an objective function, the proposed scheme possesses good power efficiency better than the equal power allocation. By the ISHDAF scheme and HDAF relay selection strategy, an optimized power allocation for both the source and relay nodes is obtained, as well as an effective reduction of outage probability. In addition, the optimal relay location for maximizing the gain of the proposed algorithm is also investigated and designed. Simulation results show that, in both single relay and multirelay selection systems, some outage probability gains by the proposed scheme can be obtained. In the comparison of the optimized power allocation scheme with the equal power allocation one, nearly 0.1695 gains are obtained in the ISHDAF single relay network at a total power of 2 dB, and about 0.083 gains are obtained in the HDAF relay selection system with 2 relays at a total power of 2 dB.

Efficient exact optimization of multi-objective redundancy allocation problems in series-parallel systems

International Nuclear Information System (INIS)

Cao, Dingzhou; Murat, Alper; Chinnam, Ratna Babu

2013-01-01

This paper proposes a decomposition-based approach to exactly solve the multi-objective Redundancy Allocation Problem for series-parallel systems. Redundancy allocation problem is a form of reliability optimization and has been the subject of many prior studies. The majority of these earlier studies treat redundancy allocation problem as a single objective problem maximizing the system reliability or minimizing the cost given certain constraints. The few studies that treated redundancy allocation problem as a multi-objective optimization problem relied on meta-heuristic solution approaches. However, meta-heuristic approaches have significant limitations: they do not guarantee that Pareto points are optimal and, more importantly, they may not identify all the Pareto-optimal points. In this paper, we treat redundancy allocation problem as a multi-objective problem, as is typical in practice. We decompose the original problem into several multi-objective sub-problems, efficiently and exactly solve sub-problems, and then systematically combine the solutions. The decomposition-based approach can efficiently generate all the Pareto-optimal solutions for redundancy allocation problems. Experimental results demonstrate the effectiveness and efficiency of the proposed method over meta-heuristic methods on a numerical example taken from the literature.

Modeling the Effect of Bandwidth Allocation on Network Performance

African Journals Online (AJOL)

... The proposed model showed improved performance for CDMA networks, but further increase in the bandwidth did not benefit the network; (iii) A reliability measure such as the spectral efficiency is therefore useful to redeem the limitation in (ii). Keywords: Coverage Capacity, CDMA, Mobile Network, Network Throughput ...

A Theoretical Assessment on Optimal Asset Allocations in Insurance Industry

Directory of Open Access Journals (Sweden)

Bilel Jarraya

2013-10-01

Full Text Available In recent years the financial markets known a rapid development and become more and more complex. So, many regulatory requirements, focused on banks as well as insurance sector, have been developed. These regulatory are concentrated essentially on business risk control and required capital to cover risks. These requirements have influenced the asset allocation issue in insurance industry. These requirements have influenced the asset allocation issue in insurance industry. This section is interested by this issue. In first time it highlights some research works in this issue. Then we will investigate the relation between Solvency and optimal asset allocation. Finally we will explore the principal used methods in modeling asset and in choosing the optimal portfolio composition.

Optimized maritime emergency resource allocation under dynamic demand.

Directory of Open Access Journals (Sweden)

Wenfen Zhang

Full Text Available Emergency resource is important for people evacuation and property rescue when accident occurs. The relief efforts could be promoted by a reasonable emergency resource allocation schedule in advance. As the marine environment is complicated and changeful, the place, type, severity of maritime accident is uncertain and stochastic, bringing about dynamic demand of emergency resource. Considering dynamic demand, how to make a reasonable emergency resource allocation schedule is challenging. The key problem is to determine the optimal stock of emergency resource for supplier centers to improve relief efforts. This paper studies the dynamic demand, and which is defined as a set. Then a maritime emergency resource allocation model with uncertain data is presented. Afterwards, a robust approach is developed and used to make sure that the resource allocation schedule performs well with dynamic demand. Finally, a case study shows that the proposed methodology is feasible in maritime emergency resource allocation. The findings could help emergency manager to schedule the emergency resource allocation more flexibly in terms of dynamic demand.

An Optimization Approach to the Dynamic Allocation of Economic Capital

NARCIS (Netherlands)

Laeven, R.J.A.; Goovaerts, M.J.

2004-01-01

We propose an optimization approach to allocating economic capital, distinguishing between an allocation or raising principle and a measure for the risk residual. The approach is applied both at the aggregate (conglomerate) level and at the individual (subsidiary) level and yields an integrated

Design optimization of the distributed modal filtering rod fiber for increasing single mode bandwidth

DEFF Research Database (Denmark)

Jørgensen, Mette Marie; Petersen, Sidsel Rübner; Laurila, Marko

2012-01-01

. Large preform tolerances are compensated during the fiber draw resulting in ultra low NA fibers with very large cores. In this paper, design optimization of the SM bandwidth of the DMF rod fiber is presented. Analysis of band gap properties results in a fourfold increase of the SM bandwidth compared...... LMA fiber amplifiers having high pump absorption through a pump cladding that is decoupled from the outer fiber. However, achieving ultra low NA for single-mode (SM) guidance is challenging, and thus different design strategies must be applied to filter out higher order modes (HOMs). The novel...... distributed modal filtering (DMF) design presented here enables SM guidance, and previous results have shown a SM mode field diameter of 60 μm operating in a 20 nm SM bandwidth. The DMF rod fiber has high index ring-shaped inclusions acting as resonators enabling SM guidance through modal filtering of HOMs...

Cluster Formation and Joint Power-Bandwidth Allocation for Imperfect NOMA in DL-HetNets

KAUST Repository

Celik, Abdulkadir

2017-04-15

Non-orthogonal multiple access (NOMA) has recently drawn attentions on its ability to fairly serve multiple users on the same radio resource with a desirable performance. However, achievable NOMA gain is primarily limited by channel gain disparity and successive interference cancellation (SIC) receiver characteristics. Accordingly, we introduce an imperfect SIC receiver model considering the power disparity and sensitivity constraints, delay tolerance, and residual interference due to detection and estimation errors. Then, a generic cluster formation (CF) and Power-Bandwidth Allocation (PBA) is formulated as a mixed-integer non-linear programming (MINLP) problem for downlink (DL) heterogeneous networks (HetNets). After dividing the MINLP problem into mixed-integer and non-linear subprobems, we first transform CF into a multi-partite matching, which is solved sequentially using bi-partite matching techniques. For sumrate maximization, max-min fairness, and energy & spectrum efficiency objectives, we secondly put highly non-convex joint PBA into a convex form using geometric programming (GP). Extensive simulations unleash the potential of NOMA to handle large number of users, traffic offloading, and user fairness.

Fair Adaptive Bandwidth and Subchannel Allocation in the WiMAX Uplink

Directory of Open Access Journals (Sweden)

Antoni Morell

2009-01-01

Full Text Available In some modern communication systems, as it is the case of WiMAX, it has been decided to implement Demand Assignment Multiple Access (DAMA solutions. End-users request transmission opportunities before accessing the system, which provides an efficient way to share system resources. In this paper, we briefly review the PHY and MAC layers of an OFDMA-based WiMAX system, and we propose to use a Network Utility Maximization (NUM framework to formulate the DAMA strategy foreseen in the uplink of IEEE 802.16. Utility functions are chosen to achieve fair solutions attaining different degrees of fairness and to further support the QoS requirements of the services in the system. Moreover, since the standard allocates resources in a terminal basis but each terminal may support several services, we develop a new decomposition technique, the coupled-decompositions method, that obtains the optimal service flow allocation with a small number of iterations (the improvement is significant when compared to other known solutions. Furthermore, since the PHY layer in mobile WiMAX has the means to adapt the transport capacities of the links between the Base Station (BS and the Subscriber Stations (SSs, the proposed PHY-MAC cross-layer design uses this extra degree of freedom in order to enhance the network utility.

Combining spatial modeling and choice experiments for the optimal spatial allocation of wind turbines

International Nuclear Information System (INIS)

Drechsler, Martin; Ohl, Cornelia; Meyerhoff, Juergen; Eichhorn, Marcus; Monsees, Jan

2011-01-01

Although wind power is currently the most efficient source of renewable energy, the installation of wind turbines (WT) in landscapes often leads to conflicts in the affected communities. We propose that such conflicts can be mitigated by a welfare-optimal spatial allocation of WT in the landscape so that a given energy target is reached at minimum social costs. The energy target is motivated by the fact that wind power production is associated with relatively low CO 2 emissions. Social costs comprise energy production costs as well as external costs caused by harmful impacts on humans and biodiversity. We present a modeling approach that combines spatially explicit ecological-economic modeling and choice experiments to determine the welfare-optimal spatial allocation of WT in West Saxony, Germany. The welfare-optimal sites balance production and external costs. Results indicate that in the welfare-optimal allocation the external costs represent about 14% of the total costs (production costs plus external costs). Optimizing wind power production without consideration of the external costs would lead to a very different allocation of WT that would marginally reduce the production costs but strongly increase the external costs and thus lead to substantial welfare losses. - Highlights: → We combine modeling and economic valuation to optimally allocate wind turbines. → Welfare-optimal allocation balances energy production costs and external costs. → External costs (impacts on the environment) can be substantial. → Ignoring external costs leads to suboptimal allocations and welfare losses.

Efficient Bandwidth Management for Ethernet Passive Optical Networks

KAUST Repository

Elrasad, Amr Elsayed M.

2016-05-15

The increasing bandwidth demands in access networks motivates network operators, networking devices manufacturers, and standardization institutions to search for new approaches for access networks. These approaches should support higher bandwidth, longer distance between end user and network operator, and less energy consumption. Ethernet Passive Optical Network (EPON) is a favorable choice for broadband access networks. EPONs support transmission rates up to 10 Gbps. EPONs also support distance between end users and central office up to 20 Km. Moreover, optical networks have the least energy consumption among all types of networks. In this dissertation, we focus on reducing delay and saving energy in EPONs. Reducing delay is essential for delay-sensitive traffic, while minimizing energy consumption is an environmental necessity and also reduces the network operating costs. We identify five challenges, namely excess bandwidth allocation, frame delineation, congestion resolution, large round trip time delay in long-reach EPONs (LR-EPONs), and energy saving. We provide a Dynamic Bandwidth Allocation (DBA) approach for each challenge. We also propose a novel scheme that combines the features of the proposed approaches in one highly performing scheme. Our approach is to design novel DBA protocols that can further reduce the delay and be simultaneously simple and fair. We also present a dynamic bandwidth allocation scheme for Green EPONs taking into consideration maximizing energy saving under target delay constraints. Regarding excess bandwidth allocation, we develop an effective DBA scheme called Delayed Excess Scheduling (DES). DES achieves significant delay and jitter reduction and is more suitable for industrial deployment due to its simplicity. Utilizing DES in hybrid TDM/WDM EPONs (TWDM-EPONs) is also investigated. We also study eliminating the wasted bandwidth due to frame delineation. We develop an interactive DBA scheme, Efficient Grant Sizing Interleaved

A Goal Programming Optimization Model for The Allocation of Liquid Steel Production

Science.gov (United States)

Hapsari, S. N.; Rosyidi, C. N.

2018-03-01

This research was conducted in one of the largest steel companies in Indonesia which has several production units and produces a wide range of steel products. One of the important products in the company is billet steel. The company has four Electric Arc Furnace (EAF) which produces liquid steel which must be procesed further to be billet steel. The billet steel plant needs to make their production process more efficient to increase the productvity. The management has four goals to be achieved and hence the optimal allocation of the liquid steel production is needed to achieve those goals. In this paper, a goal programming optimization model is developed to determine optimal allocation of liquid steel production in each EAF, to satisfy demand in 3 periods and the company goals, namely maximizing the volume of production, minimizing the cost of raw materials, minimizing maintenance costs, maximizing sales revenues, and maximizing production capacity. From the results of optimization, only maximizing production capacity goal can not achieve the target. However, the model developed in this papare can optimally allocate liquid steel so the allocation of production does not exceed the maximum capacity of the machine work hours and maximum production capacity.

Spatial dependence in wind and optimal wind power allocation: A copula-based analysis

International Nuclear Information System (INIS)

Grothe, Oliver; Schnieders, Julius

2011-01-01

The investment decision on the placement of wind turbines is, neglecting legal formalities, mainly driven by the aim to maximize the expected annual energy production of single turbines. The result is a concentration of wind farms at locations with high average wind speed. While this strategy may be optimal for single investors maximizing their own return on investment, the resulting overall allocation of wind turbines may be unfavorable for energy suppliers and the economy because of large fluctuations in the overall wind power output. This paper investigates to what extent optimal allocation of wind farms in Germany can reduce these fluctuations. We analyze stochastic dependencies of wind speed for a large data set of German on- and offshore weather stations and find that these dependencies turn out to be highly nonlinear but constant over time. Using copula theory we determine the value at risk of energy production for given allocation sets of wind farms and derive optimal allocation plans. We find that the optimized allocation of wind farms may substantially stabilize the overall wind energy supply on daily as well as hourly frequency. - Highlights: → Spatial modeling of wind forces in Germany. → A novel way to assess nonlinear dependencies of wind forces by copulas. → Wind turbine allocation by maximizing lower quantiles of energy production. → Optimal results show major increase in reliable part of wind energy.

Stochastic Averaging for Constrained Optimization With Application to Online Resource Allocation

Science.gov (United States)

Chen, Tianyi; Mokhtari, Aryan; Wang, Xin; Ribeiro, Alejandro; Giannakis, Georgios B.

2017-06-01

Existing approaches to resource allocation for nowadays stochastic networks are challenged to meet fast convergence and tolerable delay requirements. The present paper leverages online learning advances to facilitate stochastic resource allocation tasks. By recognizing the central role of Lagrange multipliers, the underlying constrained optimization problem is formulated as a machine learning task involving both training and operational modes, with the goal of learning the sought multipliers in a fast and efficient manner. To this end, an order-optimal offline learning approach is developed first for batch training, and it is then generalized to the online setting with a procedure termed learn-and-adapt. The novel resource allocation protocol permeates benefits of stochastic approximation and statistical learning to obtain low-complexity online updates with learning errors close to the statistical accuracy limits, while still preserving adaptation performance, which in the stochastic network optimization context guarantees queue stability. Analysis and simulated tests demonstrate that the proposed data-driven approach improves the delay and convergence performance of existing resource allocation schemes.

Sensitive Constrained Optimal PMU Allocation with Complete Observability for State Estimation Solution

Directory of Open Access Journals (Sweden)

R. Manam

2017-12-01

Full Text Available In this paper, a sensitive constrained integer linear programming approach is formulated for the optimal allocation of Phasor Measurement Units (PMUs in a power system network to obtain state estimation. In this approach, sensitive buses along with zero injection buses (ZIB are considered for optimal allocation of PMUs in the network to generate state estimation solutions. Sensitive buses are evolved from the mean of bus voltages subjected to increase of load consistently up to 50%. Sensitive buses are ranked in order to place PMUs. Sensitive constrained optimal PMU allocation in case of single line and no line contingency are considered in observability analysis to ensure protection and control of power system from abnormal conditions. Modeling of ZIB constraints is included to minimize the number of PMU network allocations. This paper presents optimal allocation of PMU at sensitive buses with zero injection modeling, considering cost criteria and redundancy to increase the accuracy of state estimation solution without losing observability of the whole system. Simulations are carried out on IEEE 14, 30 and 57 bus systems and results obtained are compared with traditional and other state estimation methods available in the literature, to demonstrate the effectiveness of the proposed method.

Optimal allocation of resources for suppressing epidemic spreading on networks

Science.gov (United States)

Chen, Hanshuang; Li, Guofeng; Zhang, Haifeng; Hou, Zhonghuai

2017-07-01

Efficient allocation of limited medical resources is crucial for controlling epidemic spreading on networks. Based on the susceptible-infected-susceptible model, we solve the optimization problem of how best to allocate the limited resources so as to minimize prevalence, providing that the curing rate of each node is positively correlated to its medical resource. By quenched mean-field theory and heterogeneous mean-field (HMF) theory, we prove that an epidemic outbreak will be suppressed to the greatest extent if the curing rate of each node is directly proportional to its degree, under which the effective infection rate λ has a maximal threshold λcopt=1 / , where is the average degree of the underlying network. For a weak infection region (λ ≳λcopt ), we combine perturbation theory with the Lagrange multiplier method (LMM) to derive the analytical expression of optimal allocation of the curing rates and the corresponding minimized prevalence. For a general infection region (λ >λcopt ), the high-dimensional optimization problem is converted into numerically solving low-dimensional nonlinear equations by the HMF theory and LMM. Counterintuitively, in the strong infection region the low-degree nodes should be allocated more medical resources than the high-degree nodes to minimize prevalence. Finally, we use simulated annealing to validate the theoretical results.

Optimal manpower allocation in aircraft line maintenance (Case in GMF AeroAsia)

Science.gov (United States)

Puteri, V. E.; Yuniaristanto, Hisjam, M.

2017-11-01

This paper presents a mathematical modeling to find the optimal manpower allocation in an aircraft line maintenance. This research focuses on assigning the number and type of manpower that allocated to each service. This study considers the licenced worker or Aircraft Maintenance Engineer Licence (AMEL) and non licenced worker or Aircraft Maintenance Technician (AMT). In this paper, we also consider the relationship of each station in terms of the possibility to transfer the manpower among them. The optimization model considers the number of manpowers needed for each service and the requirement of AMEL worker. This paper aims to determine the optimal manpower allocation using the mathematical modeling. The objective function of the model is to find the minimum employee expenses. The model was solved using the ILOG CPLEX software. The results show that the manpower allocation can meet the manpower need and the all load can be served.

Optimal treatment cost allocation methods in pollution control

International Nuclear Information System (INIS)

Chen Wenying; Fang Dong; Xue Dazhi

1999-01-01

Total emission control is an effective pollution control strategy. However, Chinese application of total emission control lacks reasonable and fair methods for optimal treatment cost allocation, a critical issue in total emission control. The author considers four approaches to allocate treatment costs. The first approach is to set up a multiple-objective planning model and to solve the model using the shortest distance ideal point method. The second approach is to define degree of satisfaction for cost allocation results for each polluter and to establish a method based on this concept. The third is to apply bargaining and arbitration theory to develop a model. The fourth is to establish a cooperative N-person game model which can be solved using the Shapley value method, the core method, the Cost Gap Allocation method or the Minimum Costs-Remaining Savings method. These approaches are compared using a practicable case study

Optimal allocation of reviewers for peer feedback

DEFF Research Database (Denmark)

Wind, David Kofoed; Jensen, Ulf Aslak; Jørgensen, Rasmus Malthe

2017-01-01

feedback to be effective students should give and receive useful feedback. A key challenge in peer feedback is allocating the feedback givers in a good way. It is important that reviewers are allocated to submissions such that the feedback distribution is fair - meaning that all students receive good......Peer feedback is the act of letting students give feedback to each other on submitted work. There are multiple reasons to use peer feedback, including students getting more feedback, time saving for teachers and increased learning by letting students reflect on work by others. In order for peer...... indicated the quality of the feedback. Using this model together with historical data we calculate the feedback-giving skill of each student and uses that as input to an allocation algorithm that assigns submissions to reviewers, in order to optimize the feedback quality for all students. We test...

Optimal Bandwidth Selection in Observed-Score Kernel Equating

Science.gov (United States)

Häggström, Jenny; Wiberg, Marie

2014-01-01

The selection of bandwidth in kernel equating is important because it has a direct impact on the equated test scores. The aim of this article is to examine the use of double smoothing when selecting bandwidths in kernel equating and to compare double smoothing with the commonly used penalty method. This comparison was made using both an equivalent…

Optimal Power Allocation Algorithm for Radar Network Systems Based on Low Probability of Intercept Optimization(in English

Directory of Open Access Journals (Sweden)

Shi Chen-guang

2014-08-01

Full Text Available A novel optimal power allocation algorithm for radar network systems is proposed for Low Probability of Intercept (LPI technology in modern electronic warfare. The algorithm is based on the LPI optimization. First, the Schleher intercept factor for a radar network is derived, and then the Schleher intercept factor is minimized by optimizing the transmission power allocation among netted radars in the network to guarantee target-tracking performance. Furthermore, the Nonlinear Programming Genetic Algorithm (NPGA is used to solve the resulting nonconvex, nonlinear, and constrained optimization problem. Numerical simulation results show the effectiveness of the proposed algorithm.

Bandwidth provisioning in infrastructure-based wireless networks employing directional antennas

Energy Technology Data Exchange (ETDEWEB)

Hasiviswanthan, Shiva [Los Alamos National Laboratory; Zhao, Bo [PENN STATE UNIV.; Vasudevan, Sudarshan [UNIV OF MASS AMHERST; Yrgaonkar, Bhuvan [PENN STATE UNIV.

2009-01-01

Motivated by the widespread proliferation of wireless networks employing directional antennas, we study the problem of provisioning bandwidth in such networks. Given a set of subscribers and one or more access points possessing directional antennas, we formalize the problem of orienting these antennas in two fundamental settings: (1) subscriber-centric, where the objective is to fairly allocate bandwidth among the subscribers and (2) provider-centric, where the objective is to maximize the revenue generated by satisfying the bandwidth requirements of subscribers. For both the problems, we first design algorithms for a network with only one access point working under the assumption that the number of antennas does not exceed the number of noninterfering channels. Using the well-regarded lexicographic max-min fair allocation as the objective for a subscriber-centric network, we present an optimum dynamic programming algorithm. For a provider-centric network, the allocation problem turns out to be NP-hard. We present a greedy heuristic based algorithm that guarantees almost half of the optimum revenue. We later enhance both these algorithms to operate in more general networks with multiple access points and no restrictions on the relative numbers of antennas and channels. A simulation-based evaluation using OPNET demonstrates the efficacy of our approaches and provides us further in insights into these problems.

Optimal Energy-Efficient Sensing and Power Allocation in Cognitive Radio Networks

Directory of Open Access Journals (Sweden)

Xia Wu

2014-01-01

Full Text Available We consider a joint optimization of sensing parameter and power allocation for an energy-efficient cognitive radio network (CRN in which the primary user (PU is protected. The optimization problem to maximize the energy efficiency of CRN is formulated as a function of two variables, which are sensing time and transmit power, subject to the average interference power to the PU and the target detection probability. During the optimizing process, the quality of service parameter (the minimum rate acceptable to secondary users (SUs has also been taken into consideration. The optimal solutions are analyzed and an algorithm combined with fractional programming that maximizes the energy efficiency for CRN is presented. Numerical results show that the performance improvement is achieved by the joint optimization of sensing time and power allocation.

An Optimization Algorithm for Multipath Parallel Allocation for Service Resource in the Simulation Task Workflow

Directory of Open Access Journals (Sweden)

Zhiteng Wang

2014-01-01

Full Text Available Service oriented modeling and simulation are hot issues in the field of modeling and simulation, and there is need to call service resources when simulation task workflow is running. How to optimize the service resource allocation to ensure that the task is complete effectively is an important issue in this area. In military modeling and simulation field, it is important to improve the probability of success and timeliness in simulation task workflow. Therefore, this paper proposes an optimization algorithm for multipath service resource parallel allocation, in which multipath service resource parallel allocation model is built and multiple chains coding scheme quantum optimization algorithm is used for optimization and solution. The multiple chains coding scheme quantum optimization algorithm is to extend parallel search space to improve search efficiency. Through the simulation experiment, this paper investigates the effect for the probability of success in simulation task workflow from different optimization algorithm, service allocation strategy, and path number, and the simulation result shows that the optimization algorithm for multipath service resource parallel allocation is an effective method to improve the probability of success and timeliness in simulation task workflow.

Optimal allocation of energy storage in a co-optimized electricity market: Benefits assessment and deriving indicators for economic storage ventures

International Nuclear Information System (INIS)

Krishnan, Venkat; Das, Trishna

2015-01-01

This paper presents a framework for optimally allocating storage technologies in a power system. This decision support tool helps in quantitatively answering the questions on “where to and how much to install” considering the profits from arbitrage opportunities in a co-optimized electricity market. The developed framework is illustrated on a modified IEEE (Institute of Electrical and Electronics Engineers) 24 bus RTS (Reliability Test System), and the framework finds the optimal allocation solution and the revenues storage earns at each of these locations. Bulk energy storage, CAES (compressed air energy storage) is used as the representative storage technology, and the benefits of optimally allocated storage integration onto the grid are compared with transmission expansion solution. The paper also discusses about system-level indicators to identify candidate locations for economical storage ventures, which are derived based on the optimal storage allocation solution; and applies the market price based storage venture indicators on MISO (Mid-continental Independent System Operator) and PJM (Pennsylvania-New Jersey-Maryland Interconnection) electricity markets. - Highlights: • Storage optimal allocation framework based on high-fidelity storage dispatch model. • Storage with transmission addresses energy and ancillary issues under high renewables. • Bulk storage earns higher revenues from co-optimization (∼10× energy only market). • Grid offers distributed opportunities for investing in a strategic mix of storage. • Storage opportunities depend on cross-arbitrage, as seen from MISO (Mid-continental Independent System Operator) and PJM (Pennsylvania-New Jersey-Maryland Interconnection) markets

Two-dimensional priority-based dynamic resource allocation algorithm for QoS in WDM/TDM PON networks

Science.gov (United States)

Sun, Yixin; Liu, Bo; Zhang, Lijia; Xin, Xiangjun; Zhang, Qi; Rao, Lan

2018-01-01

Wavelength division multiplexing/time division multiplexing (WDM/TDM) passive optical networks (PON) is being viewed as a promising solution for delivering multiple services and applications. The hybrid WDM / TDM PON uses the wavelength and bandwidth allocation strategy to control the distribution of the wavelength channels in the uplink direction, so that it can ensure the high bandwidth requirements of multiple Optical Network Units (ONUs) while improving the wavelength resource utilization. Through the investigation of the presented dynamic bandwidth allocation algorithms, these algorithms can't satisfy the requirements of different levels of service very well while adapting to the structural characteristics of mixed WDM / TDM PON system. This paper introduces a novel wavelength and bandwidth allocation algorithm to efficiently utilize the bandwidth and support QoS (Quality of Service) guarantees in WDM/TDM PON. Two priority based polling subcycles are introduced in order to increase system efficiency and improve system performance. The fixed priority polling subcycle and dynamic priority polling subcycle follow different principles to implement wavelength and bandwidth allocation according to the priority of different levels of service. A simulation was conducted to study the performance of the priority based polling in dynamic resource allocation algorithm in WDM/TDM PON. The results show that the performance of delay-sensitive services is greatly improved without degrading QoS guarantees for other services. Compared with the traditional dynamic bandwidth allocation algorithms, this algorithm can meet bandwidth needs of different priority traffic class, achieve low loss rate performance, and ensure real-time of high priority traffic class in terms of overall traffic on the network.

Optimal Scanning Bandwidth Strategy Incorporating Uncertainty about Adversary’s Characteristics

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Andrey Garnaev

2014-12-01

Full Text Available In this paper, we investigate the problem of designing a spectrum scanning strategy to detect an intelligent Invader who wants to utilize spectrum undetected for his/her unapproved purposes. To deal with this problem we model the situation as two games, between a Scanner and an Invader, and solve them sequentially. The first game is formulated to design the optimal (in maxmin sense scanning algorithm, while the second one allows one to find the optimal values of the parameters for the algorithm depending on the parameters of the network. These games provide solutions for two dilemmas that the rivals face. The Invader’s dilemma consists of the following: the more bandwidth the Invader attempts to use leads to a larger payoff if he is not detected, but at the same time also increases the probability of being detected and thus fined. Similarly, the Scanner faces a dilemma: the wider the bandwidth scanned, the higher the probability of detecting the Invader, but at the expense of increasing the cost of building the scanning system. The equilibrium strategies are found explicitly and reveal interesting properties. In particular, we have found a discontinuous dependence of the equilibrium strategies on the network parameters, fine and the type of the Invader’s award. This discontinuity of the fine means that the network provider has to take into account a human/social factor since some threshold values of fine could be very sensible for the Invader, while in other situations simply increasing the fine has a minimal deterrence impact. Also we show how incomplete information about the Invader’s technical characteristics and reward (e.g. motivated by using different type of application, say, video-streaming or downloading files can be incorporated into the scanning strategy to increase its efficiency.

Optimal allocation of leaf epidermal area for gas exchange.

Science.gov (United States)

de Boer, Hugo J; Price, Charles A; Wagner-Cremer, Friederike; Dekker, Stefan C; Franks, Peter J; Veneklaas, Erik J

2016-06-01

A long-standing research focus in phytology has been to understand how plants allocate leaf epidermal space to stomata in order to achieve an economic balance between the plant's carbon needs and water use. Here, we present a quantitative theoretical framework to predict allometric relationships between morphological stomatal traits in relation to leaf gas exchange and the required allocation of epidermal area to stomata. Our theoretical framework was derived from first principles of diffusion and geometry based on the hypothesis that selection for higher anatomical maximum stomatal conductance (gsmax ) involves a trade-off to minimize the fraction of the epidermis that is allocated to stomata. Predicted allometric relationships between stomatal traits were tested with a comprehensive compilation of published and unpublished data on 1057 species from all major clades. In support of our theoretical framework, stomatal traits of this phylogenetically diverse sample reflect spatially optimal allometry that minimizes investment in the allocation of epidermal area when plants evolve towards higher gsmax . Our results specifically highlight that the stomatal morphology of angiosperms evolved along spatially optimal allometric relationships. We propose that the resulting wide range of viable stomatal trait combinations equips angiosperms with developmental and evolutionary flexibility in leaf gas exchange unrivalled by gymnosperms and pteridophytes. © 2016 The Authors New Phytologist © 2016 New Phytologist Trust.

Near-Optimal Resource Allocation in Cooperative Cellular Networks Using Genetic Algorithms

OpenAIRE

Luo, Zihan; Armour, Simon; McGeehan, Joe

2015-01-01

This paper shows how a genetic algorithm can be used as a method of obtaining the near-optimal solution of the resource block scheduling problem in a cooperative cellular network. An exhaustive search is initially implementedto guarantee that the optimal result, in terms of maximizing the bandwidth efficiency of the overall network, is found, and then the genetic algorithm with the properly selected termination conditions is used in the same network. The simulation results show that the genet...

Optimal allocation of trend following strategies

Science.gov (United States)

Grebenkov, Denis S.; Serror, Jeremy

2015-09-01

We consider a portfolio allocation problem for trend following (TF) strategies on multiple correlated assets. Under simplifying assumptions of a Gaussian market and linear TF strategies, we derive analytical formulas for the mean and variance of the portfolio return. We construct then the optimal portfolio that maximizes risk-adjusted return by accounting for inter-asset correlations. The dynamic allocation problem for n assets is shown to be equivalent to the classical static allocation problem for n2 virtual assets that include lead-lag corrections in positions of TF strategies. The respective roles of asset auto-correlations and inter-asset correlations are investigated in depth for the two-asset case and a sector model. In contrast to the principle of diversification suggesting to treat uncorrelated assets, we show that inter-asset correlations allow one to estimate apparent trends more reliably and to adjust the TF positions more efficiently. If properly accounted for, inter-asset correlations are not deteriorative but beneficial for portfolio management that can open new profit opportunities for trend followers. These concepts are illustrated using daily returns of three highly correlated futures markets: the E-mini S&P 500, Euro Stoxx 50 index, and the US 10-year T-note futures.

Attending Globally or Locally: Incidental Learning of Optimal Visual Attention Allocation

Science.gov (United States)

Beck, Melissa R.; Goldstein, Rebecca R.; van Lamsweerde, Amanda E.; Ericson, Justin M.

2018-01-01

Attention allocation determines the information that is encoded into memory. Can participants learn to optimally allocate attention based on what types of information are most likely to change? The current study examined whether participants could incidentally learn that changes to either high spatial frequency (HSF) or low spatial frequency (LSF)…

Optimal Rate Allocation in Cluster-Tree WSNs

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Jose Lopez Vicario

2011-03-01

Full Text Available In this paper, we propose a solution to the problem of guaranteed time slot allocation in cluster-tree WSNs. Our design uses the so-called Network Utility Maximization (NUM approach as far as we aim to provide a fair distribution of the available resources. From the point of view of implementation, we extend here the authors’ proposed Coupled-Decompositions Method (CDM in order to compute the NUM problem inside the cluster tree topology and we prove the optimality of this new extended version of the method. As a result, we obtain a distributed solution that reduces the total amount of signalling information in the network up to a factor of 500 with respect to the classical techniques, that is, primal and dual decomposition. This is possible because the CDM finds the optimal solution with a small number of iterations. Furthermore, when we compare our solution to the standard-proposed First Come First Serve (FCFS policy, we realize that FCFS becomes pretty unfair as the traffic load in the network increases and thus, a fair allocation of resources can be considered whenever the price to pay in terms of signalling and computational complexity is controlled.

Optimization Analysis of Supply Chain Resource Allocation in Customized Online Shopping Service Mode

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Jianming Yao

2015-01-01

Full Text Available For an online-shopping company, whether it can provide its customers with customized service is the key to enhance its customers’ experience value and its own competence. A good customized service requires effective integration and reasonable allocation of the company’s supply chain resources running in the background. Based on the analysis of the allocation of supply chain resources in the customized online shopping service mode and its operational characteristics, this paper puts forward an optimization model for the resource allocation and builds an improved ant algorithm to solve it. Finally, the effectiveness and feasibility of the optimization method and algorithm are demonstrated by a numerical simulation. This paper finds that the special online shopping environments lead to many dynamic and uncertain characters of the service demands. Different customized service patterns and their combination patterns should match with different supply chain resource allocations. The optimization model not only reflects the required service cost and delivery time in the objective function, but also considers the service scale effect optimization and the relations of integration benefits and risks. The improved ant algorithm has obvious advantages in flexibly balancing the multiobjective optimizations, adjusting the convergence speed, and adjusting the operation parameters.

optimization of water resources allocation in semi-arid region

African Journals Online (AJOL)

Eng Obi Ibeje

This study is aimed at achieving optimal water resources allocation .... (2005) points out, in his discussions of non- cooperative games model ... the linear and dynamic programming model which many ... e.g. Institute of Water and Hydropower.

Minimum variance optimal rate allocation for multiplexed H.264/AVC bitstreams.

Science.gov (United States)

Tagliasacchi, Marco; Valenzise, Giuseppe; Tubaro, Stefano

2008-07-01

Consider the problem of transmitting multiple video streams to fulfill a constant bandwidth constraint. The available bit budget needs to be distributed across the sequences in order to meet some optimality criteria. For example, one might want to minimize the average distortion or, alternatively, minimize the distortion variance, in order to keep almost constant quality among the encoded sequences. By working in the rho-domain, we propose a low-delay rate allocation scheme that, at each time instant, provides a closed form solution for either the aforementioned problems. We show that minimizing the distortion variance instead of the average distortion leads, for each of the multiplexed sequences, to a coding penalty less than 0.5 dB, in terms of average PSNR. In addition, our analysis provides an explicit relationship between model parameters and this loss. In order to smooth the distortion also along time, we accommodate a shared encoder buffer to compensate for rate fluctuations. Although the proposed scheme is general, and it can be adopted for any video and image coding standard, we provide experimental evidence by transcoding bitstreams encoded using the state-of-the-art H.264/AVC standard. The results of our simulations reveal that is it possible to achieve distortion smoothing both in time and across the sequences, without sacrificing coding efficiency.

Optimal relay selection and power allocation for cognitive two-way relaying networks

KAUST Repository

Pandarakkottilil, Ubaidulla

2012-06-01

In this paper, we present an optimal scheme for power allocation and relay selection in a cognitive radio network where a pair of cognitive (or secondary) transceiver nodes communicate with each other assisted by a set of cognitive two-way relays. The secondary nodes share the spectrum with a licensed primary user (PU), and each node is assumed to be equipped with a single transmit/receive antenna. The interference to the PU resulting from the transmission from the cognitive nodes is kept below a specified limit. We propose joint relay selection and optimal power allocation among the secondary user (SU) nodes achieving maximum throughput under transmit power and PU interference constraints. A closed-form solution for optimal allocation of transmit power among the SU transceivers and the SU relay is presented. Furthermore, numerical simulations and comparisons are presented to illustrate the performance of the proposed scheme. © 2012 IEEE.

Energy-efficient routing, modulation and spectrum allocation in elastic optical networks

Science.gov (United States)

Tan, Yanxia; Gu, Rentao; Ji, Yuefeng

2017-07-01

With tremendous growth in bandwidth demand, energy consumption problem in elastic optical networks (EONs) becomes a hot topic with wide concern. The sliceable bandwidth-variable transponder in EON, which can transmit/receive multiple optical flows, was recently proposed to improve a transponder's flexibility and save energy. In this paper, energy-efficient routing, modulation and spectrum allocation (EE-RMSA) in EONs with sliceable bandwidth-variable transponder is studied. To decrease the energy consumption, we develop a Mixed Integer Linear Programming (MILP) model with corresponding EE-RMSA algorithm for EONs. The MILP model jointly considers the modulation format and optical grooming in the process of routing and spectrum allocation with the objective of minimizing the energy consumption. With the help of genetic operators, the EE-RMSA algorithm iteratively optimizes the feasible routing path, modulation format and spectrum resources solutions by explore the whole search space. In order to save energy, the optical-layer grooming strategy is designed to transmit the lightpath requests. Finally, simulation results verify that the proposed scheme is able to reduce the energy consumption of the network while maintaining the blocking probability (BP) performance compare with the existing First-Fit-KSP algorithm, Iterative Flipping algorithm and EAMGSP algorithm especially in large network topology. Our results also demonstrate that the proposed EE-RMSA algorithm achieves almost the same performance as MILP on an 8-node network.

Effective Bandwidth Allocation for WiMAX Mesh Network

Directory of Open Access Journals (Sweden)

Hung-Chin Jang

2010-04-01

Full Text Available The aim of this paper is to reduce the media access delay in a WiMAX mesh network. We observe that as the number of subscriber stations (SS in a neighborhood increases, the processes of transmission opportunity (TO competition and 3- way handshake are easy to fail. This may degrade transmission efficiency and increase packet transmission delay. Besides, the minislot allocation defined in the WiMAX mesh mode may cause many lower priority services reserve earlier minislots than that of higher priority services like rtPS. This may cause great negative impact on delay-sensitive traffic. In this paper, we design a QoS classifier to enqueue packets according to different QoS service classes, present a dynamic holdoff exponent mechanism to reduce control subframe delay, and propose a Neighborhood-Based Minislot Allocation (NBMA mechanism to reduce data subframe delay. Simulations show that the proposed methodology outperforms that of IEEE 802.16 and Baye's DynExp in delay, jitter and throughput.

A decentralized multidistrict optimization framework for system-wide pavement maintenance resource allocation

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J. Farhan

2016-05-01

Full Text Available Historically, pavement maintenance funds have been allocated based on a centralized programme development process. Such practice, though seemingly convenient, does not lead to optimal allocation of funds since districts generally have different priorities based on the state of development and condition of their respective road networks. This paper proposes a decentralized two-phased optimization framework for pavement maintenance fund allocation considering multiple objectives and cross-district trade-off at the network level. In the proposed two-phased analysis approach, Phase-I focuses on establishing the needs and funds requirements of individual districts given multiple performance targets or objectives, while a system-wide fund appropriation strategy is selected, in Phase-II, given budget and equity constraints across competing districts. The proposed approach is illustrated using a numerical example problem for appropriating funds to three districts. The results indicated that the proposed approach is not only able to evaluate the extent to which various performance targets are achieved at the central and district level, but also maintains equity in distribution of financial resources across districts. Keywords: Pavement maintenance programming, Multiobjective, Multidistrict, Optimized resource allocation, Genetic algorithm, Dynamic programming

Optimal static allocation decisions in the presence of portfolio insurance

OpenAIRE

Goltz, Felix; Martellini, Lionel; Şimşek, Koray Deniz; Simsek, Koray Deniz

2008-01-01

The focus of this paper is to determine what fraction a myopic risk-averse investor should allocate to investment strategies with convex exposure to stock market returns in a general economy with stochastically time-varying interest rates and equity risk premium. Our conclusion is that typical investors should optimally allocate a sizable fraction of their portfolio to such portfolio insurance strategies, and the associated utility gains are significant. While the fact that static investors w...

An integrated model of water resources optimization allocation based on projection pursuit model - Grey wolf optimization method in a transboundary river basin

Science.gov (United States)

Yu, Sen; Lu, Hongwei

2018-04-01

Under the effects of global change, water crisis ranks as the top global risk in the future decade, and water conflict in transboundary river basins as well as the geostrategic competition led by it is most concerned. This study presents an innovative integrated PPMGWO model of water resources optimization allocation in a transboundary river basin, which is integrated through the projection pursuit model (PPM) and Grey wolf optimization (GWO) method. This study uses the Songhua River basin and 25 control units as examples, adopting the PPMGWO model proposed in this study to allocate the water quantity. Using water consumption in all control units in the Songhua River basin in 2015 as reference to compare with optimization allocation results of firefly algorithm (FA) and Particle Swarm Optimization (PSO) algorithms as well as the PPMGWO model, results indicate that the average difference between corresponding allocation results and reference values are 0.195 bil m3, 0.151 bil m3, and 0.085 bil m3, respectively. Obviously, the average difference of the PPMGWO model is the lowest and its optimization allocation result is closer to reality, which further confirms the reasonability, feasibility, and accuracy of the PPMGWO model. And then the PPMGWO model is adopted to simulate allocation of available water quantity in Songhua River basin in 2018, 2020, and 2030. The simulation results show water quantity which could be allocated in all controls demonstrates an overall increasing trend with reasonable and equal exploitation and utilization of water resources in the Songhua River basin in future. In addition, this study has a certain reference value and application meaning to comprehensive management and water resources allocation in other transboundary river basins.

Balanced Bipartite Graph Based Register Allocation for Network Processors in Mobile and Wireless Networks

Directory of Open Access Journals (Sweden)

Feilong Tang

2010-01-01

Full Text Available Mobile and wireless networks are the integrant infrastructure of mobile and pervasive computing that aims at providing transparent and preferred information and services for people anytime anywhere. In such environments, end-to-end network bandwidth is crucial to improve user's transparent experience when providing on-demand services such as mobile video playing. As a result, powerful computing power is required for networked nodes, especially for routers. General-purpose processors cannot meet such requirements due to their limited processing ability, and poor programmability and scalability. Intel's network processor IXP is specially designed for fast packet processing to achieve a broad bandwidth. IXP provides a large number of registers to reduce the number of memory accesses. Registers in an IXP are physically partitioned as two banks so that two source operands in an instruction have to come from the two banks respectively, which makes the IXP register allocation tricky and different from conventional ones. In this paper, we investigate an approach for efficiently generating balanced bipartite graph and register allocation algorithms for the dual-bank register allocation in IXPs. The paper presents a graph uniform 2-way partition algorithm (FPT, which provides an optimal solution to the graph partition, and a heuristic algorithm for generating balanced bipartite graph. Finally, we design a framework for IXP register allocation. Experimental results demonstrate the framework and the algorithms are efficient in register allocation for IXP network processors.

DYNAMIC OPTIMAL BUDGET ALLOCATION FOR INTEGRATED MARKETING CONSIDERING PERSISTENCE

OpenAIRE

SHIZHONG AI; RONG DU; QIYING HU

2010-01-01

Aiming at forming dynamic optimal integrated marketing policies, we build a budget allocation model considering both current effects and sustained ones. The model includes multiple time periods and multiple marketing tools which interact through a common resource pool as well as through delayed cross influences on each other's sales, reflecting the nature of "integrated marketing" and its dynamics. In our study, marginal analysis is used to illuminate the structure of optimal policy. We deriv...

Optimal water resource allocation modelling in the Lowveld of Zimbabwe

Directory of Open Access Journals (Sweden)

D. Mhiribidi

2018-05-01

Full Text Available The management and allocation of water from multi-reservoir systems is complex and thus requires dynamic modelling systems to achieve optimality. A multi-reservoir system in the Southern Lowveld of Zimbabwe is used for irrigation of sugarcane estates that produce sugar for both local and export consumption. The system is burdened with water allocation problems, made worse by decommissioning of dams. Thus the aim of this research was to develop an operating policy model for the Lowveld multi-reservoir system.The Mann Kendall Trend and Wilcoxon Signed-Rank tests were used to assess the variability of historic monthly rainfall and dam inflows for the period 1899–2015. The WEAP model was set up to evaluate the water allocation system of the catchment and come-up with a reference scenario for the 2015/2016 hydrologic year. Stochastic Dynamic Programming approach was used for optimisation of the multi-reservoirs releases.Results showed no significant trend in the rainfall but a significantly decreasing trend in inflows (p < 0.05. The water allocation model (WEAP showed significant deficits ( ∼  40 % in irrigation water allocation in the reference scenario. The optimal rule curves for all the twelve months for each reservoir were obtained and considered to be a proper guideline for solving multi- reservoir management problems within the catchment. The rule curves are effective tools in guiding decision makers in the release of water without emptying the reservoirs but at the same time satisfying the demands based on the inflow, initial storage and end of month storage.

Artificial intelligent techniques for optimizing water allocation in a reservoir watershed

Science.gov (United States)

Chang, Fi-John; Chang, Li-Chiu; Wang, Yu-Chung

2014-05-01

This study proposes a systematical water allocation scheme that integrates system analysis with artificial intelligence techniques for reservoir operation in consideration of the great uncertainty upon hydrometeorology for mitigating droughts impacts on public and irrigation sectors. The AI techniques mainly include a genetic algorithm and adaptive-network based fuzzy inference system (ANFIS). We first derive evaluation diagrams through systematic interactive evaluations on long-term hydrological data to provide a clear simulation perspective of all possible drought conditions tagged with their corresponding water shortages; then search the optimal reservoir operating histogram using genetic algorithm (GA) based on given demands and hydrological conditions that can be recognized as the optimal base of input-output training patterns for modelling; and finally build a suitable water allocation scheme through constructing an adaptive neuro-fuzzy inference system (ANFIS) model with a learning of the mechanism between designed inputs (water discount rates and hydrological conditions) and outputs (two scenarios: simulated and optimized water deficiency levels). The effectiveness of the proposed approach is tested on the operation of the Shihmen Reservoir in northern Taiwan for the first paddy crop in the study area to assess the water allocation mechanism during drought periods. We demonstrate that the proposed water allocation scheme significantly and substantially avails water managers of reliably determining a suitable discount rate on water supply for both irrigation and public sectors, and thus can reduce the drought risk and the compensation amount induced by making restrictions on agricultural use water.

Optimizing prescribed fire allocation for managing fire risk in central Catalonia.

Science.gov (United States)

Alcasena, Fermín J; Ager, Alan A; Salis, Michele; Day, Michelle A; Vega-Garcia, Cristina

2018-04-15

We used spatial optimization to allocate and prioritize prescribed fire treatments in the fire-prone Bages County, central Catalonia (northeastern Spain). The goal of this study was to identify suitable strategic locations on forest lands for fuel treatments in order to: 1) disrupt major fire movements, 2) reduce ember emissions, and 3) reduce the likelihood of large fires burning into residential communities. We first modeled fire spread, hazard and exposure metrics under historical extreme fire weather conditions, including node influence grid for surface fire pathways, crown fraction burned and fire transmission to residential structures. Then, we performed an optimization analysis on individual planning areas to identify production possibility frontiers for addressing fire exposure and explore alternative prescribed fire treatment configurations. The results revealed strong trade-offs among different fire exposure metrics, showed treatment mosaics that optimize the allocation of prescribed fire, and identified specific opportunities to achieve multiple objectives. Our methods can contribute to improving the efficiency of prescribed fire treatment investments and wildfire management programs aimed at creating fire resilient ecosystems, facilitating safe and efficient fire suppression, and safeguarding rural communities from catastrophic wildfires. The analysis framework can be used to optimally allocate prescribed fire in other fire-prone areas within the Mediterranean region and elsewhere. Copyright © 2017 Elsevier B.V. All rights reserved.

Optimal load allocation of multiple fuel boilers.

Science.gov (United States)

Dunn, Alex C; Du, Yan Yi

2009-04-01

This paper presents a new methodology for optimally allocating a set of multiple industrial boilers that each simultaneously consumes multiple fuel types. Unlike recent similar approaches in the utility industry that use soft computing techniques, this approach is based on a second-order gradient search method that is easy to implement without any specialized optimization software. The algorithm converges rapidly and the application yields significant savings benefits, up to 3% of the overall operating cost of industrial boiler systems in the examples given and potentially higher in other cases, depending on the plant circumstances. Given today's energy prices, this can yield significant savings benefits to manufacturers that raise steam for plant operations.

Winter wheat optimizes allocation in response to carbon limitation

Science.gov (United States)

Huang, Jianbei; Hammerbacher, Almuth; Trumbore, Susan; Hartmann, Henrik

2016-04-01

• Plant photosynthesis is not carbon-saturated at current atmospheric CO2 concentration ([CO2]) thus carbon allocation priority is of critical importance in determining plant response to environmental changes, including increasing [CO2]. • We quantified the percentage of daytime net assimilation (A) allocated to whole-plant nighttime respiration (R) and structural growth (SG), nonstructural carbohydrates (NSC) and secondary metabolites (SMs) during winter wheat (Triticum aestivum) vegetative growth (over 4 weeks) at glacial, ambient, and elevated [CO2] (170, 390 and 680 ppm). • We found that R/A remained relatively constant (11-14%) across [CO2] treatments, whereas plants allocated less C to growth and more C to export at low [CO2] than elevated [CO2]; low [CO2] grown plants tended to invest overall less C into NSC and SMs than to SG due to reduced NSC availability; while leaf SMs/NSC was greater at 170 ppm than at 680 ppm [CO2] this was the opposite for root SMs/NSC; biomass, especially NSC, were preferentially allocated to leaves instead of stems and roots, likely to relieve C limitation induced by low [CO2]. • We conclude that C limitation may force plants to reduce C allocation to long-term survival in order to secure short-term survival. Furthermore, they optimized allocation of the available resource by concentrating biomass and storage to those tissues responsible for assimilation.

Optimizing investment fund allocation using vehicle routing problem framework

Science.gov (United States)

Mamat, Nur Jumaadzan Zaleha; Jaaman, Saiful Hafizah; Ahmad, Rokiah Rozita

2014-07-01

The objective of investment is to maximize total returns or minimize total risks. To determine the optimum order of investment, vehicle routing problem method is used. The method which is widely used in the field of resource distribution shares almost similar characteristics with the problem of investment fund allocation. In this paper we describe and elucidate the concept of using vehicle routing problem framework in optimizing the allocation of investment fund. To better illustrate these similarities, sectorial data from FTSE Bursa Malaysia is used. Results show that different values of utility for risk-averse investors generate the same investment routes.

Optimizing VM allocation and data placement for data-intensive applications in cloud using ACO metaheuristic algorithm

Directory of Open Access Journals (Sweden)

T.P. Shabeera

2017-04-01

Full Text Available Nowadays data-intensive applications for processing big data are being hosted in the cloud. Since the cloud environment provides virtualized resources for computation, and data-intensive applications require communication between the computing nodes, the placement of Virtual Machines (VMs and location of data affect the overall computation time. Majority of the research work reported in the current literature consider the selection of physical nodes for placing data and VMs as independent problems. This paper proposes an approach which considers VM placement and data placement hand in hand. The primary objective is to reduce cross network traffic and bandwidth usage, by placing required number of VMs and data in Physical Machines (PMs which are physically closer. The VM and data placement problem (referred as MinDistVMDataPlacement problem is defined in this paper and has been proved to be NP- Hard. This paper presents and evaluates a metaheuristic algorithm based on Ant Colony Optimization (ACO, which selects a set of adjacent PMs for placing data and VMs. Data is distributed in the physical storage devices of the selected PMs. According to the processing capacity of each PM, a set of VMs are placed on these PMs to process data stored in them. We use simulation to evaluate our algorithm. The results show that the proposed algorithm selects PMs in close proximity and the jobs executed in the VMs allocated by the proposed scheme outperforms other allocation schemes.

An approach involving dynamic group search optimization for allocating resources in OFDM-based cognitive radio system

Directory of Open Access Journals (Sweden)

Sameer Suresh Nanivadekar

2018-03-01

Full Text Available Allocation of channel resources in a cognitive radio system for achieving minimized transmission energy at an increased transmission rate is a challenging research. This paper proposes a resource allocation algorithm based on the meta-heuristic search principle. The proposed algorithm is an improved version of the Group Search Optimizer (GSO, which is a currently developed optimization algorithm that works through imitating the searching behaviour of the animals. The improvement is accomplished through introducing dynamics in the maximum pursuit angle of the GSO members. A cognitive radio system, relying on Orthogonal Frequency Division Multiplexing (OFDM for its operation, is simulated and the experimentations are carried out for sub-channel allocation. The proposed algorithm is experimentally compared with five renowned optimization algorithms, namely, conventional GSO, Particle Swarm Optimization, Genetic Algorithm, Firefly Algorithm and Artificial Bee Colony algorithm. The obtained results assert the competing performance of the proposed algorithm over the other algorithms. Keywords: Cognitive radio, OFDM, Resource, Allocation, Optimization, GSO

Bandwidth allocation for video under quality of service constraints

CERN Document Server

Anjum, Bushra

2014-01-01

We present queueing-based algorithms to calculate the bandwidth required for a video stream so that the three main Quality of Service constraints, i.e., end-to-end delay, jitter and packet loss, are ensured. Conversational and streaming video-based applications are becoming a major part of the everyday Internet usage. The quality of these applications (QoS), as experienced by the user, depends on three main metrics of the underlying network, namely, end-to-end delay, jitter and packet loss. These metrics are, in turn, directly related to the capacity of the links that the video traffic trave

Optimal dynamic water allocation: Irrigation extractions and environmental tradeoffs in the Murray River, Australia

Science.gov (United States)

Grafton, R. Quentin; Chu, Hoang Long; Stewardson, Michael; Kompas, Tom

2011-12-01

A key challenge in managing semiarid basins, such as in the Murray-Darling in Australia, is to balance the trade-offs between the net benefits of allocating water for irrigated agriculture, and other uses, versus the costs of reduced surface flows for the environment. Typically, water planners do not have the tools to optimally and dynamically allocate water among competing uses. We address this problem by developing a general stochastic, dynamic programming model with four state variables (the drought status, the current weather, weather correlation, and current storage) and two controls (environmental release and irrigation allocation) to optimally allocate water between extractions and in situ uses. The model is calibrated to Australia's Murray River that generates: (1) a robust qualitative result that "pulse" or artificial flood events are an optimal way to deliver environmental flows over and above conveyance of base flows; (2) from 2001 to 2009 a water reallocation that would have given less to irrigated agriculture and more to environmental flows would have generated between half a billion and over 3 billion U.S. dollars in overall economic benefits; and (3) water markets increase optimal environmental releases by reducing the losses associated with reduced water diversions.

A genetic algorithm approach to optimization for the radiological worker allocation problem

International Nuclear Information System (INIS)

Yan Chen; Masakuni Narita; Masashi Tsuji; Sangduk Sa

1996-01-01

The worker allocation optimization problem in radiological facilities inevitably involves various types of requirements and constraints relevant to radiological protection and labor management. Some of these goals and constraints are not amenable to a rigorous mathematical formulation. Conventional methods for this problem rely heavily on sophisticated algebraic or numerical algorithms, which cause difficulties in the search for optimal solutions in the search space of worker allocation optimization problems. Genetic algorithms (GAB) are stochastic search algorithms introduced by J. Holland in the 1970s based on ideas and techniques from genetic and evolutionary theories. The most striking characteristic of GAs is the large flexibility allowed in the formulation of the optimal problem and the process of the search for the optimal solution. In the formulation, it is not necessary to define the optimal problem in rigorous mathematical terms, as required in the conventional methods. Furthermore, by designing a model of evolution for the optimal search problem, the optimal solution can be sought efficiently with computational simple manipulations without highly complex mathematical algorithms. We reported a GA approach to the worker allocation problem in radiological facilities in the previous study. In this study, two types of hard constraints were employed to reduce the huge search space, where the optimal solution is sought in such a way as to satisfy as many of soft constraints as possible. It was demonstrated that the proposed evolutionary method could provide the optimal solution efficiently compared with conventional methods. However, although the employed hard constraints could localize the search space into a very small region, it brought some complexities in the designed genetic operators and demanded additional computational burdens. In this paper, we propose a simplified evolutionary model with less restrictive hard constraints and make comparisons between

An improved model for the oPtImal Measurement Probes Allocation tool

International Nuclear Information System (INIS)

Sterle, C.; Neto, A.C.; De Tommasi, G.

2015-01-01

Highlights: • The problem of optimally allocating the probes of a diagnostic system is tackled. • The problem is decomposed in two consecutive optimization problems. • Two original ILP models are proposed and sequentially solved to optimality. • The proposed ILP models improve and extend the previous work present in literature. • Real size instances have been optimally solved with very low computation time. - Abstract: The oPtImal Measurement Probes Allocation (PIMPA) tool has been recently proposed in [1] to maximize the reliability of a tokamak diagnostic system against the failure of one or more of the processing nodes. PIMPA is based on the solution of integer linear programming (ILP) problems, and it minimizes the effect of the failure of a data acquisition component. The first formulation of the PIMPA model did not support the concept of individual slots. This work presents an improved ILP model that addresses the above mentioned problem, by taking into account all the individual probes.

An improved model for the oPtImal Measurement Probes Allocation tool

Energy Technology Data Exchange (ETDEWEB)

Sterle, C., E-mail: claudio.sterle@unina.it [Consorzio CREATE/Dipartimento di Ingegneria Elettrica e delle Tecnologie dell’Informazione, Università degli Studi di Napoli Federico II, Via Claudio 21, 80125 Napoli (Italy); Neto, A.C. [Fusion for Energy, 08019 Barcelona (Spain); De Tommasi, G. [Consorzio CREATE/Dipartimento di Ingegneria Elettrica e delle Tecnologie dell’Informazione, Università degli Studi di Napoli Federico II, Via Claudio 21, 80125 Napoli (Italy)

2015-10-15

Highlights: • The problem of optimally allocating the probes of a diagnostic system is tackled. • The problem is decomposed in two consecutive optimization problems. • Two original ILP models are proposed and sequentially solved to optimality. • The proposed ILP models improve and extend the previous work present in literature. • Real size instances have been optimally solved with very low computation time. - Abstract: The oPtImal Measurement Probes Allocation (PIMPA) tool has been recently proposed in [1] to maximize the reliability of a tokamak diagnostic system against the failure of one or more of the processing nodes. PIMPA is based on the solution of integer linear programming (ILP) problems, and it minimizes the effect of the failure of a data acquisition component. The first formulation of the PIMPA model did not support the concept of individual slots. This work presents an improved ILP model that addresses the above mentioned problem, by taking into account all the individual probes.

Hybrid Optimization-Based Approach for Multiple Intelligent Vehicles Requests Allocation

Directory of Open Access Journals (Sweden)

Ahmed Hussein

2018-01-01

Full Text Available Self-driving cars are attracting significant attention during the last few years, which makes the technology advances jump fast and reach a point of having a number of automated vehicles on the roads. Therefore, the necessity of cooperative driving for these automated vehicles is exponentially increasing. One of the main issues in the cooperative driving world is the Multirobot Task Allocation (MRTA problem. This paper addresses the MRTA problem, specifically for the problem of vehicles and requests allocation. The objective is to introduce a hybrid optimization-based approach to solve the problem of multiple intelligent vehicles requests allocation as an instance of MRTA problem, to find not only a feasible solution, but also an optimized one as per the objective function. Several test scenarios were implemented in order to evaluate the efficiency of the proposed approach. These scenarios are based on well-known benchmarks; thus a comparative study is conducted between the obtained results and the suboptimal results. The analysis of the experimental results shows that the proposed approach was successful in handling various scenarios, especially with the increasing number of vehicles and requests, which displays the proposed approach efficiency and performance.

Stochastic resource allocation in emergency departments with a multi-objective simulation optimization algorithm.

Science.gov (United States)

Feng, Yen-Yi; Wu, I-Chin; Chen, Tzu-Li

2017-03-01

The number of emergency cases or emergency room visits rapidly increases annually, thus leading to an imbalance in supply and demand and to the long-term overcrowding of hospital emergency departments (EDs). However, current solutions to increase medical resources and improve the handling of patient needs are either impractical or infeasible in the Taiwanese environment. Therefore, EDs must optimize resource allocation given limited medical resources to minimize the average length of stay of patients and medical resource waste costs. This study constructs a multi-objective mathematical model for medical resource allocation in EDs in accordance with emergency flow or procedure. The proposed mathematical model is complex and difficult to solve because its performance value is stochastic; furthermore, the model considers both objectives simultaneously. Thus, this study develops a multi-objective simulation optimization algorithm by integrating a non-dominated sorting genetic algorithm II (NSGA II) with multi-objective computing budget allocation (MOCBA) to address the challenges of multi-objective medical resource allocation. NSGA II is used to investigate plausible solutions for medical resource allocation, and MOCBA identifies effective sets of feasible Pareto (non-dominated) medical resource allocation solutions in addition to effectively allocating simulation or computation budgets. The discrete event simulation model of ED flow is inspired by a Taiwan hospital case and is constructed to estimate the expected performance values of each medical allocation solution as obtained through NSGA II. Finally, computational experiments are performed to verify the effectiveness and performance of the integrated NSGA II and MOCBA method, as well as to derive non-dominated medical resource allocation solutions from the algorithms.

Simulation-Based Optimization for Storage Allocation Problem of Outbound Containers in Automated Container Terminals

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Ning Zhao

2015-01-01

Full Text Available Storage allocation of outbound containers is a key factor of the performance of container handling system in automated container terminals. Improper storage plans of outbound containers make QC waiting inevitable; hence, the vessel handling time will be lengthened. A simulation-based optimization method is proposed in this paper for the storage allocation problem of outbound containers in automated container terminals (SAPOBA. A simulation model is built up by Timed-Colored-Petri-Net (TCPN, used to evaluate the QC waiting time of storage plans. Two optimization approaches, based on Particle Swarm Optimization (PSO and Genetic Algorithm (GA, are proposed to form the complete simulation-based optimization method. Effectiveness of this method is verified by experiment, as the comparison of the two optimization approaches.

Probabilistic Bandwidth Assignment in Wireless Sensor Networks

OpenAIRE

Khan , Dawood; Nefzi , Bilel; Santinelli , Luca; Song , Ye-Qiong

2012-01-01

International audience; With this paper we offer an insight in designing and analyzing wireless sensor networks in a versatile manner. Our framework applies probabilistic and component-based design principles for the wireless sensor network modeling and consequently analysis; while maintaining flexibility and accuracy. In particular, we address the problem of allocating and reconfiguring the available bandwidth. The framework has been successfully implemented in IEEE 802.15.4 using an Admissi...

Stereoscopic Visual Attention-Based Regional Bit Allocation Optimization for Multiview Video Coding

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Dai Qionghai

2010-01-01

Full Text Available We propose a Stereoscopic Visual Attention- (SVA- based regional bit allocation optimization for Multiview Video Coding (MVC by the exploiting visual redundancies from human perceptions. We propose a novel SVA model, where multiple perceptual stimuli including depth, motion, intensity, color, and orientation contrast are utilized, to simulate the visual attention mechanisms of human visual system with stereoscopic perception. Then, a semantic region-of-interest (ROI is extracted based on the saliency maps of SVA. Both objective and subjective evaluations of extracted ROIs indicated that the proposed SVA model based on ROI extraction scheme outperforms the schemes only using spatial or/and temporal visual attention clues. Finally, by using the extracted SVA-based ROIs, a regional bit allocation optimization scheme is presented to allocate more bits on SVA-based ROIs for high image quality and fewer bits on background regions for efficient compression purpose. Experimental results on MVC show that the proposed regional bit allocation algorithm can achieve over % bit-rate saving while maintaining the subjective image quality. Meanwhile, the image quality of ROIs is improved by  dB at the cost of insensitive image quality degradation of the background image.

Distributed Channel Allocation and Time Slot Optimization for Green Internet of Things

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Kaiqi Ding

2017-10-01

Full Text Available In sustainable smart cities, power saving is a severe challenge in the energy-constrained Internet of Things (IoT. Efficient utilization of limited multiple non-overlap channels and time resources is a promising solution to reduce the network interference and save energy consumption. In this paper, we propose a joint channel allocation and time slot optimization solution for IoT. First, we propose a channel ranking algorithm which enables each node to rank its available channels based on the channel properties. Then, we propose a distributed channel allocation algorithm so that each node can choose a proper channel based on the channel ranking and its own residual energy. Finally, the sleeping duration and spectrum sensing duration are jointly optimized to maximize the normalized throughput and satisfy energy consumption constraints simultaneously. Different from the former approaches, our proposed solution requires no central coordination or any global information that each node can operate based on its own local information in a total distributed manner. Also, theoretical analysis and extensive simulations have validated that when applying our solution in the network of IoT: (i each node can be allocated to a proper channel based on the residual energy to balance the lifetime; (ii the network can rapidly converge to a collision-free transmission through each node’s learning ability in the process of the distributed channel allocation; and (iii the network throughput is further improved via the dynamic time slot optimization.

Distributed Channel Allocation and Time Slot Optimization for Green Internet of Things.

Science.gov (United States)

Ding, Kaiqi; Zhao, Haitao; Hu, Xiping; Wei, Jibo

2017-10-28

In sustainable smart cities, power saving is a severe challenge in the energy-constrained Internet of Things (IoT). Efficient utilization of limited multiple non-overlap channels and time resources is a promising solution to reduce the network interference and save energy consumption. In this paper, we propose a joint channel allocation and time slot optimization solution for IoT. First, we propose a channel ranking algorithm which enables each node to rank its available channels based on the channel properties. Then, we propose a distributed channel allocation algorithm so that each node can choose a proper channel based on the channel ranking and its own residual energy. Finally, the sleeping duration and spectrum sensing duration are jointly optimized to maximize the normalized throughput and satisfy energy consumption constraints simultaneously. Different from the former approaches, our proposed solution requires no central coordination or any global information that each node can operate based on its own local information in a total distributed manner. Also, theoretical analysis and extensive simulations have validated that when applying our solution in the network of IoT: (i) each node can be allocated to a proper channel based on the residual energy to balance the lifetime; (ii) the network can rapidly converge to a collision-free transmission through each node's learning ability in the process of the distributed channel allocation; and (iii) the network throughput is further improved via the dynamic time slot optimization.

Optimal and Fair Resource Allocation for Multiuser Wireless Multimedia Transmissions

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Zhangyu Guan

2009-01-01

Full Text Available This paper presents an optimal and fair strategy for multiuser multimedia radio resource allocation (RRA based on coopetition, which suggests a judicious mixture of competition and cooperation. We formulate the co-opetition strategy as sum utility maximization at constraints from both Physical (PHY and Application (APP layers. We show that the maximization can be solved efficiently employing the well-defined Layering as Optimization Decomposition (LOD method. Moreover, the coopetition strategy is applied to power allocation among multiple video users, and evaluated through comparing with existing- competition based strategy. Numerical results indicate that, the co-opetition strategy adapts the best to the changes of network conditions, participating users, and so forth. It is also shown that the coopetition can lead to an improved number of satisfied users, and in the meanwhile provide more flexible tradeoff between system efficiency and fairness among users.

An Optimal Online Resource Allocation Algorithm for Energy Harvesting Body Area Networks

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Guangyuan Wu

2018-01-01

Full Text Available In Body Area Networks (BANs, how to achieve energy management to extend the lifetime of the body area networks system is one of the most critical problems. In this paper, we design a body area network system powered by renewable energy, in which the sensors carried by patient with energy harvesting module can transmit data to a personal device. We do not require any a priori knowledge of the stochastic nature of energy harvesting and energy consumption. We formulate a user utility optimization problem. We use Lyapunov Optimization techniques to decompose the problem into three sub-problems, i.e., battery management, collecting rate control and transmission power allocation. We propose an online resource allocation algorithm to achieve two major goals: (1 balancing sensors’ energy harvesting and energy consumption while stabilizing the BANs system; and (2 maximizing the user utility. Performance analysis addresses required battery capacity, bounded data queue length and optimality of the proposed algorithm. Simulation results verify the optimization of algorithm.

Resource allocation in IT projects: using schedule optimization

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Michael Chilton

2014-01-01

Full Text Available Resource allocation is the process of assigning resources to tasks throughout the life of a project. Despite sophisticated software packages devoted to keeping track of tasks, resources and resource assignments, it is often the case that project managers find some resources over-allocated and therefore unable to complete the assigned work in the allotted amount of time. Most scheduling software has provisions for leveling resources, but the techniques for doing so simply add time to the schedule and may cause delays in tasks that are critical to the project in meeting deadlines. This paper presents a software application that ensures that resources are properly balanced at the beginning of the project and eliminates the situation in which resources become over-allocated. It can be used in a multi-project environment and reused throughout the project as tasks, resource assignments and availability, and the project scope change. The application utilizes the bounded enumeration technique to formulate an optimal schedule for which both the task sequence and resource availability are taken into account. It is run on a database server to reduce the running time and make it a viable application for practitioners.

A Thrust Allocation Method for Efficient Dynamic Positioning of a Semisubmersible Drilling Rig Based on the Hybrid Optimization Algorithm

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Luman Zhao

2015-01-01

Full Text Available A thrust allocation method was proposed based on a hybrid optimization algorithm to efficiently and dynamically position a semisubmersible drilling rig. That is, the thrust allocation was optimized to produce the generalized forces and moment required while at the same time minimizing the total power consumption under the premise that forbidden zones should be taken into account. An optimization problem was mathematically formulated to provide the optimal thrust allocation by introducing the corresponding design variables, objective function, and constraints. A hybrid optimization algorithm consisting of a genetic algorithm and a sequential quadratic programming (SQP algorithm was selected and used to solve this problem. The proposed method was evaluated by applying it to a thrust allocation problem for a semisubmersible drilling rig. The results indicate that the proposed method can be used as part of a cost-effective strategy for thrust allocation of the rig.

Near-optimal power allocation with PSO algorithm for MIMO cognitive networks using multiple AF two-way relays

KAUST Repository

Alsharoa, Ahmad M.

2014-06-01

In this paper, the problem of power allocation for a multiple-input multiple-output two-way system is investigated in underlay Cognitive Radio (CR) set-up. In the CR underlay mode, secondary users are allowed to exploit the spectrum allocated to primary users in an opportunistic manner by respecting a tolerated temperature limit. The secondary networks employ an amplify-and-forward two-way relaying technique in order to maximize the sum rate under power budget and interference constraints. In this context, we formulate an optimization problem that is solved in two steps. First, we derive a closed-form expression of the optimal power allocated to terminals. Then, we employ a strong optimization tool based on particle swarm optimization algorithm to find the power allocated to secondary relays. Simulation results demonstrate the efficiency of the proposed solution and analyze the impact of some system parameters on the achieved performance. © 2014 IEEE.

Optimal allocation of multi-state retransmitters in acyclic transmission networks

International Nuclear Information System (INIS)

Levitin, Gregory

2002-01-01

In this paper, an algorithm for optimal allocation of multi-state elements (MEs) in acyclic transmission networks (ATNs) is suggested. The ATNs consist of a number of positions (nodes) in which MEs capable of receiving and sending a signal are allocated. Each network has a root position where the signal source is located, a number of leaf positions that can only receive a signal, and a number of intermediate positions containing MEs capable of transmitting the received signal to some other nodes. Each ME that is located in a nonleaf node can have different states determined by a set of nodes receiving the signal directly from this ME. The probability of each state is assumed to be known for each ME. The ATN reliability is defined as the probability that a signal from the root node is transmitted to each leaf node. The optimal distribution of MEs with different characteristics among ATN positions provides the greatest possible ATN reliability. The suggested algorithm is based on using a universal generating function technique for network reliability evaluation. A genetic algorithm is used as the optimization tool. Illustrative examples are presented

Optimal allocation of industrial PV-storage micro-grid considering important load

Science.gov (United States)

He, Shaohua; Ju, Rong; Yang, Yang; Xu, Shuai; Liang, Lei

2018-03-01

At present, the industrial PV-storage micro-grid has been widely used. This paper presents an optimal allocation model of PV-storage micro-grid capacity considering the important load of industrial users. A multi-objective optimization model is established to promote the local extinction of PV power generation and the maximum investment income of the enterprise as the objective function. Particle swarm optimization (PSO) is used to solve the case of a city in Jiangsu Province, the results are analyzed economically.

Multi-objective reliability redundancy allocation in an interval environment using particle swarm optimization

International Nuclear Information System (INIS)

Zhang, Enze; Chen, Qingwei

2016-01-01

Most of the existing works addressing reliability redundancy allocation problems are based on the assumption of fixed reliabilities of components. In real-life situations, however, the reliabilities of individual components may be imprecise, most often given as intervals, under different operating or environmental conditions. This paper deals with reliability redundancy allocation problems modeled in an interval environment. An interval multi-objective optimization problem is formulated from the original crisp one, where system reliability and cost are simultaneously considered. To render the multi-objective particle swarm optimization (MOPSO) algorithm capable of dealing with interval multi-objective optimization problems, a dominance relation for interval-valued functions is defined with the help of our newly proposed order relations of interval-valued numbers. Then, the crowding distance is extended to the multi-objective interval-valued case. Finally, the effectiveness of the proposed approach has been demonstrated through two numerical examples and a case study of supervisory control and data acquisition (SCADA) system in water resource management. - Highlights: • We model the reliability redundancy allocation problem in an interval environment. • We apply the particle swarm optimization directly on the interval values. • A dominance relation for interval-valued multi-objective functions is defined. • The crowding distance metric is extended to handle imprecise objective functions.

Optimizing MPBSM Resource Allocation Based on Revenue Management: A China Mobile Sichuan Case

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Xu Chen

2015-01-01

Full Text Available The key to determining the network service level of telecom operators is resource allocation for mobile phone base station maintenance (MPBSM. Given intense market competition and higher consumer requirements for network service levels, an increasing proportion of resources have been allocated to MPBSM. Maintenance costs account for the rising fraction of direct costs, and the management of MPBSM resource allocation presents special challenges to telecom operators. China Mobile is the largest telecom operator in the world. Its subsidiary, China Mobile Sichuan, is the first in China to use revenue management in improving MPBSM resource allocation. On the basis of comprehensive revenue (including both economic revenue and social revenue, the subsidiary established a classification model of its base stations. The model scientifically classifies more than 25,000 base stations according to comprehensive revenue. China Mobile Sichuan also conducted differentiation allocation of MPBSM resources on the basis of the classification results. Furthermore, it optimized the assessment system of the telecom base stations to establish an assurance system for the use of MPBSM resources. After half-year implementation, the cell availability of both VIP base stations and total base stations significantly improved. The optimization also reduced economic losses to RMB 10.134 million, and enhanced customer satisfaction with network service by 3.2%.

Dynamic Optimization for IPS2 Resource Allocation Based on Improved Fuzzy Multiple Linear Regression

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Maokuan Zheng

2017-01-01

Full Text Available The study mainly focuses on resource allocation optimization for industrial product-service systems (IPS2. The development of IPS2 leads to sustainable economy by introducing cooperative mechanisms apart from commodity transaction. The randomness and fluctuation of service requests from customers lead to the volatility of IPS2 resource utilization ratio. Three basic rules for resource allocation optimization are put forward to improve system operation efficiency and cut unnecessary costs. An approach based on fuzzy multiple linear regression (FMLR is developed, which integrates the strength and concision of multiple linear regression in data fitting and factor analysis and the merit of fuzzy theory in dealing with uncertain or vague problems, which helps reduce those costs caused by unnecessary resource transfer. The iteration mechanism is introduced in the FMLR algorithm to improve forecasting accuracy. A case study of human resource allocation optimization in construction machinery industry is implemented to test and verify the proposed model.

Manajemen Bandwidth Simple Queue dan Queue Tree pada PT. Endorsindo Makmur Selaras

OpenAIRE

Budiman, Arif

2015-01-01

  The purpose of this study is to analyze and optimize the bandwidth management at PT. Endorsindo Makmur Selaras, with the expectation that the distribution of bandwidth can be evenly distributed to each employee so that the employee can improve performance and quality of the company. Research methods used include analysis methods (survey and interview system that runs directly on the user) and to optimize bandwidth management method to configure the proxy using the Queue Tree. The re...

Optimal resource allocation solutions for heterogeneous cognitive radio networks

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Babatunde Awoyemi

2017-05-01

Full Text Available Cognitive radio networks (CRN are currently gaining immense recognition as the most-likely next-generation wireless communication paradigm, because of their enticing promise of mitigating the spectrum scarcity and/or underutilisation challenge. Indisputably, for this promise to ever materialise, CRN must of necessity devise appropriate mechanisms to judiciously allocate their rather scarce or limited resources (spectrum and others among their numerous users. ‘Resource allocation (RA in CRN', which essentially describes mechanisms that can effectively and optimally carry out such allocation, so as to achieve the utmost for the network, has therefore recently become an important research focus. However, in most research works on RA in CRN, a highly significant factor that describes a more realistic and practical consideration of CRN has been ignored (or only partially explored, i.e., the aspect of the heterogeneity of CRN. To address this important aspect, in this paper, RA models that incorporate the most essential concepts of heterogeneity, as applicable to CRN, are developed and the imports of such inclusion in the overall networking are investigated. Furthermore, to fully explore the relevance and implications of the various heterogeneous classifications to the RA formulations, weights are attached to the different classes and their effects on the network performance are studied. In solving the developed complex RA problems for heterogeneous CRN, a solution approach that examines and exploits the structure of the problem in achieving a less-complex reformulation, is extensively employed. This approach, as the results presented show, makes it possible to obtain optimal solutions to the rather difficult RA problems of heterogeneous CRN.

Bandwidth Optimization On Design Of Visual Display Information System Based Networking At Politeknik Negeri Bali

Science.gov (United States)

Sudiartha, IKG; Catur Bawa, IGNB

2018-01-01

Information can not be separated from the social life of the community, especially in the world of education. One of the information fields is academic calendar information, activity agenda, announcement and campus activity news. In line with technological developments, text-based information is becoming obsolete. For that need creativity to present information more quickly, accurately and interesting by exploiting the development of digital technology and internet. In this paper will be developed applications for the provision of information in the form of visual display, applied to computer network system with multimedia applications. Network-based applications provide ease in updating data through internet services, attractive presentations with multimedia support. The application “Networking Visual Display Information Unit” can be used as a medium that provides information services for students and academic employee more interesting and ease in updating information than the bulletin board. The information presented in the form of Running Text, Latest Information, Agenda, Academic Calendar and Video provide an interesting presentation and in line with technological developments at the Politeknik Negeri Bali. Through this research is expected to create software “Networking Visual Display Information Unit” with optimal bandwidth usage by combining local data sources and data through the network. This research produces visual display design with optimal bandwidth usage and application in the form of supporting software.

Models of resource allocation optimization when solving the control problems in organizational systems

Science.gov (United States)

Menshikh, V.; Samorokovskiy, A.; Avsentev, O.

2018-03-01

The mathematical model of optimizing the allocation of resources to reduce the time for management decisions and algorithms to solve the general problem of resource allocation. The optimization problem of choice of resources in organizational systems in order to reduce the total execution time of a job is solved. This problem is a complex three-level combinatorial problem, for the solving of which it is necessary to implement the solution to several specific problems: to estimate the duration of performing each action, depending on the number of performers within the group that performs this action; to estimate the total execution time of all actions depending on the quantitative composition of groups of performers; to find such a distribution of the existing resource of performers in groups to minimize the total execution time of all actions. In addition, algorithms to solve the general problem of resource allocation are proposed.

Optimal Allocation of Wind Turbines by Considering Transmission Security Constraints and Power System Stability

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Rodrigo Palma-Behnke

2013-01-01

Full Text Available A novel optimization methodology consisting of finding the near optimal location of wind turbines (WTs on a planned transmission network in a secure and cost-effective way is presented on this paper. While minimizing the investment costs of WTs, the algorithm allocates the turbines so that a desired wind power energy-penetration level is reached. The optimization considers both transmission security and power system stability constraints. The results of the optimization provide regulators with a support instrument to give proper signals to WT investors, in order to achieve secure and cost effective wind power network integration. The proposal is especially aimed at countries in the initial stage of wind power development, where the WT network integration process can still be influenced by policy-makers. The proposed methodology is validated with a real power system. Obtained results are compared with those generated from a business-as-usual (BAU scenario, in which the WT network allocation is made according to existing WT projects. The proposed WT network allocation scheme not only reduces the total investment costs associated with a determined wind power energy target, but also improves power system stability.

Optimizing Irrigation Water Allocation under Multiple Sources of Uncertainty in an Arid River Basin

Science.gov (United States)

Wei, Y.; Tang, D.; Gao, H.; Ding, Y.

2015-12-01

Population growth and climate change add additional pressures affecting water resources management strategies for meeting demands from different economic sectors. It is especially challenging in arid regions where fresh water is limited. For instance, in the Tailanhe River Basin (Xinjiang, China), a compromise must be made between water suppliers and users during drought years. This study presents a multi-objective irrigation water allocation model to cope with water scarcity in arid river basins. To deal with the uncertainties from multiple sources in the water allocation system (e.g., variations of available water amount, crop yield, crop prices, and water price), the model employs a interval linear programming approach. The multi-objective optimization model developed from this study is characterized by integrating eco-system service theory into water-saving measures. For evaluation purposes, the model is used to construct an optimal allocation system for irrigation areas fed by the Tailan River (Xinjiang Province, China). The objective functions to be optimized are formulated based on these irrigation areas' economic, social, and ecological benefits. The optimal irrigation water allocation plans are made under different hydroclimate conditions (wet year, normal year, and dry year), with multiple sources of uncertainty represented. The modeling tool and results are valuable for advising decision making by the local water authority—and the agricultural community—especially on measures for coping with water scarcity (by incorporating uncertain factors associated with crop production planning).

The optimal amount and allocation of of sampling effort for plant health inspection

NARCIS (Netherlands)

Surkov, I.; Oude Lansink, A.G.J.M.; Werf, van der W.

2009-01-01

Plant import inspection can prevent the introduction of exotic pests and diseases, thereby averting economic losses. We explore the optimal allocation of a fixed budget, taking into account risk differentials, and the optimal-sized budget to minimise total pest costs. A partial-equilibrium market

Optimal Allocation of Water Resources Based on Water Supply Security

Directory of Open Access Journals (Sweden)

Jianhua Wang

2016-06-01

Full Text Available Under the combined impacts of climate change and human activities, a series of water issues, such as water shortages, have arisen all over the world. According to current studies in Science and Nature, water security has become a frontier critical topic. Water supply security (WSS, which is the state of water resources and their capacity and their capacity to meet the demand of water users by water supply systems, is an important part of water security. Currently, WSS is affected by the amount of water resources, water supply projects, water quality and water management. Water shortages have also led to water supply insecurity. WSS is now evaluated based on the balance of the supply and demand under a single water resources condition without considering the dynamics of the varying conditions of water resources each year. This paper developed an optimal allocation model for water resources that can realize the optimal allocation of regional water resources and comprehensively evaluate WSS. The objective of this model is to minimize the duration of water shortages in the long term, as characterized by the Water Supply Security Index (WSSI, which is the assessment value of WSS, a larger WSSI value indicates better results. In addition, the simulation results of the model can determine the change process and dynamic evolution of the WSS. Quanzhou, a city in China with serious water shortage problems, was selected as a case study. The allocation results of the current year and target year of planning demonstrated that the level of regional comprehensive WSS was significantly influenced by the capacity of water supply projects and the conditions of the natural water resources. The varying conditions of the water resources allocation results in the same year demonstrated that the allocation results and WSSI were significantly affected by reductions in precipitation, decreases in the water yield coefficient, and changes in the underlying surface.

The Ordered Capacitated Multi-Objective Location-Allocation Problem for Fire Stations Using Spatial Optimization

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Samira Bolouri

2018-01-01

Full Text Available Determining the positions of facilities, and allocating demands to them, is a vitally important problem. Location-allocation problems are optimization NP-hard procedures. This article evaluates the ordered capacitated multi-objective location-allocation problem for fire stations, using simulated annealing and a genetic algorithm, with goals such as minimizing the distance and time as well as maximizing the coverage. After tuning the parameters of the algorithms using sensitivity analysis, they were used separately to process data for Region 11, Tehran. The results showed that the genetic algorithm was more efficient than simulated annealing, and therefore, the genetic algorithm was used in later steps. Next, we increased the number of stations. Results showed that the model can successfully provide seven optimal locations and allocate high demands (280,000 to stations in a discrete space in a GIS, assuming that the stations’ capacities are known. Following this, we used a weighting program so that in each repetition, we could allot weights to each target randomly. Finally, by repeating the model over 10 independent executions, a set of solutions with the least sum and the highest number of non-dominated solutions was selected from among many non-dominated solutions as the best set of optimal solutions.

Optimal allocation of testing resources for statistical simulations

Science.gov (United States)

Quintana, Carolina; Millwater, Harry R.; Singh, Gulshan; Golden, Patrick

2015-07-01

Statistical estimates from simulation involve uncertainty caused by the variability in the input random variables due to limited data. Allocating resources to obtain more experimental data of the input variables to better characterize their probability distributions can reduce the variance of statistical estimates. The methodology proposed determines the optimal number of additional experiments required to minimize the variance of the output moments given single or multiple constraints. The method uses multivariate t-distribution and Wishart distribution to generate realizations of the population mean and covariance of the input variables, respectively, given an amount of available data. This method handles independent and correlated random variables. A particle swarm method is used for the optimization. The optimal number of additional experiments per variable depends on the number and variance of the initial data, the influence of the variable in the output function and the cost of each additional experiment. The methodology is demonstrated using a fretting fatigue example.

A Grooming Nodes Optimal Allocation Method for Multicast in WDM Networks

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Chengying Wei

2016-01-01

Full Text Available The grooming node has the capability of grooming multicast traffic with the small granularity into established light at high cost of complexity and node architecture. In the paper, a grooming nodes optimal allocation (GNOA method is proposed to optimize the allocation of the grooming nodes constraint by the blocking probability for multicast traffic in sparse WDM networks. In the proposed GNOA method, the location of each grooming node is determined by the SCLD strategy. The improved smallest cost largest degree (SCLD strategy is designed to select the nongrooming nodes in the proposed GNOA method. The simulation results show that the proposed GNOA method can reduce the required number of grooming nodes and decrease the cost of constructing a network to guarantee a certain request blocking probability when the wavelengths per fiber and transmitter/receiver ports per node are sufficient for the optical multicast in WDM networks.

Interactive Land-Use Optimization Using Laguerre Voronoi Diagram with Dynamic Generating Point Allocation

Science.gov (United States)

Chaidee, S.; Pakawanwong, P.; Suppakitpaisarn, V.; Teerasawat, P.

2017-09-01

In this work, we devise an efficient method for the land-use optimization problem based on Laguerre Voronoi diagram. Previous Voronoi diagram-based methods are more efficient and more suitable for interactive design than discrete optimization-based method, but, in many cases, their outputs do not satisfy area constraints. To cope with the problem, we propose a force-directed graph drawing algorithm, which automatically allocates generating points of Voronoi diagram to appropriate positions. Then, we construct a Laguerre Voronoi diagram based on these generating points, use linear programs to adjust each cell, and reconstruct the diagram based on the adjustment. We adopt the proposed method to the practical case study of Chiang Mai University's allocated land for a mixed-use complex. For this case study, compared to other Voronoi diagram-based method, we decrease the land allocation error by 62.557 %. Although our computation time is larger than the previous Voronoi-diagram-based method, it is still suitable for interactive design.

Data analysis-based autonomic bandwidth adjustment in software defined multi-vendor optical transport networks.

Science.gov (United States)

Li, Yajie; Zhao, Yongli; Zhang, Jie; Yu, Xiaosong; Jing, Ruiquan

2017-11-27

Network operators generally provide dedicated lightpaths for customers to meet the demand for high-quality transmission. Considering the variation of traffic load, customers usually rent peak bandwidth that exceeds the practical average traffic requirement. In this case, bandwidth provisioning is unmetered and customers have to pay according to peak bandwidth. Supposing that network operators could keep track of traffic load and allocate bandwidth dynamically, bandwidth can be provided as a metered service and customers would pay for the bandwidth that they actually use. To achieve cost-effective bandwidth provisioning, this paper proposes an autonomic bandwidth adjustment scheme based on data analysis of traffic load. The scheme is implemented in a software defined networking (SDN) controller and is demonstrated in the field trial of multi-vendor optical transport networks. The field trial shows that the proposed scheme can track traffic load and realize autonomic bandwidth adjustment. In addition, a simulation experiment is conducted to evaluate the performance of the proposed scheme. We also investigate the impact of different parameters on autonomic bandwidth adjustment. Simulation results show that the step size and adjustment period have significant influences on bandwidth savings and packet loss. A small value of step size and adjustment period can bring more benefits by tracking traffic variation with high accuracy. For network operators, the scheme can serve as technical support of realizing bandwidth as metered service in the future.

Acoustic performance design and optimal allocation of sound package in ship cabin noise reduction

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YANG Deqing

2017-08-01

Full Text Available The sound package in noise reduction design of ship cabins has become the main approach for the future. The sound package is a specially designed acoustic component consisting of damping materials, absorption materials, sound isolation materials and base structural materials which can achieve the prescribed performance of noise reduction. Based on the Statistical Energy Analysis(SEAmethod, quick evaluation and design methods, and the optimal allocation theory of sound packages are investigated. The standard numerical acoustic performance evaluation model, sound package optimization design model and sound package optimal allocation model are presented. A genetic algorithm is applied to solve the presented optimization problems. Design examples demonstrate the validity and efficiency of the proposed models and solutions. The presented theory and methods benefit the standardization and programming of sound package design, and decrease noise reduction costs.

Simultaneous allocation of distributed resources using improved teaching learning based optimization

International Nuclear Information System (INIS)

Kanwar, Neeraj; Gupta, Nikhil; Niazi, K.R.; Swarnkar, Anil

2015-01-01

Highlights: • Simultaneous allocation of distributed energy resources in distribution networks. • Annual energy loss reduction is optimized using a multi-level load profile. • A new penalty factor approach is suggested to check node voltage deviations. • An improved TLBO is proposed by suggesting several modifications in standard TLBO. • An intelligent search is proposed to enhance the performance of solution technique. - Abstract: Active and reactive power flow in distribution networks can be effectively controlled by optimally placing distributed resources like shunt capacitors and distributed generators. This paper presents improved variant of Teaching Learning Based Optimization (TLBO) to efficiently and effectively deal with the problem of simultaneous allocation of these distributed resources in radial distribution networks while considering multi-level load scenario. Several algorithm specific modifications are suggested in the standard form of TLBO to cope against the intrinsic flaws of this technique. In addition, an intelligent search approach is proposed to restrict the problem search space without loss of diversity. This enhances the overall performance of the proposed method. The proposed method is investigated on IEEE 33-bus, 69-bus and 83-bus test distribution systems showing promising results

Priority and Negotiation Based Dynamic Spectrum Allocation Scheme for Multiple Radio Access Network Operators

Science.gov (United States)

Kim, Hoon; Hyon, Taein; Lee, Yeonwoo

Most of previous works have presented the dynamic spectrum allocation (DSA) gain achieved by utilizing the time or regional variations in traffic demand between multi-network operators (NOs). In this paper, we introduce the functionalities required for the entities related with the spectrum sharing and allocation and propose a spectrum allocation algorithm while considering the long-term priority between NOs, the priority between multiple class services, and the urgent bandwidth request. To take into account the priorities among the NOs and the priorities of multiple class services, a spectrum sharing metric (SSM) is proposed, while a negotiation procedure is proposed to treat the urgent bandwidth request.

Optimal load allocation of complex ship power plants

International Nuclear Information System (INIS)

Baldi, Francesco; Ahlgren, Fredrik; Melino, Francesco; Gabrielii, Cecilia; Andersson, Karin

2016-01-01

Highlights: • The optimal operation of the prime movers of hybrid ship power plants is addressed. • Both mechanical, electric and thermal power demand are considered. • The problem is modelled as a mixed integer-nonlinear programming problem. • Up to 3% savings can be achieved with hybrid power plants. • Including the thermal power demand improves the solution by up to 4%. - Abstract: In a world with increased pressure on reducing fuel consumption and carbon dioxide emissions, the cruise industry is growing in size and impact. In this context, further effort is required for improving the energy efficiency of cruise ship energy systems. In this paper, we propose a generic method for modelling the power plant of an isolated system with mechanical, electric and thermal power demands and for the optimal load allocation of the different components that are able to fulfil the demand. The optimisation problem is presented in the form of a mixed integer linear programming (MINLP) problem, where the number of engines and/or boilers running is represented by the integer variables, while their respective load is represented by the non-integer variables. The individual components are modelled using a combination of first-principle models and polynomial regressions, thus making the system nonlinear. The proposed method is applied to the load-allocation problem of a cruise ship sailing in the Baltic Sea, and used to compare the existing power plant with a hybrid propulsion plant. The results show the benefits brought by using the proposing method, which allow estimating the performance of the hybrid system (for which the load allocation is a non-trivial problem) while also including the contribution of the heat demand. This allows showing that, based on a reference round voyage, up to 3% savings could be achieved by installing the proposed system, compared to the existing one, and that a NPV of 11 kUSD could be achieved already 5 years after the installation of the

Performance Analysis and Optimal Allocation of Layered Defense M/M/N Queueing Systems

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Longyue Li

2016-01-01

Full Text Available One important mission of strategic defense is to develop an integrated layered Ballistic Missile Defense System (BMDS. Motivated by the queueing theory, we presented a work for the representation, modeling, performance simulation, and channels optimal allocation of the layered BMDS M/M/N queueing systems. Firstly, in order to simulate the process of defense and to study the Defense Effectiveness (DE, we modeled and simulated the M/M/N queueing system of layered BMDS. Specifically, we proposed the M/M/N/N and M/M/N/C queueing model for short defense depth and long defense depth, respectively; single target channel and multiple target channels were distinguished in each model. Secondly, we considered the problem of assigning limited target channels to incoming targets, we illustrated how to allocate channels for achieving the best DE, and we also proposed a novel and robust search algorithm for obtaining the minimum channel requirements across a set of neighborhoods. Simultaneously, we presented examples of optimal allocation problems under different constraints. Thirdly, several simulation examples verified the effectiveness of the proposed queueing models. This work may help to understand the rules of queueing process and to provide optimal configuration suggestions for defense decision-making.

Task Allocation and Path Planning for Collaborative Autonomous Underwater Vehicles Operating through an Underwater Acoustic Network

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Yueyue Deng

2013-01-01

Full Text Available Dynamic and unstructured multiple cooperative autonomous underwater vehicle (AUV missions are highly complex operations, and task allocation and path planning are made significantly more challenging under realistic underwater acoustic communication constraints. This paper presents a solution for the task allocation and path planning for multiple AUVs under marginal acoustic communication conditions: a location-aided task allocation framework (LAAF algorithm for multitarget task assignment and the grid-based multiobjective optimal programming (GMOOP mathematical model for finding an optimal vehicle command decision given a set of objectives and constraints. Both the LAAF and GMOOP algorithms are well suited in poor acoustic network condition and dynamic environment. Our research is based on an existing mobile ad hoc network underwater acoustic simulator and blind flooding routing protocol. Simulation results demonstrate that the location-aided auction strategy performs significantly better than the well-accepted auction algorithm developed by Bertsekas in terms of task-allocation time and network bandwidth consumption. We also demonstrate that the GMOOP path-planning technique provides an efficient method for executing multiobjective tasks by cooperative agents with limited communication capabilities. This is in contrast to existing multiobjective action selection methods that are limited to networks where constant, reliable communication is assumed to be available.

Multiple sensitive estimation and optimal sample size allocation in the item sum technique.

Science.gov (United States)

Perri, Pier Francesco; Rueda García, María Del Mar; Cobo Rodríguez, Beatriz

2018-01-01

For surveys of sensitive issues in life sciences, statistical procedures can be used to reduce nonresponse and social desirability response bias. Both of these phenomena provoke nonsampling errors that are difficult to deal with and can seriously flaw the validity of the analyses. The item sum technique (IST) is a very recent indirect questioning method derived from the item count technique that seeks to procure more reliable responses on quantitative items than direct questioning while preserving respondents' anonymity. This article addresses two important questions concerning the IST: (i) its implementation when two or more sensitive variables are investigated and efficient estimates of their unknown population means are required; (ii) the determination of the optimal sample size to achieve minimum variance estimates. These aspects are of great relevance for survey practitioners engaged in sensitive research and, to the best of our knowledge, were not studied so far. In this article, theoretical results for multiple estimation and optimal allocation are obtained under a generic sampling design and then particularized to simple random sampling and stratified sampling designs. Theoretical considerations are integrated with a number of simulation studies based on data from two real surveys and conducted to ascertain the efficiency gain derived from optimal allocation in different situations. One of the surveys concerns cannabis consumption among university students. Our findings highlight some methodological advances that can be obtained in life sciences IST surveys when optimal allocation is achieved. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A linear bi-level multi-objective program for optimal allocation of water resources.

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Ijaz Ahmad

Full Text Available This paper presents a simple bi-level multi-objective linear program (BLMOLP with a hierarchical structure consisting of reservoir managers and several water use sectors under a multi-objective framework for the optimal allocation of limited water resources. Being the upper level decision makers (i.e., leader in the hierarchy, the reservoir managers control the water allocation system and tend to create a balance among the competing water users thereby maximizing the total benefits to the society. On the other hand, the competing water use sectors, being the lower level decision makers (i.e., followers in the hierarchy, aim only to maximize individual sectoral benefits. This multi-objective bi-level optimization problem can be solved using the simultaneous compromise constraint (SICCON technique which creates a compromise between upper and lower level decision makers (DMs, and transforms the multi-objective function into a single decision-making problem. The bi-level model developed in this study has been applied to the Swat River basin in Pakistan for the optimal allocation of water resources among competing water demand sectors and different scenarios have been developed. The application of the model in this study shows that the SICCON is a simple, applicable and feasible approach to solve the BLMOLP problem. Finally, the comparisons of the model results show that the optimization model is practical and efficient when it is applied to different conditions with priorities assigned to various water users.

Dealing with equality and benefit for water allocation in a lake watershed: A Gini-coefficient based stochastic optimization approach

Science.gov (United States)

Dai, C.; Qin, X. S.; Chen, Y.; Guo, H. C.

2018-06-01

A Gini-coefficient based stochastic optimization (GBSO) model was developed by integrating the hydrological model, water balance model, Gini coefficient and chance-constrained programming (CCP) into a general multi-objective optimization modeling framework for supporting water resources allocation at a watershed scale. The framework was advantageous in reflecting the conflicting equity and benefit objectives for water allocation, maintaining the water balance of watershed, and dealing with system uncertainties. GBSO was solved by the non-dominated sorting Genetic Algorithms-II (NSGA-II), after the parameter uncertainties of the hydrological model have been quantified into the probability distribution of runoff as the inputs of CCP model, and the chance constraints were converted to the corresponding deterministic versions. The proposed model was applied to identify the Pareto optimal water allocation schemes in the Lake Dianchi watershed, China. The optimal Pareto-front results reflected the tradeoff between system benefit (αSB) and Gini coefficient (αG) under different significance levels (i.e. q) and different drought scenarios, which reveals the conflicting nature of equity and efficiency in water allocation problems. A lower q generally implies a lower risk of violating the system constraints and a worse drought intensity scenario corresponds to less available water resources, both of which would lead to a decreased system benefit and a less equitable water allocation scheme. Thus, the proposed modeling framework could help obtain the Pareto optimal schemes under complexity and ensure that the proposed water allocation solutions are effective for coping with drought conditions, with a proper tradeoff between system benefit and water allocation equity.

TPROXY dan FILTERING SEBAGAI METODE OPTIMASI PEMAKAIAN BANDWIDTH INTERNET

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Sutiyo Sutiyo

2015-04-01

Full Text Available Until now the use of the internet disuatu agencies viewed from the initial planning, use and care, even long-term planning is still not optimal. The main factor lies in the existing human resources, especially in IT personnel and policy makers who do not understand or do not even know at all how your use of the Internet well, optimal, efficient, particularly associated with the consumption of Internet bandwidth. Internet bandwidth capacity greatly affect the speed of web access or other Internet applications. So we need a plan and maintance necessary to obtain good Internet bandwidth consumption efficiency and guaranteed QoS, such as by utilizing Tproxy and filtering methods. TProxy is a development of which has been patched Squid, a proxy to be able to pass traffic without NAT (Network Access Translation. Fitering a firewall system which is used for filtering data packets that do not want filtered dikendaki or akhirmya able to minimize traffic on bandwidth usage. Tproxy and filtering runs on the Linux platform. Linux distributions are often used to Tproxy is a variant Debian, Centos and then to use Mikrotik Filtering. At the end of each request or query from the client or the response of the proxy server does not have meaningful constraints, the bandwidth between the client and the proxy server does not happen limitation, bandwidth capable of running close to capacity including 10 Mbps Ethernet, 100 Mbps, and even a GPS (full speed.

Optimal filter bandwidth for pulse oximetry

Science.gov (United States)

Stuban, Norbert; Niwayama, Masatsugu

2012-10-01

Pulse oximeters contain one or more signal filtering stages between the photodiode and microcontroller. These filters are responsible for removing the noise while retaining the useful frequency components of the signal, thus improving the signal-to-noise ratio. The corner frequencies of these filters affect not only the noise level, but also the shape of the pulse signal. Narrow filter bandwidth effectively suppresses the noise; however, at the same time, it distorts the useful signal components by decreasing the harmonic content. In this paper, we investigated the influence of the filter bandwidth on the accuracy of pulse oximeters. We used a pulse oximeter tester device to produce stable, repetitive pulse waves with digitally adjustable R ratio and heart rate. We built a pulse oximeter and attached it to the tester device. The pulse oximeter digitized the current of its photodiode directly, without any analog signal conditioning. We varied the corner frequency of the low-pass filter in the pulse oximeter in the range of 0.66-15 Hz by software. For the tester device, the R ratio was set to R = 1.00, and the R ratio deviation measured by the pulse oximeter was monitored as a function of the corner frequency of the low-pass filter. The results revealed that lowering the corner frequency of the low-pass filter did not decrease the accuracy of the oxygen level measurements. The lowest possible value of the corner frequency of the low-pass filter is the fundamental frequency of the pulse signal. We concluded that the harmonics of the pulse signal do not contribute to the accuracy of pulse oximetry. The results achieved by the pulse oximeter tester were verified by human experiments, performed on five healthy subjects. The results of the human measurements confirmed that filtering out the harmonics of the pulse signal does not degrade the accuracy of pulse oximetry.

Allocation base of general production costs as optimization of prime costs

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Levytska I.O.

2017-03-01

Full Text Available Qualified management aimed at optimizing financial results is the key factor in today's society. Effective management decisions depend on the necessary information about the costs of production process in all its aspects – their structure, types, accounting policies of reflecting costs. General production costs, the so-called indirect costs that are not directly related to the production process, but provide its functioning in terms of supporting structural divisions and create the necessary conditions of production, play a significant role in calculating prime costs of goods (works, services. However, the accurate estimate of prime costs of goods (works, services should be determined with the value of indirect costs (in other words, general production costs, and properly determined with the base of their allocation. The choice of allocation base of general production costs is the significant moment, depending on the nature of business, which must guarantee fair distribution regarding to the largest share of direct expenses in the total structure of production costs. The study finds the essence of general production costs based on the analysis of key definitions of leading Ukrainian economists. The optimal allocation approach of general production costs is to calculate these costs as direct production costs within each subsidiary division (department separately without selecting a base as the main one to the their total amount.

Optimal allocation of conservation effort among subpopulations of a threatened species: how important is patch quality?

Science.gov (United States)

Chauvenet, Aliénor L M; Baxter, Peter W J; McDonald-Madden, Eve; Possingham, Hugh P

2010-04-01

Money is often a limiting factor in conservation, and attempting to conserve endangered species can be costly. Consequently, a framework for optimizing fiscally constrained conservation decisions for a single species is needed. In this paper we find the optimal budget allocation among isolated subpopulations of a threatened species to minimize local extinction probability. We solve the problem using stochastic dynamic programming, derive a useful and simple alternative guideline for allocating funds, and test its performance using forward simulation. The model considers subpopulations that persist in habitat patches of differing quality, which in our model is reflected in different relationships between money invested and extinction risk. We discover that, in most cases, subpopulations that are less efficient to manage should receive more money than those that are more efficient to manage, due to higher investment needed to reduce extinction risk. Our simple investment guideline performs almost as well as the exact optimal strategy. We illustrate our approach with a case study of the management of the Sumatran tiger, Panthera tigris sumatrae, in Kerinci Seblat National Park (KSNP), Indonesia. We find that different budgets should be allocated to the separate tiger subpopulations in KSNP. The subpopulation that is not at risk of extinction does not require any management investment. Based on the combination of risks of extinction and habitat quality, the optimal allocation for these particular tiger subpopulations is an unusual case: subpopulations that occur in higher-quality habitat (more efficient to manage) should receive more funds than the remaining subpopulation that is in lower-quality habitat. Because the yearly budget allocated to the KSNP for tiger conservation is small, to guarantee the persistence of all the subpopulations that are currently under threat we need to prioritize those that are easier to save. When allocating resources among subpopulations

Optimal conservation resource allocation under variable economic and ecological time discounting rates in boreal forest

DEFF Research Database (Denmark)

Mazziotta, Adriano; Montesino Pouzols, Federico; Mönkkönen, Mikko

2016-01-01

Resource allocation to multiple alternative conservation actions is a complex task. A common trade-off occurs between protection of smaller, expensive, high-quality areas versus larger, cheaper, partially degraded areas. We investigate optimal allocation into three actions in boreal forest: current......, and accounting for present revenues from timber harvesting. The present analysis assesses the cost-effective conditions to allocate resources into an inexpensive conservation strategy that nevertheless has potential to produce high ecological values in the future....

BER and optimal power allocation for amplify-and-forward relaying using pilot-aided maximum likelihood estimation

KAUST Repository

Wang, Kezhi

2014-10-01

Bit error rate (BER) and outage probability for amplify-and-forward (AF) relaying systems with two different channel estimation methods, disintegrated channel estimation and cascaded channel estimation, using pilot-aided maximum likelihood method in slowly fading Rayleigh channels are derived. Based on the BERs, the optimal values of pilot power under the total transmitting power constraints at the source and the optimal values of pilot power under the total transmitting power constraints at the relay are obtained, separately. Moreover, the optimal power allocation between the pilot power at the source, the pilot power at the relay, the data power at the source and the data power at the relay are obtained when their total transmitting power is fixed. Numerical results show that the derived BER expressions match with the simulation results. They also show that the proposed systems with optimal power allocation outperform the conventional systems without power allocation under the same other conditions. In some cases, the gain could be as large as several dB\\'s in effective signal-to-noise ratio.

BER and optimal power allocation for amplify-and-forward relaying using pilot-aided maximum likelihood estimation

KAUST Repository

Wang, Kezhi; Chen, Yunfei; Alouini, Mohamed-Slim; Xu, Feng

2014-01-01

Bit error rate (BER) and outage probability for amplify-and-forward (AF) relaying systems with two different channel estimation methods, disintegrated channel estimation and cascaded channel estimation, using pilot-aided maximum likelihood method in slowly fading Rayleigh channels are derived. Based on the BERs, the optimal values of pilot power under the total transmitting power constraints at the source and the optimal values of pilot power under the total transmitting power constraints at the relay are obtained, separately. Moreover, the optimal power allocation between the pilot power at the source, the pilot power at the relay, the data power at the source and the data power at the relay are obtained when their total transmitting power is fixed. Numerical results show that the derived BER expressions match with the simulation results. They also show that the proposed systems with optimal power allocation outperform the conventional systems without power allocation under the same other conditions. In some cases, the gain could be as large as several dB's in effective signal-to-noise ratio.

Biometric Quantization through Detection Rate Optimized Bit Allocation

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C. Chen

2009-01-01

Full Text Available Extracting binary strings from real-valued biometric templates is a fundamental step in many biometric template protection systems, such as fuzzy commitment, fuzzy extractor, secure sketch, and helper data systems. Previous work has been focusing on the design of optimal quantization and coding for each single feature component, yet the binary string—concatenation of all coded feature components—is not optimal. In this paper, we present a detection rate optimized bit allocation (DROBA principle, which assigns more bits to discriminative features and fewer bits to nondiscriminative features. We further propose a dynamic programming (DP approach and a greedy search (GS approach to achieve DROBA. Experiments of DROBA on the FVC2000 fingerprint database and the FRGC face database show good performances. As a universal method, DROBA is applicable to arbitrary biometric modalities, such as fingerprint texture, iris, signature, and face. DROBA will bring significant benefits not only to the template protection systems but also to the systems with fast matching requirements or constrained storage capability.

Optimal relay selection and power allocation for cognitive two-way relaying networks

KAUST Repository

Pandarakkottilil, Ubaidulla; Aï ssa, Sonia

2012-01-01

In this paper, we present an optimal scheme for power allocation and relay selection in a cognitive radio network where a pair of cognitive (or secondary) transceiver nodes communicate with each other assisted by a set of cognitive two-way relays

Compression of Video Tracking and Bandwidth Balancing Routing in Wireless Multimedia Sensor Networks

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Yin Wang

2015-12-01

Full Text Available There has been a tremendous growth in multimedia applications over wireless networks. Wireless Multimedia Sensor Networks(WMSNs have become the premier choice in many research communities and industry. Many state-of-art applications, such as surveillance, traffic monitoring, and remote heath care are essentially video tracking and transmission in WMSNs. The transmission speed is constrained by the big file size of video data and fixed bandwidth allocation in constant routing paths. In this paper, we present a CamShift based algorithm to compress the tracking of videos. Then we propose a bandwidth balancing strategy in which each sensor node is able to dynamically select the node for the next hop with the highest potential bandwidth capacity to resume communication. Key to this strategy is that each node merely maintains two parameters that contain its historical bandwidth varying trend and then predict its near future bandwidth capacity. Then, the forwarding node selects the next hop with the highest potential bandwidth capacity. Simulations demonstrate that our approach significantly increases the data received by the sink node and decreases the delay on video transmission in Wireless Multimedia Sensor Network environments.

Optimal power allocation of a sensor node under different rate constraints

KAUST Repository

Ayala Solares, Jose Roberto

2012-06-01

The optimal transmit power of a sensor node while satisfying different rate constraints is derived. First, an optimization problem with an instantaneous transmission rate constraint is addressed. Next, the optimal power is analyzed, but now with an average transmission rate constraint. The optimal solution for a class of fading channels, in terms of system parameters, is presented and a suboptimal solution is also proposed for an easier, yet efficient, implementation. Insightful asymptotical analysis for both schemes, considering a Rayleigh fading channel, are shown. Finally, the optimal power allocation for a sensor node in a cognitive radio environment is analyzed where an optimum solution for a class of fading channels is again derived. In all cases, numerical results are provided for either Rayleigh or Nakagami-m fading channels. © 2012 IEEE.

Two-stage simplified swarm optimization for the redundancy allocation problem in a multi-state bridge system

International Nuclear Information System (INIS)

Lai, Chyh-Ming; Yeh, Wei-Chang

2016-01-01

The redundancy allocation problem involves configuring an optimal system structure with high reliability and low cost, either by alternating the elements with more reliable elements and/or by forming them redundantly. The multi-state bridge system is a special redundancy allocation problem and is commonly used in various engineering systems for load balancing and control. Traditional methods for redundancy allocation problem cannot solve multi-state bridge systems efficiently because it is impossible to transfer and reduce a multi-state bridge system to series and parallel combinations. Hence, a swarm-based approach called two-stage simplified swarm optimization is proposed in this work to effectively and efficiently solve the redundancy allocation problem in a multi-state bridge system. For validating the proposed method, two experiments are implemented. The computational results indicate the advantages of the proposed method in terms of solution quality and computational efficiency. - Highlights: • Propose two-stage SSO (SSO_T_S) to deal with RAP in multi-state bridge system. • Dynamic upper bound enhances the efficiency of searching near-optimal solution. • Vector-update stages reduces the problem dimensions. • Statistical results indicate SSO_T_S is robust both in solution quality and runtime.

Application of goal programming to decision problem on optimal allocation of radiation workers

International Nuclear Information System (INIS)

Sa, Sangduk; Narita, Masakuni

1993-01-01

This paper is concerned with an optimal planning in a multiple objective decision-making problem of allocating radiation workers to workplaces associated with occupational exposure. The model problem is formulated with the application of goal programming which effectively followed up diverse and conflicting factors influencing the optimal decision. The formulation is based on the data simulating the typical situations encountered at the operating facilities such as nuclear power plants where exposure control is critical to the management. Multiple goals set by the decision-maker/manager who has the operational responsibilities for radiological protection are illustrated in terms of work requirements, exposure constraints of the places, desired allocation of specific personnel and so on. Test results of the model are considered to indicate that the model structure and its solution process can provide the manager with a good set of analysis of his problems in implementing the optimization review of radiation protection during normal operation. (author)

Optimizing multiple reliable forward contracts for reservoir allocation using multitime scale streamflow forecasts

Science.gov (United States)

Lu, Mengqian; Lall, Upmanu; Robertson, Andrew W.; Cook, Edward

2017-03-01

Streamflow forecasts at multiple time scales provide a new opportunity for reservoir management to address competing objectives. Market instruments such as forward contracts with specified reliability are considered as a tool that may help address the perceived risk associated with the use of such forecasts in lieu of traditional operation and allocation strategies. A water allocation process that enables multiple contracts for water supply and hydropower production with different durations, while maintaining a prescribed level of flood risk reduction, is presented. The allocation process is supported by an optimization model that considers multitime scale ensemble forecasts of monthly streamflow and flood volume over the upcoming season and year, the desired reliability and pricing of proposed contracts for hydropower and water supply. It solves for the size of contracts at each reliability level that can be allocated for each future period, while meeting target end of period reservoir storage with a prescribed reliability. The contracts may be insurable, given that their reliability is verified through retrospective modeling. The process can allow reservoir operators to overcome their concerns as to the appropriate skill of probabilistic forecasts, while providing water users with short-term and long-term guarantees as to how much water or energy they may be allocated. An application of the optimization model to the Bhakra Dam, India, provides an illustration of the process. The issues of forecast skill and contract performance are examined. A field engagement of the idea is useful to develop a real-world perspective and needs a suitable institutional environment.

Resource allocation using ANN in LTE

Science.gov (United States)

Yigit, Tuncay; Ersoy, Mevlut

2017-07-01

LTE is the 4th generation wireless network technology, which provides flexible bandwidth, higher data speeds and lower delay. Difficulties may be experienced upon an increase in the number of users in LTE. The objective of this study is to ensure a faster solution to any such resource allocation problems which might arise upon an increase in the number of users. A fast and effective solution has been obtained by making use of Artificial Neural Network. As a result, fast working artificial intelligence methods may be used in resource allocation problems during operation.

Optimizing the allocation of resources for genomic selection in one breeding cycle.

Science.gov (United States)

Riedelsheimer, Christian; Melchinger, Albrecht E

2013-11-01

We developed a universally applicable planning tool for optimizing the allocation of resources for one cycle of genomic selection in a biparental population. The framework combines selection theory with constraint numerical optimization and considers genotype  ×  environment interactions. Genomic selection (GS) is increasingly implemented in plant breeding programs to increase selection gain but little is known how to optimally allocate the resources under a given budget. We investigated this problem with model calculations by combining quantitative genetic selection theory with constraint numerical optimization. We assumed one selection cycle where both the training and prediction sets comprised double haploid (DH) lines from the same biparental population. Grain yield for testcrosses of maize DH lines was used as a model trait but all parameters can be adjusted in a freely available software implementation. An extension of the expected selection accuracy given by Daetwyler et al. (2008) was developed to correctly balance between the number of environments for phenotyping the training set and its population size in the presence of genotype × environment interactions. Under small budget, genotyping costs mainly determine whether GS is superior over phenotypic selection. With increasing budget, flexibility in resource allocation increases greatly but selection gain leveled off quickly requiring balancing the number of populations with the budget spent for each population. The use of an index combining phenotypic and GS predicted values in the training set was especially beneficial under limited resources and large genotype × environment interactions. Once a sufficiently high selection accuracy is achieved in the prediction set, further selection gain can be achieved most efficiently by massively expanding its size. Thus, with increasing budget, reducing the costs for producing a DH line becomes increasingly crucial for successfully exploiting the

A Knowledge-Informed and Pareto-Based Artificial Bee Colony Optimization Algorithm for Multi-Objective Land-Use Allocation

Directory of Open Access Journals (Sweden)

Lina Yang

2018-02-01

Full Text Available Land-use allocation is of great significance in urban development. This type of allocation is usually considered to be a complex multi-objective spatial optimization problem, whose optimized result is a set of Pareto-optimal solutions (Pareto front reflecting different tradeoffs in several objectives. However, obtaining a Pareto front is a challenging task, and the Pareto front obtained by state-of-the-art algorithms is still not sufficient. To achieve better Pareto solutions, taking the grid-representative land-use allocation problem with two objectives as an example, an artificial bee colony optimization algorithm for multi-objective land-use allocation (ABC-MOLA is proposed. In this algorithm, the traditional ABC’s search direction guiding scheme and solution maintaining process are modified. In addition, a knowledge-informed neighborhood search strategy, which utilizes the auxiliary knowledge of natural geography and spatial structures to facilitate the neighborhood spatial search around each solution, is developed to further improve the Pareto front’s quality. A series of comparison experiments (a simulated experiment with small data volume and a real-world data experiment for a large area shows that all the Pareto fronts obtained by ABC-MOLA totally dominate the Pareto fronts by other algorithms, which demonstrates ABC-MOLA’s effectiveness in achieving Pareto fronts of high quality.

An Optimal Joint User Association and Power Allocation Algorithm for Secrecy Information Transmission in Heterogeneous Networks

Directory of Open Access Journals (Sweden)

Rong Chai

2017-01-01

Full Text Available In recent years, heterogeneous radio access technologies have experienced rapid development and gradually achieved effective coordination and integration, resulting in heterogeneous networks (HetNets. In this paper, we consider the downlink secure transmission of HetNets where the information transmission from base stations (BSs to legitimate users is subject to the interception of eavesdroppers. In particular, we stress the problem of joint user association and power allocation of the BSs. To achieve data transmission in a secure and energy efficient manner, we introduce the concept of secrecy energy efficiency which is defined as the ratio of the secrecy transmission rate and power consumption of the BSs and formulate the problem of joint user association and power allocation as an optimization problem which maximizes the joint secrecy energy efficiency of all the BSs under the power constraint of the BSs and the minimum data rate constraint of user equipment (UE. By equivalently transforming the optimization problem into two subproblems, that is, power allocation subproblem and user association subproblem of the BSs, and applying iterative method and Kuhn-Munkres (K-M algorithm to solve the two subproblems, respectively, the optimal user association and power allocation strategies can be obtained. Numerical results demonstrate that the proposed algorithm outperforms previously proposed algorithms.

Theoretical Aspects of Optimizing the Allocation of Public Financial Resources at Local Level

OpenAIRE

Eugen DOGARIU

2010-01-01

The allocation of financial resources at local, but also at central level, is an issue especially since in times of crisis, finding the optimum way to spend public funds concerns all authorities. This paper aims to identify the ways in which, by leaving from the division of powers based on the allocation of resources and tools available, the local authorities can identify an optimal level of public expenditure so as to achieve a maximum level of using them. Also, the paper seeks to identify t...

Reliability–redundancy allocation problem considering optimal redundancy strategy using parallel genetic algorithm

International Nuclear Information System (INIS)

Kim, Heungseob; Kim, Pansoo

2017-01-01

To maximize the reliability of a system, the traditional reliability–redundancy allocation problem (RRAP) determines the component reliability and level of redundancy for each subsystem. This paper proposes an advanced RRAP that also considers the optimal redundancy strategy, either active or cold standby. In addition, new examples are presented for it. Furthermore, the exact reliability function for a cold standby redundant subsystem with an imperfect detector/switch is suggested, and is expected to replace the previous approximating model that has been used in most related studies. A parallel genetic algorithm for solving the RRAP as a mixed-integer nonlinear programming model is presented, and its performance is compared with those of previous studies by using numerical examples on three benchmark problems. - Highlights: • Optimal strategy is proposed to solve reliability redundancy allocation problem. • The redundancy strategy uses parallel genetic algorithm. • Improved reliability function for a cold standby subsystem is suggested. • Proposed redundancy strategy enhances the system reliability.

Optimal allocation of International Atomic Energy Agency inspection resources

International Nuclear Information System (INIS)

Markin, J.T.

1987-12-01

The Safeguards Department of the International Atomic Energy Agency (IAEA) conducts inspections to assure the peaceful use of a state's nuclear materials and facilities. Because of limited resources for conducting inspections, the careful disposition of inspection effort among these facilities is essential if the IAEA is to attain its safeguards goals. This report describes an optimization procedure for assigning an inspection effort to maximize attainment of IAEA goals. The procedure does not require quantitative estimates of safeguards effectiveness, material value, or facility importance. Instead, the optimization is based on qualitative, relative prioritizations of inspection activities and materials to be safeguarded. This allocation framework is applicable to an arbitrary group of facilities such as a state's fuel cycle, the facilities inspected by an operations division, or all of the facilities inspected by the IAEA

Optimal Control of Micro Grid Operation Mode Seamless Switching Based on Radau Allocation Method

Science.gov (United States)

Chen, Xiaomin; Wang, Gang

2017-05-01

The seamless switching process of micro grid operation mode directly affects the safety and stability of its operation. According to the switching process from island mode to grid-connected mode of micro grid, we establish a dynamic optimization model based on two grid-connected inverters. We use Radau allocation method to discretize the model, and use Newton iteration method to obtain the optimal solution. Finally, we implement the optimization mode in MATLAB and get the optimal control trajectory of the inverters.

Optimal Power Allocation for Downstream xDSL With Per-Modem Total Power Constraints: Broadcast Channel Optimal Spectrum Balancing (BC-OSB)

Science.gov (United States)

Le Nir, Vincent; Moonen, Marc; Verlinden, Jan; Guenach, Mamoun

2009-02-01

Recently, the duality between Multiple Input Multiple Output (MIMO) Multiple Access Channels (MAC) and MIMO Broadcast Channels (BC) has been established under a total power constraint. The same set of rates for MAC can be achieved in BC exploiting the MAC-BC duality formulas while preserving the total power constraint. In this paper, we describe the BC optimal power allo- cation applying this duality in a downstream x-Digital Subscriber Lines (xDSL) context under a total power constraint for all modems over all tones. Then, a new algorithm called BC-Optimal Spectrum Balancing (BC-OSB) is devised for a more realistic power allocation under per-modem total power constraints. The capacity region of the primal BC problem under per-modem total power constraints is found by the dual optimization problem for the BC under per-modem total power constraints which can be rewritten as a dual optimization problem in the MAC by means of a precoder matrix based on the Lagrange multipliers. We show that the duality gap between the two problems is zero. The multi-user power allocation problem has been solved for interference channels and MAC using the OSB algorithm. In this paper we solve the problem of multi-user power allocation for the BC case using the OSB algorithm as well and we derive a computational efficient algorithm that will be referred to as BC-OSB. Simulation results are provided for two VDSL2 scenarios: the first one with Differential-Mode (DM) transmission only and the second one with both DM and Phantom- Mode (PM) transmissions.

Energy-Efficient Power Allocation of Cognitive Radio Systems without CSI at the Transmitter

KAUST Repository

Sboui, Lokman

2015-01-07

Two major issues are facing today’s wireless communications evolution: -Spectrum scarcity: Need for more bandwidth. As a solution, the Cognitive Radio (CR) paradigm, where secondary users (unlicensed) share the spectrum with licensed users, was introduced. -Energy consumption and CO2 emission: The ICT produce 2% of global CO2 emission (equivalent to the aviation industry emission). The cellular networks produces 0.2%. As solution energy efficient systems should be designed rather than traditional spectral efficient systems. In this work, we aim to determine the optimal energy efficient power allocation of CR when the channel state information at the transmitter CSI-T is not available.

Energy-Efficient Power Allocation of Cognitive Radio Systems without CSI at the Transmitter

KAUST Repository

Sboui, Lokman; Rezki, Zouheir; Alouini, Mohamed-Slim

2015-01-01

Two major issues are facing today’s wireless communications evolution: -Spectrum scarcity: Need for more bandwidth. As a solution, the Cognitive Radio (CR) paradigm, where secondary users (unlicensed) share the spectrum with licensed users, was introduced. -Energy consumption and CO2 emission: The ICT produce 2% of global CO2 emission (equivalent to the aviation industry emission). The cellular networks produces 0.2%. As solution energy efficient systems should be designed rather than traditional spectral efficient systems. In this work, we aim to determine the optimal energy efficient power allocation of CR when the channel state information at the transmitter CSI-T is not available.

Resource Allocation Optimization Model of Collaborative Logistics Network Based on Bilevel Programming

Directory of Open Access Journals (Sweden)

Xiao-feng Xu

2017-01-01

Full Text Available Collaborative logistics network resource allocation can effectively meet the needs of customers. It can realize the overall benefit maximization of the logistics network and ensure that collaborative logistics network runs orderly at the time of creating value. Therefore, this article is based on the relationship of collaborative logistics network supplier, the transit warehouse, and sellers, and we consider the uncertainty of time to establish a bilevel programming model with random constraints and propose a genetic simulated annealing hybrid intelligent algorithm to solve it. Numerical example shows that the method has stronger robustness and convergence; it can achieve collaborative logistics network resource allocation rationalization and optimization.

Sensitivity-Bandwidth Limit in a Multimode Optoelectromechanical Transducer

Science.gov (United States)

Moaddel Haghighi, I.; Malossi, N.; Natali, R.; Di Giuseppe, G.; Vitali, D.

2018-03-01

An optoelectromechanical system formed by a nanomembrane capacitively coupled to an L C resonator and to an optical interferometer has recently been employed for the highly sensitive optical readout of rf signals [T. Bagci et al., Nature (London) 507, 81 (2013), 10.1038/nature13029]. We propose and experimentally demonstrate how the bandwidth of such a transducer can be increased by controlling the interference between two electromechanical interaction pathways of a two-mode mechanical system. With a proof-of-principle device operating at room temperature, we achieve a sensitivity of 300 nV /√{Hz } over a bandwidth of 15 kHz in the presence of radio-frequency noise, and an optimal shot-noise-limited sensitivity of 10 nV /√{Hz } over a bandwidth of 5 kHz. We discuss strategies for improving the performance of the device, showing that, for the same given sensitivity, a mechanical multimode transducer can achieve a bandwidth significantly larger than that for a single-mode one.

A generalized fuzzy credibility-constrained linear fractional programming approach for optimal irrigation water allocation under uncertainty

Science.gov (United States)

Zhang, Chenglong; Guo, Ping

2017-10-01

The vague and fuzzy parametric information is a challenging issue in irrigation water management problems. In response to this problem, a generalized fuzzy credibility-constrained linear fractional programming (GFCCFP) model is developed for optimal irrigation water allocation under uncertainty. The model can be derived from integrating generalized fuzzy credibility-constrained programming (GFCCP) into a linear fractional programming (LFP) optimization framework. Therefore, it can solve ratio optimization problems associated with fuzzy parameters, and examine the variation of results under different credibility levels and weight coefficients of possibility and necessary. It has advantages in: (1) balancing the economic and resources objectives directly; (2) analyzing system efficiency; (3) generating more flexible decision solutions by giving different credibility levels and weight coefficients of possibility and (4) supporting in-depth analysis of the interrelationships among system efficiency, credibility level and weight coefficient. The model is applied to a case study of irrigation water allocation in the middle reaches of Heihe River Basin, northwest China. Therefore, optimal irrigation water allocation solutions from the GFCCFP model can be obtained. Moreover, factorial analysis on the two parameters (i.e. λ and γ) indicates that the weight coefficient is a main factor compared with credibility level for system efficiency. These results can be effective for support reasonable irrigation water resources management and agricultural production.

Optimizing time and resource allocation trade-offs for investment into morphological and behavioral defense

DEFF Research Database (Denmark)

Steiner, Uli; Pfeiffer, Thomas

2007-01-01

pronounced at intermediate environmental conditions. Optimizing single traits generally leads to a more pronounced response of the defense traits, which implies that studying single traits leads to an overestimation of their response to predation. Behavioral defense and morphological defense compensate......Prey organisms are confronted with time and resource allocation trade-offs. Time allocation trade-offs partition time, for example, between foraging effort to acquire resources and behavioral defense. Resource allocation trade-offs partition the acquired resources between multiple traits...... for and augment each other depending on predator densities and the effectiveness of the defense mechanisms. In the presence of time constraints, the model shows peak investment into morphological and behavioral defense at intermediate resource levels....

Optimal allocation of land and water resources to achieve Water, Energy and Food Security in the upper Blue Nile basin

Science.gov (United States)

Allam, M.; Eltahir, E. A. B.

2017-12-01

Rapid population growth, hunger problems, increasing energy demands, persistent conflicts between the Nile basin riparian countries and the potential impacts of climate change highlight the urgent need for the conscious stewardship of the upper Blue Nile (UBN) basin resources. This study develops a framework for the optimal allocation of land and water resources to agriculture and hydropower production in the UBN basin. The framework consists of three optimization models that aim to: (a) provide accurate estimates of the basin water budget, (b) allocate land and water resources optimally to agriculture, and (c) allocate water to agriculture and hydropower production, and investigate trade-offs between them. First, a data assimilation procedure for data-scarce basins is proposed to deal with data limitations and produce estimates of the hydrologic components that are consistent with the principles of mass and energy conservation. Second, the most representative topography and soil properties datasets are objectively identified and used to delineate the agricultural potential in the basin. The agricultural potential is incorporated into a land-water allocation model that maximizes the net economic benefits from rain-fed agriculture while allowing for enhancing the soils from one suitability class to another to increase agricultural productivity in return for an investment in soil inputs. The optimal agricultural expansion is expected to reduce the basin flow by 7.6 cubic kilometres, impacting downstream countries. The optimization framework is expanded to include hydropower production. This study finds that allocating water to grow rain-fed teff in the basin is more profitable than allocating water for hydropower production. Optimal operation rules for the Grand Ethiopian Renaissance dam (GERD) are identified to maximize annual hydropower generation while achieving a relatively uniform monthly production rate. Trade-offs between agricultural expansion and hydropower

Hierarchical resource allocation for robust in-home video streaming

NARCIS (Netherlands)

Stok, van der P.D.V.; Jarnikov, D.; Kozlov, S.; Hartskamp, van M.A.; Lukkien, J.J.

2007-01-01

High quality video streaming puts high demands on network and processor resources. The bandwidth of the communication medium and the timely arrival of the frames necessitate a tight resource allocation. Given the dynamic environment where videos are started and stopped and electro-magnetic

Finding the Pareto Optimal Equitable Allocation of Homogeneous Divisible Goods Among Three Players

Directory of Open Access Journals (Sweden)

Marco Dall'Aglio

2017-01-01

Full Text Available We consider the allocation of a finite number of homogeneous divisible items among three players. Under the assumption that each player assigns a positive value to every item, we develop a simple algorithm that returns a Pareto optimal and equitable allocation. This is based on the tight relationship between two geometric objects of fair division: The Individual Pieces Set (IPS and the Radon-Nykodim Set (RNS. The algorithm can be considered as an extension of the Adjusted Winner procedure by Brams and Taylor to the three-player case, without the guarantee of envy-freeness. (original abstract

Large Portfolio Risk Management and Optimal Portfolio Allocation with Dynamic Copulas

OpenAIRE

Thorsten Lehnert; Xisong Jin

2011-01-01

Previous research focuses on the importance of modeling the multivariate distribution for optimal portfolio allocation and active risk management. However, available dynamic models are not easily applied for high-dimensional problems due to the curse of dimensionality. In this paper, we extend the framework of the Dynamic Conditional Correlation/Equicorrelation and an extreme value approach into a series of Dynamic Conditional Elliptical Copulas. We investigate risk measures like Value at Ris...

Optimization of NANOGrav's time allocation for maximum sensitivity to single sources

International Nuclear Information System (INIS)

Christy, Brian; Anella, Ryan; Lommen, Andrea; Camuccio, Richard; Handzo, Emma; Finn, Lee Samuel

2014-01-01

Pulsar timing arrays (PTAs) are a collection of precisely timed millisecond pulsars (MSPs) that can search for gravitational waves (GWs) in the nanohertz frequency range by observing characteristic signatures in the timing residuals. The sensitivity of a PTA depends on the direction of the propagating GW source, the timing accuracy of the pulsars, and the allocation of the available observing time. The goal of this paper is to determine the optimal time allocation strategy among the MSPs in the North American Nanohertz Observatory for Gravitational Waves (NANOGrav) for a single source of GW under a particular set of assumptions. We consider both an isotropic distribution of sources across the sky and a specific source in the Virgo cluster. This work improves on previous efforts by modeling the effect of intrinsic spin noise for each pulsar. We find that, in general, the array is optimized by maximizing time spent on the best-timed pulsars, with sensitivity improvements typically ranging from a factor of 1.5 to 4.

The Optimal Allocation for Capital Preservation: an Evidence Australian Portfolio

Directory of Open Access Journals (Sweden)

Riznaldi Akbar

2018-05-01

Full Text Available This study analyzes optimal asset mix for Australian portfolios with the main investment objective for capital preservation. An alternative measure of risk of annual maximum drawdown has been used to reflect investor preference for capital preservation as opposed to conventional risk measure of standard deviation and variance. The contribution of the study is two folds. First, this study has put different perspective to look at portfolio risk in the view of capital preservation. Second, the optimal weight for asset class mix that minimizes annual maximum drawdown has been analyzed for the case of Australian market. The results suggest that for capital preservation, investors should expect lower returns and need to put a greater allocation on less risky assets such as cash or bond. To this end, cash and bond have provided stable long term annual returns along with contained level of annual maximum drawdowns. In contrast, when investors demand higher expected return, they should increase asset allocation into stocks (equities market at the expense of higher maximum drawdowns. Bahasa Indonesia Abstrak: Studi ini menganalisis bauran aset optimal untuk portofolio Australia dengan tujuan investasi utama untuk pelestarian modal. Ukuran alternatif risiko penarikan maksimum tahunan telah digunakan untuk mencerminkan preferensi investor untuk pelestarian modal dibandingkan dengan ukuran risiko konvensional standar deviasi dan varians. Kontribusi dari penelitian ini adalah dua lipatan. Pertama, penelitian ini telah menempatkan perspektif yang berbeda untuk melihat risiko portofolio dalam pandangan pelestarian modal. Kedua, bobot optimal untuk campuran kelas aset yang meminimalkan penarikan maksimum tahunan telah dianalisis untuk kasus pasar Australia. Hasilnya menunjukkan bahwa untuk pelestarian modal, investor harus mengharapkan pengembalian yang lebih rendah dan perlu menempatkan alokasi yang lebih besar pada aset yang kurang berisiko seperti uang tunai

Optimal Allocation of Smart Substations in a Distribution System Considering Interruption Costs of Customers

DEFF Research Database (Denmark)

Sun, Lei; You, Shi; Hu, Junjie

2016-01-01

number and allocation of smart substations in a given distribution system is presented, with the upgrade costs of substations and the interruption costs of customers taken into account. Besides, the reliability criterion is also properly considered in the model. By linearization strategies, the SSAM......One of the major functions of a smart substation (SS) is to restore power supply to interrupted customers as quickly as possible after an outage. The high cost of a smart substation limits its widespread utilization. In this paper, a smart substation allocation model (SSAM) to determine the optimal...

Optimal conservation resource allocation under variable economic and ecological time discounting rates in boreal forest.

Science.gov (United States)

Mazziotta, Adriano; Pouzols, Federico Montesino; Mönkkönen, Mikko; Kotiaho, Janne S; Strandman, Harri; Moilanen, Atte

2016-09-15

Resource allocation to multiple alternative conservation actions is a complex task. A common trade-off occurs between protection of smaller, expensive, high-quality areas versus larger, cheaper, partially degraded areas. We investigate optimal allocation into three actions in boreal forest: current standard forest management rules, setting aside of mature stands, or setting aside of clear-cuts. We first estimated how habitat availability for focal indicator species and economic returns from timber harvesting develop through time as a function of forest type and action chosen. We then developed an optimal resource allocation by accounting for budget size and habitat availability of indicator species in different forest types. We also accounted for the perspective adopted towards sustainability, modeled via temporal preference and economic and ecological time discounting. Controversially, we found that in boreal forest set-aside followed by protection of clear-cuts can become a winning cost-effective strategy when accounting for habitat requirements of multiple species, long planning horizon, and limited budget. It is particularly effective when adopting a long-term sustainability perspective, and accounting for present revenues from timber harvesting. The present analysis assesses the cost-effective conditions to allocate resources into an inexpensive conservation strategy that nevertheless has potential to produce high ecological values in the future. Copyright © 2016 Elsevier Ltd. All rights reserved.

Optimal Allocation of Generalized Power Sources in Distribution Network Based on Multi-Objective Particle Swarm Optimization Algorithm

Directory of Open Access Journals (Sweden)

Li Ran

2017-01-01

Full Text Available Optimal allocation of generalized power sources in distribution network is researched. A simple index of voltage stability is put forward. Considering the investment and operation benefit, the stability of voltage and the pollution emissions of generalized power sources in distribution network, a multi-objective optimization planning model is established. A multi-objective particle swarm optimization algorithm is proposed to solve the optimal model. In order to improve the global search ability, the strategies of fast non-dominated sorting, elitism and crowding distance are adopted in this algorithm. Finally, tested the model and algorithm by IEEE-33 node system to find the best configuration of GP, the computed result shows that with the generalized power reasonable access to the active distribution network, the investment benefit and the voltage stability of the system is improved, and the proposed algorithm has better global search capability.

Optimal allocation of the limited oral cholera vaccine supply between endemic and epidemic settings.

Science.gov (United States)

Moore, Sean M; Lessler, Justin

2015-10-06

The World Health Organization (WHO) recently established a global stockpile of oral cholera vaccine (OCV) to be preferentially used in epidemic response (reactive campaigns) with any vaccine remaining after 1 year allocated to endemic settings. Hence, the number of cholera cases or deaths prevented in an endemic setting represents the minimum utility of these doses, and the optimal risk-averse response to any reactive vaccination request (i.e. the minimax strategy) is one that allocates the remaining doses between the requested epidemic response and endemic use in order to ensure that at least this minimum utility is achieved. Using mathematical models, we find that the best minimax strategy is to allocate the majority of doses to reactive campaigns, unless the request came late in the targeted epidemic. As vaccine supplies dwindle, the case for reactive use of the remaining doses grows stronger. Our analysis provides a lower bound for the amount of OCV to keep in reserve when responding to any request. These results provide a strategic context for the fulfilment of requests to the stockpile, and define allocation strategies that minimize the number of OCV doses that are allocated to suboptimal situations. © 2015 The Authors.

Decision tables and rule engines in organ allocation systems for optimal transparency and flexibility.

Science.gov (United States)

Schaafsma, Murk; van der Deijl, Wilfred; Smits, Jacqueline M; Rahmel, Axel O; de Vries Robbé, Pieter F; Hoitsma, Andries J

2011-05-01

Organ allocation systems have become complex and difficult to comprehend. We introduced decision tables to specify the rules of allocation systems for different organs. A rule engine with decision tables as input was tested for the Kidney Allocation System (ETKAS). We compared this rule engine with the currently used ETKAS by running 11,000 historical match runs and by running the rule engine in parallel with the ETKAS on our allocation system. Decision tables were easy to implement and successful in verifying correctness, completeness, and consistency. The outcomes of the 11,000 historical matches in the rule engine and the ETKAS were exactly the same. Running the rule engine simultaneously in parallel and in real time with the ETKAS also produced no differences. Specifying organ allocation rules in decision tables is already a great step forward in enhancing the clarity of the systems. Yet, using these tables as rule engine input for matches optimizes the flexibility, simplicity and clarity of the whole process, from specification to the performed matches, and in addition this new method allows well controlled simulations. © 2011 The Authors. Transplant International © 2011 European Society for Organ Transplantation.

Optimal Portfolio Allocation under a Probabilistic Risk Constraint and the Incentives for Financial Innovation

NARCIS (Netherlands)

J. Daníelsson (Jón); B.N. Jorgensen (Bjørn); C.G. de Vries (Casper); X. Yang (Xiaoguang)

2001-01-01

textabstractWe derive, in a complete markets environment, an investor's optimal portfolio allocation subject to both a budget constraint and a probabilistic risk constraint. We demonstrate that the set of feasible portfolios need not be connected or convex, while the number of local optima increases

Optimal power allocation and joint source-channel coding for wireless DS-CDMA visual sensor networks

Science.gov (United States)

Pandremmenou, Katerina; Kondi, Lisimachos P.; Parsopoulos, Konstantinos E.

2011-01-01

In this paper, we propose a scheme for the optimal allocation of power, source coding rate, and channel coding rate for each of the nodes of a wireless Direct Sequence Code Division Multiple Access (DS-CDMA) visual sensor network. The optimization is quality-driven, i.e. the received quality of the video that is transmitted by the nodes is optimized. The scheme takes into account the fact that the sensor nodes may be imaging scenes with varying levels of motion. Nodes that image low-motion scenes will require a lower source coding rate, so they will be able to allocate a greater portion of the total available bit rate to channel coding. Stronger channel coding will mean that such nodes will be able to transmit at lower power. This will both increase battery life and reduce interference to other nodes. Two optimization criteria are considered. One that minimizes the average video distortion of the nodes and one that minimizes the maximum distortion among the nodes. The transmission powers are allowed to take continuous values, whereas the source and channel coding rates can assume only discrete values. Thus, the resulting optimization problem lies in the field of mixed-integer optimization tasks and is solved using Particle Swarm Optimization. Our experimental results show the importance of considering the characteristics of the video sequences when determining the transmission power, source coding rate and channel coding rate for the nodes of the visual sensor network.

Optimization of lift gas allocation in a gas lifted oil field as non-linear optimization problem

Directory of Open Access Journals (Sweden)

Roshan Sharma

2012-01-01

Full Text Available Proper allocation and distribution of lift gas is necessary for maximizing total oil production from a field with gas lifted oil wells. When the supply of the lift gas is limited, the total available gas should be optimally distributed among the oil wells of the field such that the total production of oil from the field is maximized. This paper describes a non-linear optimization problem with constraints associated with the optimal distribution of the lift gas. A non-linear objective function is developed using a simple dynamic model of the oil field where the decision variables represent the lift gas flow rate set points of each oil well of the field. The lift gas optimization problem is solved using the emph'fmincon' solver found in MATLAB. As an alternative and for verification, hill climbing method is utilized for solving the optimization problem. Using both of these methods, it has been shown that after optimization, the total oil production is increased by about 4. For multiple oil wells sharing lift gas from a common source, a cascade control strategy along with a nonlinear steady state optimizer behaves as a self-optimizing control structure when the total supply of lift gas is assumed to be the only input disturbance present in the process. Simulation results show that repeated optimization performed after the first time optimization under the presence of the input disturbance has no effect in the total oil production.

Optimal capital accumulation and the allocation of investment between traded and nontraded sectors in oil-producing countries.

NARCIS (Netherlands)

van Wijnbergen, S.J.G.

1985-01-01

A paper on the optimal capital accumulation and allocation of investment in oil exporting countries. Investigates the basis of consumption and investment levels on optimizing forward-looking behavior, the role of physical capital in the production, the impact of the decline in oil revenues on the

A Fuzzy Max–Min Decision Bi-Level Fuzzy Programming Model for Water Resources Optimization Allocation under Uncertainty

Directory of Open Access Journals (Sweden)

Chongfeng Ren

2018-04-01

Full Text Available Water competing conflict among water competing sectors from different levels should be taken under consideration during the optimization allocation of water resources. Furthermore, uncertainties are inevitable in the optimization allocation of water resources. In order to deal with the above problems, this study developed a fuzzy max–min decision bi-level fuzzy programming model. The developed model was then applied to a case study in Wuwei, Gansu Province, China. In this study, the net benefit and yield were regarded as the upper-level and lower-level objectives, respectively. Optimal water resource plans were obtained under different possibility levels of fuzzy parameters, which could deal with water competing conflict between the upper level and the lower level effectively. The obtained results are expected to make great contribution in helping local decision-makers to make decisions on dealing with the water competing conflict between the upper and lower level and the optimal use of water resources under uncertainty.

The multi-port berth allocation problem with speed optimization and emission considerations

DEFF Research Database (Denmark)

Venturini, Giada; Iris, Cagatay; Kontovas, Christos A.

2017-01-01

The container shipping industry faces many interrelated challenges and opportunities, as its role in the global trading system has become increasingly important over the last decades. On the one side, collaboration between port terminals and shipping liners can lead to costs savings and help...... achieve a sustainable supply chain, and on the other side, the optimization of operations and sailing times leads to reductions in bunker consumption and, thus, to fuel cost and air emissions reductions. To that effect, there is an increasing need to address the integration opportunities and environmental...... issues related to container shipping through optimization. This paper focuses on the well known Berth Allocation Problem (BAP), an optimization problem assigning berthing times and positions to vessels in container terminals. We introduce a novel mathematical formulation that extends the classical BAP...

Optimization of Water Allocation between Different Crops in Water Stress Conditions in Qazvin Irrigation Network

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Mehdi Mohammad khani

2017-06-01

Full Text Available Introduction: Evaluations show the necessity of using optimization models in order to determine optimal allocation of water in different water conditions. Its use can be proposed according to developed model abilities in this study in order to optimize water productivity and provide sustainable management and development of water resources over irrigation and drainage networks. Basic needs of the earth growing population and limitation of water and soil resources remindnecessity of optimal use of resources. World’s more than 280 million hectare lands are covered by irrigation networks (Khalkhali et al., 2006. The efficiency of most projects is between 30-50 percent and studies show that performance of most irrigation and drainage networks is not desirable and they have not achieved their aims. Hirich et al. (2014 Used deficit irrigation to improve crop water productivity of sweet corn, chickpea, faba bean and quinoa. For all crops, the highest water productivity and yield were obtained when deficit irrigation was applied during the vegetative growth stage. During the second season 2011 two cultivars of quinoa, faba bean and sweet corn have been cultivated applying 6 deficit irrigation treatments (rainfed, 0, 25, 50, 75 and 100% of full irrigation only during the vegetative growth stage, while in the rest of a crop cycle full irrigation was provided except for rainfed treatment. For quinoa and faba bean, treatment receiving 50% of the full irrigation during the vegetative growth stage recorded the highest yield and water productivity, while for sweet corn applying 75% of full irrigation was the optimal treatment in terms of yield and water productivity. Moghaddasi et al. (2010 worked examines and compares this approach with that based on the optimization method to manage agricultural water demand during drought to minimize damage. The results show that the optimization method resulted in 42% more income for the agricultural sector using the

Distributed Bees Algorithm Parameters Optimization for a Cost Efficient Target Allocation in Swarms of Robots

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Álvaro Gutiérrez

2011-11-01

Full Text Available Swarms of robots can use their sensing abilities to explore unknown environments and deploy on sites of interest. In this task, a large number of robots is more effective than a single unit because of their ability to quickly cover the area. However, the coordination of large teams of robots is not an easy problem, especially when the resources for the deployment are limited. In this paper, the Distributed Bees Algorithm (DBA, previously proposed by the authors, is optimized and applied to distributed target allocation in swarms of robots. Improved target allocation in terms of deployment cost efficiency is achieved through optimization of the DBA’s control parameters by means of a Genetic Algorithm. Experimental results show that with the optimized set of parameters, the deployment cost measured as the average distance traveled by the robots is reduced. The cost-efficient deployment is in some cases achieved at the expense of increased robots’ distribution error. Nevertheless, the proposed approach allows the swarm to adapt to the operating conditions when available resources are scarce.

Assessing the effects of adaptation measures on optimal water resources allocation under varied water availability conditions

Science.gov (United States)

Liu, Dedi; Guo, Shenglian; Shao, Quanxi; Liu, Pan; Xiong, Lihua; Wang, Le; Hong, Xingjun; Xu, Yao; Wang, Zhaoli

2018-01-01

Human activities and climate change have altered the spatial and temporal distribution of water availability which is a principal prerequisite for allocation of different water resources. In order to quantify the impacts of climate change and human activities on water availability and optimal allocation of water resources, hydrological models and optimal water resource allocation models should be integrated. Given that increasing human water demand and varying water availability conditions necessitate adaptation measures, we propose a framework to assess the effects of these measures on optimal allocation of water resources. The proposed model and framework were applied to a case study of the middle and lower reaches of the Hanjiang River Basin in China. Two representative concentration pathway (RCP) scenarios (RCP2.6 and RCP4.5) were employed to project future climate, and the Variable Infiltration Capacity (VIC) hydrological model was used to simulate the variability of flows under historical (1956-2011) and future (2012-2099) conditions. The water availability determined by simulating flow with the VIC hydrological model was used to establish the optimal water resources allocation model. The allocation results were derived under an extremely dry year (with an annual average water flow frequency of 95%), a very dry year (with an annual average water flow frequency of 90%), a dry year (with an annual average water flow frequency of 75%), and a normal year (with an annual average water flow frequency of 50%) during historical and future periods. The results show that the total available water resources in the study area and the inflow of the Danjiangkou Reservoir will increase in the future. However, the uneven distribution of water availability will cause water shortage problems, especially in the boundary areas. The effects of adaptation measures, including water saving, and dynamic control of flood limiting water levels (FLWLs) for reservoir operation, were

A Location-Allocation Model for Seaport-Dry Port System Optimization

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Xuejun Feng

2013-01-01

Full Text Available Seaports participate in hinterland economic development through partnerships with dry ports, and the combined seaport-dry port network serves as the backbone of regional logistics. This paper constructs a location-allocation model for the regional seaport-dry port network optimization problem and develops a greedy algorithm and a genetic algorithm to obtain its solution. This model is applicable to situations under which the geographic distribution of demand is known. A case study involving configuration of dry ports near the west bank of the Taiwan Strait is conducted, and the model is successfully applied.

OPTIM, Minimization of Band-Width of Finite Elements Problems

International Nuclear Information System (INIS)

Huart, M.

1977-01-01

1 - Nature of the physical problem solved: To minimize the band-width of finite element problems. 2 - Method of solution: A surface is constructed from the x-y-coordinates of each node using its node number as z-value. This surface consists of triangles. Nodes are renumbered in such a way as to minimize the surface area. 3 - Restrictions on the complexity of the problem: This program is applicable to 2-D problems. It is dimensioned for a maximum of 1000 elements

Fluid limits for bandwidth-sharing networks with rate constraints

NARCIS (Netherlands)

M. Frolkova (Masha); J. Reed (Josh); A.P. Zwart (Bert)

2013-01-01

htmlabstractBandwidth-sharing networks as introduced by Massouli\\'e~\\& Roberts (1998) model the dynamic interaction among an evolving population of elastic flows competing for several links. With policies based on optimization procedures, such models are of interest both from a~Queueing Theory and

Optimal allocation of thermodynamic irreversibility for the integrated design of propulsion and thermal management systems

Science.gov (United States)

Maser, Adam Charles

work losses over the time history of the mission. The characterization of the thermodynamic irreversibility distribution helps give the propulsion systems designer an absolute and consistent view of the tradeoffs associated with the design of the entire integrated system. Consequently, this leads directly to the question of the proper allocation of irreversibility across each of the components. The process of searching for the most favorable allocation of this irreversibility is the central theme of the research and must take into account production cost and vehicle mission performance. The production cost element is accomplished by including an engine component weight and cost prediction capability within the system model. The vehicle mission performance is obtained by directly linking the propulsion and thermal management model to a vehicle performance model and flying it through a mission profile. A canonical propulsion and thermal management systems architecture is then presented to experimentally test each element of the methodology separately: first the integrated modeling and simulation, then the irreversibility, cost, and mission performance considerations, and then finally the proper technique to perform the optimal allocation. A goal of this research is the description of the optimal allocation of system irreversibility to enable an engine cycle design with improved performance and cost at the vehicle-level. To do this, a numerical optimization was first used to minimize system-level production and operating costs by fixing the performance requirements and identifying the best settings for all of the design variables. There are two major drawbacks to this approach: It does not allow the designer to directly trade off the performance requirements and it does not allow the individual component losses to directly factor into the optimization. An irreversibility allocation approach based on the economic concept of resource allocation is then compared to the

Multiobjective optimal allocation problem with probabilistic non ...

African Journals Online (AJOL)

user

In multivariate stratified sampling where more than one characteristic are to be estimated, an allocation which is optimum for one characteristic may not be optimum for other characteristics also. In such situations a compromise criterion is needed to work out a usable allocation which is optimum for all characteristics in some ...

Wireless visual sensor network resource allocation using cross-layer optimization

Science.gov (United States)

Bentley, Elizabeth S.; Matyjas, John D.; Medley, Michael J.; Kondi, Lisimachos P.

2009-01-01

In this paper, we propose an approach to manage network resources for a Direct Sequence Code Division Multiple Access (DS-CDMA) visual sensor network where nodes monitor scenes with varying levels of motion. It uses cross-layer optimization across the physical layer, the link layer and the application layer. Our technique simultaneously assigns a source coding rate, a channel coding rate, and a power level to all nodes in the network based on one of two criteria that maximize the quality of video of the entire network as a whole, subject to a constraint on the total chip rate. One criterion results in the minimal average end-to-end distortion amongst all nodes, while the other criterion minimizes the maximum distortion of the network. Our approach allows one to determine the capacity of the visual sensor network based on the number of nodes and the quality of video that must be transmitted. For bandwidth-limited applications, one can also determine the minimum bandwidth needed to accommodate a number of nodes with a specific target chip rate. Video captured by a sensor node camera is encoded and decoded using the H.264 video codec by a centralized control unit at the network layer. To reduce the computational complexity of the solution, Universal Rate-Distortion Characteristics (URDCs) are obtained experimentally to relate bit error probabilities to the distortion of corrupted video. Bit error rates are found first by using Viterbi's upper bounds on the bit error probability and second, by simulating nodes transmitting data spread by Total Square Correlation (TSC) codes over a Rayleigh-faded DS-CDMA channel and receiving that data using Auxiliary Vector (AV) filtering.

Test scheduling optimization for 3D network-on-chip based on cloud evolutionary algorithm of Pareto multi-objective

Science.gov (United States)

Xu, Chuanpei; Niu, Junhao; Ling, Jing; Wang, Suyan

2018-03-01

In this paper, we present a parallel test strategy for bandwidth division multiplexing under the test access mechanism bandwidth constraint. The Pareto solution set is combined with a cloud evolutionary algorithm to optimize the test time and power consumption of a three-dimensional network-on-chip (3D NoC). In the proposed method, all individuals in the population are sorted in non-dominated order and allocated to the corresponding level. Individuals with extreme and similar characteristics are then removed. To increase the diversity of the population and prevent the algorithm from becoming stuck around local optima, a competition strategy is designed for the individuals. Finally, we adopt an elite reservation strategy and update the individuals according to the cloud model. Experimental results show that the proposed algorithm converges to the optimal Pareto solution set rapidly and accurately. This not only obtains the shortest test time, but also optimizes the power consumption of the 3D NoC.

Holding-time-aware asymmetric spectrum allocation in virtual optical networks

Science.gov (United States)

Lyu, Chunjian; Li, Hui; Liu, Yuze; Ji, Yuefeng

2017-10-01

Virtual optical networks (VONs) have been considered as a promising solution to support current high-capacity dynamic traffic and achieve rapid applications deployment. Since most of the network services (e.g., high-definition video service, cloud computing, distributed storage) in VONs are provisioned by dedicated data centers, needing different amount of bandwidth resources in both directions, the network traffic is mostly asymmetric. The common strategy, symmetric provisioning of traffic in optical networks, leads to a waste of spectrum resources in such traffic patterns. In this paper, we design a holding-time-aware asymmetric spectrum allocation module based on SDON architecture and an asymmetric spectrum allocation algorithm based on the module is proposed. For the purpose of reducing spectrum resources' waste, the algorithm attempts to reallocate the idle unidirectional spectrum slots in VONs, which are generated due to the asymmetry of services' bidirectional bandwidth. This part of resources can be exploited by other requests, such as short-time non-VON requests. We also introduce a two-dimensional asymmetric resource model for maintaining idle spectrum resources information of VON in spectrum and time domains. Moreover, a simulation is designed to evaluate the performance of the proposed algorithm, and results show that our proposed asymmetric spectrum allocation algorithm can improve the resource waste and reduce blocking probability.

Optimal Capacity Allocation of Large-Scale Wind-PV-Battery Units

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Kehe Wu

2014-01-01

Full Text Available An optimal capacity allocation of large-scale wind-photovoltaic- (PV- battery units was proposed. First, an output power model was established according to meteorological conditions. Then, a wind-PV-battery unit was connected to the power grid as a power-generation unit with a rated capacity under a fixed coordinated operation strategy. Second, the utilization rate of renewable energy sources and maximum wind-PV complementation was considered and the objective function of full life cycle-net present cost (NPC was calculated through hybrid iteration/adaptive hybrid genetic algorithm (HIAGA. The optimal capacity ratio among wind generator, PV array, and battery device also was calculated simultaneously. A simulation was conducted based on the wind-PV-battery unit in Zhangbei, China. Results showed that a wind-PV-battery unit could effectively minimize the NPC of power-generation units under a stable grid-connected operation. Finally, the sensitivity analysis of the wind-PV-battery unit demonstrated that the optimization result was closely related to potential wind-solar resources and government support. Regions with rich wind resources and a reasonable government energy policy could improve the economic efficiency of their power-generation units.

Gain-switched all-fiber laser with narrow bandwidth

DEFF Research Database (Denmark)

Larsen, Casper; Giesberts, M.; Nyga, S.

2013-01-01

pulse energy is 20 μJ in a duration of 135 ns at 7 kHz. The bandwidth increases for a higher pump pulse energy and repetition rate, and this sets the limit of the output pulse energy. A single power amplifier is added to raise the peak power to the kW-level and the pulse energy to 230 μJ while keeping......Gain-switching of a CW fiber laser is a simple and cost-effective approach to generate pulses using an all-fiber system. We report on the construction of a narrow bandwidth (below 0.1 nm) gain-switched fiber laser and optimize the pulse energy and pulse duration under this constraint. The extracted...

A probabilistic approach for optimal sensor allocation in structural health monitoring

International Nuclear Information System (INIS)

Azarbayejani, M; Reda Taha, M M; El-Osery, A I; Choi, K K

2008-01-01

Recent advances in sensor technology promote using large sensor networks to efficiently and economically monitor, identify and quantify damage in structures. In structural health monitoring (SHM) systems, the effectiveness and reliability of the sensor network are crucial to determine the optimal number and locations of sensors in SHM systems. Here, we suggest a probabilistic approach for identifying the optimal number and locations of sensors for SHM. We demonstrate a methodology to establish the probability distribution function that identifies the optimal sensor locations such that damage detection is enhanced. The approach is based on using the weights of a neural network trained from simulations using a priori knowledge about damage locations and damage severities to generate a normalized probability distribution function for optimal sensor allocation. We also demonstrate that the optimal sensor network can be related to the highest probability of detection (POD). The redundancy of the proposed sensor network is examined using a 'leave one sensor out' analysis. A prestressed concrete bridge is selected as a case study to demonstrate the effectiveness of the proposed method. The results show that the proposed approach can provide a robust design for sensor networks that are more efficient than a uniform distribution of sensors on a structure

Application of the hybrid Big Bang-Big Crunch algorithm to optimal reconfiguration and distributed generation power allocation in distribution systems

International Nuclear Information System (INIS)

Sedighizadeh, Mostafa; Esmaili, Masoud; Esmaeili, Mobin

2014-01-01

In this paper, a multi-objective framework is proposed for simultaneous optimal network reconfiguration and DG (distributed generation) power allocation. The proposed method encompasses objective functions of power losses, voltage stability, DG cost, and greenhouse gas emissions and it is optimized subject to power system operational and technical constraints. In order to solve the optimization problem, the HBB-BC (Hybrid Big Bang-Big Crunch) algorithm as one of the most recent heuristic tools is modified and employed here by introducing a mutation operator to enhance its exploration capability. To resolve the scaling problem of differently-scaled objective functions, a fuzzy membership is used to bring them into a same scale and then, the fuzzy fitness of the final objective function is utilized to measure the satisfaction level of the obtained solution. The proposed method is tested on balanced and unbalanced test systems and its results are comprehensively compared with previous methods considering different scenarios. According to results, the proposed method not only offers an enhanced exploration capability but also has a better converge rate compared with previous methods. In addition, the simultaneous network reconfiguration and DG power allocation leads to a more optimal result than separately doing tasks of reconfiguration and DG power allocation. - Highlights: • Hybrid Big Bang-Big Crunch algorithm is applied to network reconfiguration problem. • Joint reconfiguration and DG power allocation leads to a more optimal solution. • A mutation operator is used to improve the exploration capability of HBB-BC method. • The HBB-BC has a better convergence rate than the compared algorithms

Optimizing Real-Time Vaccine Allocation in a Stochastic SIR Model.

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Chantal Nguyen

Full Text Available Real-time vaccination following an outbreak can effectively mitigate the damage caused by an infectious disease. However, in many cases, available resources are insufficient to vaccinate the entire at-risk population, logistics result in delayed vaccine deployment, and the interaction between members of different cities facilitates a wide spatial spread of infection. Limited vaccine, time delays, and interaction (or coupling of cities lead to tradeoffs that impact the overall magnitude of the epidemic. These tradeoffs mandate investigation of optimal strategies that minimize the severity of the epidemic by prioritizing allocation of vaccine to specific subpopulations. We use an SIR model to describe the disease dynamics of an epidemic which breaks out in one city and spreads to another. We solve a master equation to determine the resulting probability distribution of the final epidemic size. We then identify tradeoffs between vaccine, time delay, and coupling, and we determine the optimal vaccination protocols resulting from these tradeoffs.

Bandwidth efficient coding

CERN Document Server

Anderson, John B

2017-01-01

Bandwidth Efficient Coding addresses the major challenge in communication engineering today: how to communicate more bits of information in the same radio spectrum. Energy and bandwidth are needed to transmit bits, and bandwidth affects capacity the most. Methods have been developed that are ten times as energy efficient at a given bandwidth consumption as simple methods. These employ signals with very complex patterns and are called "coding" solutions. The book begins with classical theory before introducing new techniques that combine older methods of error correction coding and radio transmission in order to create narrowband methods that are as efficient in both spectrum and energy as nature allows. Other topics covered include modulation techniques such as CPM, coded QAM and pulse design.

Allocating HIV prevention funds in the United States: recommendations from an optimization model.

Directory of Open Access Journals (Sweden)

Arielle Lasry

Full Text Available The Centers for Disease Control and Prevention (CDC had an annual budget of approximately $327 million to fund health departments and community-based organizations for core HIV testing and prevention programs domestically between 2001 and 2006. Annual HIV incidence has been relatively stable since the year 2000 and was estimated at 48,600 cases in 2006 and 48,100 in 2009. Using estimates on HIV incidence, prevalence, prevention program costs and benefits, and current spending, we created an HIV resource allocation model that can generate a mathematically optimal allocation of the Division of HIV/AIDS Prevention's extramural budget for HIV testing, and counseling and education programs. The model's data inputs and methods were reviewed by subject matter experts internal and external to the CDC via an extensive validation process. The model projects the HIV epidemic for the United States under different allocation strategies under a fixed budget. Our objective is to support national HIV prevention planning efforts and inform the decision-making process for HIV resource allocation. Model results can be summarized into three main recommendations. First, more funds should be allocated to testing and these should further target men who have sex with men and injecting drug users. Second, counseling and education interventions ought to provide a greater focus on HIV positive persons who are aware of their status. And lastly, interventions should target those at high risk for transmitting or acquiring HIV, rather than lower-risk members of the general population. The main conclusions of the HIV resource allocation model have played a role in the introduction of new programs and provide valuable guidance to target resources and improve the impact of HIV prevention efforts in the United States.

A simulation-based optimization approach for free distributed repairable multi-state availability-redundancy allocation problems

International Nuclear Information System (INIS)

Attar, Ahmad; Raissi, Sadigh; Khalili-Damghani, Kaveh

2017-01-01

A simulation-based optimization (SBO) method is proposed to handle multi-objective joint availability-redundancy allocation problem (JARAP). Here, there is no emphasis on probability distributions of time to failures and repair times for multi-state multi-component series-parallel configuration under active, cold and hot standby strategies. Under such conditions, estimation of availability is not a trivial task. First, an efficient computer simulation model is proposed to estimate the availability of the aforementioned system. Then, the estimated availability values are used in a repetitive manner as parameter of a two-objective joint availability-redundancy allocation optimization model through SBO mechanism. The optimization model is then solved using two well-known multi-objective evolutionary computation algorithms, i.e., non-dominated sorting genetic algorithm (NSGA-II), and Strength Pareto Evolutionary Algorithm (SPEA2). The proposed SBO approach is tested using non-exponential numerical example with multi-state repairable components. The results are presented and discussed through different demand scenarios under cold and hot standby strategies. Furthermore, performance of NSGA-II and SPEA2 are statistically compared regarding multi-objective accuracy, and diversity metrics. - Highlights: • A Simulation-Based Optimization (SBO) procedure is introduced for JARAP. • The proposed SBO works for any given failure and repair times. • An efficient simulation procedure is developed to estimate availability. • Customized NSGA-II and SPEA2 are proposed to solve the bi-objective JARAP. • Statistical analysis is employed to test the performance of optimization methods.

An Optimization Waste Load Allocation Model in River Systems

Science.gov (United States)

Amirpoor Daylami, A.; jarihani, A. A.; Aminisola, K.

2012-04-01

In many river systems, increasing of the waste discharge leads to increasing pollution of these water bodies. While the capacity of the river flow for pollution acceptance is limited and the ability of river to clean itself is restricted, the dischargers have to release their waste into the river after a primary pollution treatment process. Waste Load Allocation as a well-known water quality control strategy is used to determine the optimal pollutant removal at a number of point sources along the river. This paper aim at developing a new approach for treatment and management of wastewater inputs into the river systems, such that water quality standards in these receiving waters are met. In this study, inspired by the fact that cooperation among some single point source waste dischargers can lead to a more waste acceptance capacity and/or more optimum quality control in a river, an efficient approach was implemented to determine both primary waste water treatment levels and/or the best releasing points of the waste into the river. In this methodology, a genetic algorithm is used as an optimization tool to calculate optimal fraction removal levels of each one of single or shared discharger. Besides, a sub-model embedded to optimization model was used to simulate water quality of the river in each one of discharging scenarios based on the modified Streeter and Phelps quality equations. The practical application of the model is illustrated with a case study of the Gharesoo river system in west of Iran.

Energy-Efficient Optimal Power Allocation in Integrated Wireless Sensor and Cognitive Satellite Terrestrial Networks.

Science.gov (United States)

Shi, Shengchao; Li, Guangxia; An, Kang; Gao, Bin; Zheng, Gan

2017-09-04

This paper proposes novel satellite-based wireless sensor networks (WSNs), which integrate the WSN with the cognitive satellite terrestrial network. Having the ability to provide seamless network access and alleviate the spectrum scarcity, cognitive satellite terrestrial networks are considered as a promising candidate for future wireless networks with emerging requirements of ubiquitous broadband applications and increasing demand for spectral resources. With the emerging environmental and energy cost concerns in communication systems, explicit concerns on energy efficient resource allocation in satellite networks have also recently received considerable attention. In this regard, this paper proposes energy-efficient optimal power allocation schemes in the cognitive satellite terrestrial networks for non-real-time and real-time applications, respectively, which maximize the energy efficiency (EE) of the cognitive satellite user while guaranteeing the interference at the primary terrestrial user below an acceptable level. Specifically, average interference power (AIP) constraint is employed to protect the communication quality of the primary terrestrial user while average transmit power (ATP) or peak transmit power (PTP) constraint is adopted to regulate the transmit power of the satellite user. Since the energy-efficient power allocation optimization problem belongs to the nonlinear concave fractional programming problem, we solve it by combining Dinkelbach's method with Lagrange duality method. Simulation results demonstrate that the fading severity of the terrestrial interference link is favorable to the satellite user who can achieve EE gain under the ATP constraint comparing to the PTP constraint.

An Optimal Allocation Model of Public Transit Mode Proportion for the Low-Carbon Transportation

Directory of Open Access Journals (Sweden)

Linjun Lu

2015-01-01

Full Text Available Public transit has been widely recognized as a potential way to develop low-carbon transportation. In this paper, an optimal allocation model of public transit mode proportion (MPMP has been built to achieve the low-carbon public transit. Optimal ratios of passenger traffic for rail, bus, and taxi are derived by running the model using typical data. With different values of traffic demand, construction cost, travel time, and accessibilities, MPMP can generate corresponding optimal ratios, benefiting decision impacts analysis and decision makers. Instead of considering public transit as a united system, it is separated into units in this paper. And Shanghai is used to test model validity and practicality.

Spin-torque diode with tunable sensitivity and bandwidth by out-of-plane magnetic field

Energy Technology Data Exchange (ETDEWEB)

Li, X.; Zheng, C.; Pong, Philip W. T. [Department of Electrical and Electronic Engineering, The University of Hong Kong (Hong Kong); Zhou, Y., E-mail: yanzhou@hku.hk [School of Electronics Science and Engineering, Nanjing University, Nanjing 210093 (China); Department of Physics, The University of Hong Kong (Hong Kong); Kubota, H.; Yuasa, S. [Spintronics Research Center, National Institute of Advanced Industrial Science and Technology, Tsukuba, Ibaraki 305-8568 (Japan)

2016-06-06

Spin-torque diodes based on nanosized magnetic tunnel junctions are novel microwave detectors with high sensitivity and wide frequency bandwidth. While previous reports mainly focus on improving the sensitivity, the approaches to extend the bandwidth are limited. This work experimentally demonstrates that through optimizing the orientation of the external magnetic field, wide bandwidth can be achieved while maintaining high sensitivity. The mechanism of the frequency- and sensitivity-tuning is investigated through analyzing the dependence of resonant frequency and DC voltage on the magnitude and the tilt angle of hard-plane magnetic field. The frequency dependence is qualitatively explicated by Kittel's ferromagnetic resonance model. The asymmetric resonant frequency at positive and negative magnetic field is verified by the numerical simulation considering the in-plane anisotropy. The DC voltage dependence is interpreted through evaluating the misalignment angle between the magnetization of the free layer and the reference layer. The tunability of the detector performance by the magnetic field angle is evaluated through characterizing the sensitivity and bandwidth under 3D magnetic field. The frequency bandwidth up to 9.8 GHz or maximum sensitivity up to 154 mV/mW (after impedance mismatch correction) can be achieved by tuning the angle of the applied magnetic field. The results show that the bandwidth and sensitivity can be controlled and adjusted through optimizing the orientation of the magnetic field for various applications and requirements.

Optimization Model for cooperative water allocation and valuation in large river basins regarding environmental constraints

Science.gov (United States)

Pournazeri, S.

2011-12-01

A comprehensive optimization model named Cooperative Water Allocation Model (CWAM) is developed for equitable and efficient water allocation and valuation of Zab river basin in order to solve the draught problems of Orumieh Lake in North West of Iran. The model's methodology consists of three phases. The first represents an initial water rights allocation among competing users. The second comprises the water reallocation process for complete usage by consumers. The third phase performs an allocation of the net benefit of the stakeholders participating in a coalition by applying cooperative game theory. The environmental constraints are accounted for in the water allocation model by entering probable environmental damage in a target function, and inputting the minimum water requirement of users. The potential of underground water usage is evaluated in order to compensate for the variation in the amount of surface water. This is conducted by applying an integrated economic- hydrologic river basin model. A node-link river basin network is utilized in CWAM which consists of two major blocks. The first indicates the internal water rights allocation and the second is associated to water and net benefit reallocation. System control, loss in links by evaporation or seepage, modification of inflow into the node, loss in nodes and loss in outflow are considered in this model. Water valuation is calculated for environmental, industrial, municipal and agricultural usage by net benefit function. It can be seen that the water rights are allocated efficiently and incomes are distributed appropriately based on quality and quantity limitations.

A particle-based simplified swarm optimization algorithm for reliability redundancy allocation problems

International Nuclear Information System (INIS)

Huang, Chia-Ling

2015-01-01

This paper proposes a new swarm intelligence method known as the Particle-based Simplified Swarm Optimization (PSSO) algorithm while undertaking a modification of the Updating Mechanism (UM), called N-UM and R-UM, and simultaneously applying an Orthogonal Array Test (OA) to solve reliability–redundancy allocation problems (RRAPs) successfully. One difficulty of RRAP is the need to maximize system reliability in cases where the number of redundant components and the reliability of corresponding components in each subsystem are simultaneously decided with nonlinear constraints. In this paper, four RRAP benchmarks are used to display the applicability of the proposed PSSO that advances the strengths of both PSO and SSO to enable optimizing the RRAP that belongs to mixed-integer nonlinear programming. When the computational results are compared with those of previously developed algorithms in existing literature, the findings indicate that the proposed PSSO is highly competitive and performs well. - Highlights: • This paper proposes a particle-based simplified swarm optimization algorithm (PSSO) to optimize RRAP. • Furthermore, the UM and an OA are adapted to advance in optimizing RRAP. • Four systems are introduced and the results demonstrate the PSSO performs particularly well

Design and Profit Allocation in Two-Echelon Heterogeneous Cooperative Logistics Network Optimization

Directory of Open Access Journals (Sweden)

Yong Wang

2018-01-01

Full Text Available In modern supply chain, logistics companies usually operate individually and optimization researches often concentrate on solving problems related to separate networks. Consequences like the complexity of urban transportation networks and long distance deliveries or pickups and pollution are leading problems to more expenses and more complaints from environment protection organizations. A solution approach to these issues is proposed in this article and consists in the adoption of two-echelon heterogeneous cooperative logistics networks (THCLN. The optimization methodology includes the formation of cooperative coalitions, the reallocation of customers to appropriate logistics facilities, and the determination of the best profit allocation scheme. First, a mixed integer linear programing model is introduced to minimize the total operating cost of nonempty coalitions. Thus, the Genetic Algorithm (GA and the Particle Swarm Optimization (PSO algorithm are hybridized to propose GA-PSO heuristics. GA-PSO is employed to provide good solutions to customer clustering units’ reallocation problem. In addition, a negotiation process is established based on logistics centers as coordinators. The case study of Chongqing city is conducted to verify the feasibility of THCLN in practice. The grand coalition and two heterogeneous subcoalitions are designed, and the collective profit is distributed based on cooperative game theory. The Minimum Cost Remaining Savings (MCRS model is used to determine good allocation schemes and strictly monotonic path principles are considered to evaluate and decide the most appropriate coalition sequence. Comparisons proved the combination of GA-PSO and MCRS better as results are found closest to the core center. Therefore, the proposed approach can be implemented in real world environment, increase the reliability of urban logistics network, and allow decision makers to improve service efficiency.

Optimizing Bandwidth Limited Problems Using One-SidedCommunication and Overlap

Energy Technology Data Exchange (ETDEWEB)

Bell, Christian; Bonachea, Dan; Nishtala, Rajesh; Yelick, Katherine

2005-10-14

Partitioned Global Address Space languages like Unified Parallel C (UPC) are typically valued for their expressiveness, especially for computations with fine-grained random accesses. In this paper we show that the one-sided communication model used in these languages also has a significant performance advantage for bandwidth-limited applications. We demonstrate this benefit through communication microbenchmarks and a case-study that compares UPC and MPI implementations of the NAS Fourier Transform (FT) benchmark. Our optimizations rely on aggressively overlapping communication with computation but spreading communication events throughout the course of the local computation. This alleviates the potential communication bottleneck that occurs when the communication is packed into a single phase (e.g., the large all-to-all in a multidimensional FFT). Even though the new algorithms require more messages for the same total volume of data, the resulting overlap leads to speedups of over 1.75x and 1.9x for the two-sided and one-sided implementations, respectively, when compared to the default NAS Fortran/MPI release. Our best one-sided implementations show an average improvement of 15 percent over our best two-sided implementations. We attribute this difference to the lower software overhead of one-sided communication, which is partly fundamental to the semantic difference between one-sided and two-sided communication. Our UPC results use the Berkeley UPC compiler with the GASNet communication system, and demonstrate the portability and scalability of that language and implementation, with performance approaching 0.5TFlop/s on the FT benchmark running on 512 processors.

Coarse-Grain Bandwidth Estimation Scheme for Large-Scale Network

Science.gov (United States)

Cheung, Kar-Ming; Jennings, Esther H.; Sergui, John S.

2013-01-01

A large-scale network that supports a large number of users can have an aggregate data rate of hundreds of Mbps at any time. High-fidelity simulation of a large-scale network might be too complicated and memory-intensive for typical commercial-off-the-shelf (COTS) tools. Unlike a large commercial wide-area-network (WAN) that shares diverse network resources among diverse users and has a complex topology that requires routing mechanism and flow control, the ground communication links of a space network operate under the assumption of a guaranteed dedicated bandwidth allocation between specific sparse endpoints in a star-like topology. This work solved the network design problem of estimating the bandwidths of a ground network architecture option that offer different service classes to meet the latency requirements of different user data types. In this work, a top-down analysis and simulation approach was created to size the bandwidths of a store-and-forward network for a given network topology, a mission traffic scenario, and a set of data types with different latency requirements. These techniques were used to estimate the WAN bandwidths of the ground links for different architecture options of the proposed Integrated Space Communication and Navigation (SCaN) Network. A new analytical approach, called the "leveling scheme," was developed to model the store-and-forward mechanism of the network data flow. The term "leveling" refers to the spreading of data across a longer time horizon without violating the corresponding latency requirement of the data type. Two versions of the leveling scheme were developed: 1. A straightforward version that simply spreads the data of each data type across the time horizon and doesn't take into account the interactions among data types within a pass, or between data types across overlapping passes at a network node, and is inherently sub-optimal. 2. Two-state Markov leveling scheme that takes into account the second order behavior of

Raman scheme for adjustable-bandwidth quantum memory

International Nuclear Information System (INIS)

Le Goueet, J.-L.; Berman, P. R.

2009-01-01

We propose a scenario of quantum memory for light based on Raman scattering. The storage medium is a vapor and the different spectral components of the input pulse are stored in different atomic velocity classes. One uses appropriate pulses to reverse the resulting Doppler phase shift and to regenerate the input pulse, without distortion, in the backward direction. The different stages of the protocol are detailed and the recovery efficiency is calculated in the semiclassical picture. Since the memory bandwidth is determined by the Raman transition Doppler width, it can be adjusted by changing the angle between the input pulse wave vector and the control beams. The optical depth also depends on the beam angle. As a consequence the available optical depth can be optimized depending on the needed bandwidth. The predicted recovery efficiency is close to 100% for large optical depth.

Bandwidth trading under misaligned objectives: decentralized measurement-based control

NARCIS (Netherlands)

M.R.H. Mandjes (Michel); M. Ramakrishnan

2006-01-01

htmlabstractThis paper studies the interplay between a profit-maximizing network and a number of users competing for the finite bandwidth on each link. In our setting, the objectives of the network and the users are ‘misaligned’, in that the prices that optimize the network’s profit do not maximize

Bandwidth trading under misaligned objectives: decentralized measurement-based control

NARCIS (Netherlands)

Mandjes, M.R.H.; Ramakrishnan, M.

2008-01-01

This paper studies the interplay between a profit-maximizing network and a number of users competing for the finite bandwidth on each link. In our setting, the objectives of the network and the users are ‘misaligned’, in that the prices that optimize the network’s profit do not maximize the

Optimal Waste Load Allocation Using Multi-Objective Optimization and Multi-Criteria Decision Analysis

Directory of Open Access Journals (Sweden)

L. Saberi

2016-10-01

Full Text Available Introduction: Increasing demand for water, depletion of resources of acceptable quality, and excessive water pollution due to agricultural and industrial developments has caused intensive social and environmental problems all over the world. Given the environmental importance of rivers, complexity and extent of pollution factors and physical, chemical and biological processes in these systems, optimal waste-load allocation in river systems has been given considerable attention in the literature in the past decades. The overall objective of planning and quality management of river systems is to develop and implement a coordinated set of strategies and policies to reduce or allocate of pollution entering the rivers so that the water quality matches by proposing environmental standards with an acceptable reliability. In such matters, often there are several different decision makers with different utilities which lead to conflicts. Methods/Materials: In this research, a conflict resolution framework for optimal waste load allocation in river systems is proposed, considering the total treatment cost and the Biological Oxygen Demand (BOD violation characteristics. There are two decision-makers inclusive waste load discharges coalition and environmentalists who have conflicting objectives. This framework consists of an embedded river water quality simulator, which simulates the transport process including reaction kinetics. The trade-off curve between objectives is obtained using the Multi-objective Particle Swarm Optimization Algorithm which these objectives are minimization of the total cost of treatment and penalties that must be paid by discharges and a violation of water quality standards considering BOD parameter which is controlled by environmentalists. Thus, the basic policy of river’s water quality management is formulated in such a way that the decision-makers are ensured their benefits will be provided as far as possible. By using MOPSO

Bandwidth-limited control and ringdown suppression in high-Q resonators.

Science.gov (United States)

Borneman, Troy W; Cory, David G

2012-12-01

We describe how the transient behavior of a tuned and matched resonator circuit and a ringdown suppression pulse may be integrated into an optimal control theory (OCT) pulse-design algorithm to derive control sequences with limited ringdown that perform a desired quantum operation in the presence of resonator distortions of the ideal waveform. Inclusion of ringdown suppression in numerical pulse optimizations significantly reduces spectrometer deadtime when using high quality factor (high-Q) resonators, leading to increased signal-to-noise ratio (SNR) and sensitivity of inductive measurements. To demonstrate the method, we experimentally measure the free-induction decay of an inhomogeneously broadened solid-state free radical spin system at high Q. The measurement is enabled by using a numerically optimized bandwidth-limited OCT pulse, including ringdown suppression, robust to variations in static and microwave field strengths. We also discuss the applications of pulse design in high-Q resonators to universal control of anisotropic-hyperfine coupled electron-nuclear spin systems via electron-only modulation even when the bandwidth of the resonator is significantly smaller than the hyperfine coupling strength. These results demonstrate how limitations imposed by linear response theory may be vastly exceeded when using a sufficiently accurate system model to optimize pulses of high complexity. Copyright © 2012 Elsevier Inc. All rights reserved.

Network Bandwidth Utilization Forecast Model on High Bandwidth Network

Energy Technology Data Exchange (ETDEWEB)

Yoo, Wucherl; Sim, Alex

2014-07-07

With the increasing number of geographically distributed scientific collaborations and the scale of the data size growth, it has become more challenging for users to achieve the best possible network performance on a shared network. We have developed a forecast model to predict expected bandwidth utilization for high-bandwidth wide area network. The forecast model can improve the efficiency of resource utilization and scheduling data movements on high-bandwidth network to accommodate ever increasing data volume for large-scale scientific data applications. Univariate model is developed with STL and ARIMA on SNMP path utilization data. Compared with traditional approach such as Box-Jenkins methodology, our forecast model reduces computation time by 83.2percent. It also shows resilience against abrupt network usage change. The accuracy of the forecast model is within the standard deviation of the monitored measurements.

Network bandwidth utilization forecast model on high bandwidth networks

Energy Technology Data Exchange (ETDEWEB)

Yoo, Wuchert (William) [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Sim, Alex [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

2015-03-30

With the increasing number of geographically distributed scientific collaborations and the scale of the data size growth, it has become more challenging for users to achieve the best possible network performance on a shared network. We have developed a forecast model to predict expected bandwidth utilization for high-bandwidth wide area network. The forecast model can improve the efficiency of resource utilization and scheduling data movements on high-bandwidth network to accommodate ever increasing data volume for large-scale scientific data applications. Univariate model is developed with STL and ARIMA on SNMP path utilization data. Compared with traditional approach such as Box-Jenkins methodology, our forecast model reduces computation time by 83.2%. It also shows resilience against abrupt network usage change. The accuracy of the forecast model is within the standard deviation of the monitored measurements.

Optimal Allocation of Static Var Compensator via Mixed Integer Conic Programming

Energy Technology Data Exchange (ETDEWEB)

Zhang, Xiaohu [ORNL; Shi, Di [Global Energy Interconnection Research Institute North America (GEIRI North America), California; Wang, Zhiwei [Global Energy Interconnection Research Institute North America (GEIRI North America), California; Huang, Junhui [Global Energy Interconnection Research Institute North America (GEIRI North America), California; Wang, Xu [Global Energy Interconnection Research Institute North America (GEIRI North America), California; Liu, Guodong [ORNL; Tomsovic, Kevin [University of Tennessee, Knoxville (UTK)

2017-01-01

Shunt FACTS devices, such as, a Static Var Compensator (SVC), are capable of providing local reactive power compensation. They are widely used in the network to reduce the real power loss and improve the voltage profile. This paper proposes a planning model based on mixed integer conic programming (MICP) to optimally allocate SVCs in the transmission network considering load uncertainty. The load uncertainties are represented by a number of scenarios. Reformulation and linearization techniques are utilized to transform the original non-convex model into a convex second order cone programming (SOCP) model. Numerical case studies based on the IEEE 30-bus system demonstrate the effectiveness of the proposed planning model.

Two-Stage Multiobjective Optimization for Emergency Supplies Allocation Problem under Integrated Uncertainty

Directory of Open Access Journals (Sweden)

Xuejie Bai

2016-01-01

Full Text Available This paper proposes a new two-stage optimization method for emergency supplies allocation problem with multisupplier, multiaffected area, multirelief, and multivehicle. The triplet of supply, demand, and the availability of path is unknown prior to the extraordinary event and is descriptive with fuzzy random variable. Considering the fairness, timeliness, and economical efficiency, a multiobjective expected value model is built for facility location, vehicle routing, and supply allocation decisions. The goals of proposed model aim to minimize the proportion of demand nonsatisfied and response time of emergency reliefs and the total cost of the whole process. When the demand and the availability of path are discrete, the expected values in the objective functions are converted into their equivalent forms. When the supply amount is continuous, the equilibrium chance in the constraint is transformed to its equivalent one. To overcome the computational difficulty caused by multiple objectives, a goal programming model is formulated to obtain a compromise solution. Finally, an example is presented to illustrate the validity of the proposed model and the effectiveness of the solution method.

Software defined multi-OLT passive optical network for flexible traffic allocation

Science.gov (United States)

Zhang, Shizong; Gu, Rentao; Ji, Yuefeng; Zhang, Jiawei; Li, Hui

2016-10-01

With the rapid growth of 4G mobile network and vehicular network services mobile terminal users have increasing demand on data sharing among different radio remote units (RRUs) and roadside units (RSUs). Meanwhile, commercial video-streaming, video/voice conference applications delivered through peer-to-peer (P2P) technology are still keep on stimulating the sharp increment of bandwidth demand in both business and residential subscribers. However, a significant issue is that, although wavelength division multiplexing (WDM) and orthogonal frequency division multiplexing (OFDM) technology have been proposed to fulfil the ever-increasing bandwidth demand in access network, the bandwidth of optical fiber is not unlimited due to the restriction of optical component properties and modulation/demodulation technology, and blindly increase the wavelength cannot meet the cost-sensitive characteristic of the access network. In this paper, we propose a software defined multi-OLT PON architecture to support efficient scheduling of access network traffic. By introducing software defined networking technology and wavelength selective switch into TWDM PON system in central office, multiple OLTs can be considered as a bandwidth resource pool and support flexible traffic allocation for optical network units (ONUs). Moreover, under the configuration of the control plane, ONUs have the capability of changing affiliation between different OLTs under different traffic situations, thus the inter-OLT traffic can be localized and the data exchange pressure of the core network can be released. Considering this architecture is designed to be maximum following the TWDM PON specification, the existing optical distribution network (ODN) investment can be saved and conventional EPON/GPON equipment can be compatible with the proposed architecture. What's more, based on this architecture, we propose a dynamic wavelength scheduling algorithm, which can be deployed as an application on control plane

NOTES ON OPTIMAL ALLOCATION FOR FIXED SIZE CONFIDENCE REGIONS OF THE DIFFERENCE OF TWO MULTINORMAL MEANS

OpenAIRE

Hyakutake, Hiroto; Kawasaki, Hidefumi

2004-01-01

We consider the problem of constructing a fixed-size confidence region of the difference of two multinormal means when the covariance matrices have intraclass correlation structure. When the covariance matrices are known, we derive an optimal allocation. A two-stage procedure is given for the problem with unknown covariance matrices.

Ant Colony Optimization Algorithm for Centralized Dynamic Channel Allocation in Multi-Cell OFDMA Systems

Science.gov (United States)

Kim, Hyo-Su; Kim, Dong-Hoi

The dynamic channel allocation (DCA) scheme in multi-cell systems causes serious inter-cell interference (ICI) problem to some existing calls when channels for new calls are allocated. Such a problem can be addressed by advanced centralized DCA design that is able to minimize ICI. Thus, in this paper, a centralized DCA is developed for the downlink of multi-cell orthogonal frequency division multiple access (OFDMA) systems with full spectral reuse. However, in practice, as the search space of channel assignment for centralized DCA scheme in multi-cell systems grows exponentially with the increase of the number of required calls, channels, and cells, it becomes an NP-hard problem and is currently too complicated to find an optimum channel allocation. In this paper, we propose an ant colony optimization (ACO) based DCA scheme using a low-complexity ACO algorithm which is a kind of heuristic algorithm in order to solve the aforementioned problem. Simulation results demonstrate significant performance improvements compared to the existing schemes in terms of the grade of service (GoS) performance and the forced termination probability of existing calls without degrading the system performance of the average throughput.

Optimized Energy Efficiency and Spectral Efficiency Resource Allocation Strategies for Phantom Cellular Networks

KAUST Repository

Abdelhady, Amr, M.; Amin, Osama; Alouini, Mohamed-Slim

2016-01-01

Multi-teir hetrogeneous networks have become an essential constituent for next generation cellular networks. Meanwhile, energy efficiency (EE) has been considered a critical design criterion along with the traditional spectral efficiency (SE) metric. In this context, we study power and spectrum allocation for the recently proposed two-teir architecture known as Phantom cellular networks. The optimization framework includes both EE and SE, where we propose an algorithm that computes the SE and EE resource allocation for Phantom cellular networks. Then, we compare the performance of both design strategies versus the number of users, and the ration of Phantom cellresource blocks to the total number or resource blocks. We aim to investigate the effect of some system parameters to acheive improved SE or EE performance at a non-significant loss in EE or SE performance, respectively. It was found that the system parameters can be tuned so that the EE solution does not yield a significant loss in the SE performance.

Optimized Energy Efficiency and Spectral Efficiency Resource Allocation Strategies for Phantom Cellular Networks

KAUST Repository

Abdelhady, Amr, M.

2016-01-06

Multi-teir hetrogeneous networks have become an essential constituent for next generation cellular networks. Meanwhile, energy efficiency (EE) has been considered a critical design criterion along with the traditional spectral efficiency (SE) metric. In this context, we study power and spectrum allocation for the recently proposed two-teir architecture known as Phantom cellular networks. The optimization framework includes both EE and SE, where we propose an algorithm that computes the SE and EE resource allocation for Phantom cellular networks. Then, we compare the performance of both design strategies versus the number of users, and the ration of Phantom cellresource blocks to the total number or resource blocks. We aim to investigate the effect of some system parameters to acheive improved SE or EE performance at a non-significant loss in EE or SE performance, respectively. It was found that the system parameters can be tuned so that the EE solution does not yield a significant loss in the SE performance.

Optimal Allocation of Thermal-Electric Decoupling Systems Based on the National Economy by an Improved Conjugate Gradient Method

Directory of Open Access Journals (Sweden)

Shuang Rong

2015-12-01

Full Text Available Aiming to relieve the large amount of wind power curtailment during the heating period in the North China region, a thermal-electric decoupling (TED approach is proposed to both bring down the constraint of forced power output of combined heat and power plants and increase the electric load level during valley load times that assist the power grid in consuming more wind power. The operating principles of the thermal-electric decoupling approach is described, the mathematical model of its profits is developed, the constraint conditions of its operation are listed, also, an improved parallel conjugate gradient is utilized to bypass the saddle problem and accelerate the optimal speed. Numerical simulations are implemented and reveal an optimal allocation of TED which with a rated power of 280 MW and 185 MWh heat storage capacity are possible. This allocation of TED could bring approximately 16.9 billion Yuan of economic profit and consume more than 80% of the surplus wind energy which would be curtailed without the participation of TED. The results in this article verify the effectiveness of this method that could provide a referential guidance for thermal-electric decoupling system allocation in practice.

Optimal Power Allocation of a Wireless Sensor Node under Different Rate Constraints

KAUST Repository

Solares, Jose

2011-07-01

Wireless sensor networks consist of the placement of sensors over a broad area in order to acquire data. Depending on the application, different design criteria should be considered in the construction of the sensors but among all of them, the battery life-cycle is of crucial interest. Power minimization is a problem that has been addressed from different approaches which include an analysis from an architectural perspective and with bit error rate and/or discrete instantaneous transmission rate constraints, among others. In this work, the optimal transmit power of a sensor node while satisfying different rate constraints is derived. First, an optimization problem with an instantaneous transmission rate constraint is addressed. Next, the optimal power is analyzed, but now with an average transmission rate constraint. The optimal solution for a class of fading channels, in terms of system parameters, is presented and a suboptimal solution is also proposed for an easier, yet efficient, implementation. Insightful asymptotical analysis for both schemes, considering a Rayleigh fading channel, are shown. Furthermore, the optimal power allocation for a sensor node in a cognitive radio environment is analyzed where an optimum solution for a class of fading channels is again derived. In all cases, numerical results are provided for either Rayleigh or Nakagami-m fading channels. The results obtained are extended to scenarios where we have either one transmitter-multiple receivers or multiple transmitters-one receiver.

An intelligent allocation algorithm for parallel processing

Science.gov (United States)

Carroll, Chester C.; Homaifar, Abdollah; Ananthram, Kishan G.

1988-01-01

The problem of allocating nodes of a program graph to processors in a parallel processing architecture is considered. The algorithm is based on critical path analysis, some allocation heuristics, and the execution granularity of nodes in a program graph. These factors, and the structure of interprocessor communication network, influence the allocation. To achieve realistic estimations of the executive durations of allocations, the algorithm considers the fact that nodes in a program graph have to communicate through varying numbers of tokens. Coarse and fine granularities have been implemented, with interprocessor token-communication duration, varying from zero up to values comparable to the execution durations of individual nodes. The effect on allocation of communication network structures is demonstrated by performing allocations for crossbar (non-blocking) and star (blocking) networks. The algorithm assumes the availability of as many processors as it needs for the optimal allocation of any program graph. Hence, the focus of allocation has been on varying token-communication durations rather than varying the number of processors. The algorithm always utilizes as many processors as necessary for the optimal allocation of any program graph, depending upon granularity and characteristics of the interprocessor communication network.

A stream-scale model to optimize the water allocation for Small Hydropower Plants and the application to traditional systems

Science.gov (United States)

Razurel, Pierre; Niayifar, Amin; Perona, Paolo

2017-04-01

Hydropower plays an important role in supplying worldwide energy demand where it contributes to approximately 16% of global electricity production. Although hydropower, as an emission-free renewable energy, is a reliable source of energy to mitigate climate change, its development will increase river exploitation. The environmental impacts associated with both small hydropower plants (SHP) and traditional dammed systems have been found to the consequence of changing natural flow regime with other release policies, e.g. the minimal flow. Nowadays, in some countries, proportional allocation rules are also applied aiming to mimic the natural flow variability. For example, these dynamic rules are part of the environmental guidance in the United Kingdom and constitute an improvement in comparison to static rules. In a context in which the full hydropower potential might be reached in a close future, a solution to optimize the water allocation seems essential. In this work, we present a model that enables to simulate a wide range of water allocation rules (static and dynamic) for a specific hydropower plant and to evaluate their associated economic and ecological benefits. It is developed in the form of a graphical user interface (GUI) where, depending on the specific type of hydropower plant (i.e., SHP or traditional dammed system), the user is able to specify the different characteristics (e.g., hydrological data and turbine characteristics) of the studied system. As an alternative to commonly used policies, a new class of dynamic allocation functions (non-proportional repartition rules) is introduced (e.g., Razurel et al., 2016). The efficiency plot resulting from the simulations shows the environmental indicator and the energy produced for each allocation policies. The optimal water distribution rules can be identified on the Pareto's frontier, which is obtained by stochastic optimization in the case of storage systems (e.g., Niayifar and Perona, submitted) and by

Optimal Power Allocation Strategy in a Joint Bistatic Radar and Communication System Based on Low Probability of Intercept.

Science.gov (United States)

Shi, Chenguang; Wang, Fei; Salous, Sana; Zhou, Jianjiang

2017-11-25

In this paper, we investigate a low probability of intercept (LPI)-based optimal power allocation strategy for a joint bistatic radar and communication system, which is composed of a dedicated transmitter, a radar receiver, and a communication receiver. The joint system is capable of fulfilling the requirements of both radar and communications simultaneously. First, assuming that the signal-to-noise ratio (SNR) corresponding to the target surveillance path is much weaker than that corresponding to the line of sight path at radar receiver, the analytically closed-form expression for the probability of false alarm is calculated, whereas the closed-form expression for the probability of detection is not analytically tractable and is approximated due to the fact that the received signals are not zero-mean Gaussian under target presence hypothesis. Then, an LPI-based optimal power allocation strategy is presented to minimize the total transmission power for information signal and radar waveform, which is constrained by a specified information rate for the communication receiver and the desired probabilities of detection and false alarm for the radar receiver. The well-known bisection search method is employed to solve the resulting constrained optimization problem. Finally, numerical simulations are provided to reveal the effects of several system parameters on the power allocation results. It is also demonstrated that the LPI performance of the joint bistatic radar and communication system can be markedly improved by utilizing the proposed scheme.

Large portfolio risk management and optimal portfolio allocation with dynamic elliptical copulas

Directory of Open Access Journals (Sweden)

Jin Xisong

2018-02-01

Full Text Available Previous research has focused on the importance of modeling the multivariate distribution for optimal portfolio allocation and active risk management. However, existing dynamic models are not easily applied to high-dimensional problems due to the curse of dimensionality. In this paper, we extend the framework of the Dynamic Conditional Correlation/Equicorrelation and an extreme value approach into a series of Dynamic Conditional Elliptical Copulas. We investigate risk measures such as Value at Risk (VaR and Expected Shortfall (ES for passive portfolios and dynamic optimal portfolios using Mean-Variance and ES criteria for a sample of US stocks over a period of 10 years. Our results suggest that (1 Modeling the marginal distribution is important for dynamic high-dimensional multivariate models. (2 Neglecting the dynamic dependence in the copula causes over-aggressive risk management. (3 The DCC/DECO Gaussian copula and t-copula work very well for both VaR and ES. (4 Grouped t-copulas and t-copulas with dynamic degrees of freedom further match the fat tail. (5 Correctly modeling the dependence structure makes an improvement in portfolio optimization with respect to tail risk. (6 Models driven by multivariate t innovations with exogenously given degrees of freedom provide a flexible and applicable alternative for optimal portfolio risk management.

Methodology for allocating reliability and risk

International Nuclear Information System (INIS)

Cho, N.Z.; Papazoglou, I.A.; Bari, R.A.

1986-05-01

This report describes a methodology for reliability and risk allocation in nuclear power plants. The work investigates the technical feasibility of allocating reliability and risk, which are expressed in a set of global safety criteria and which may not necessarily be rigid, to various reactor systems, subsystems, components, operations, and structures in a consistent manner. The report also provides general discussions on the problem of reliability and risk allocation. The problem is formulated as a multiattribute decision analysis paradigm. The work mainly addresses the first two steps of a typical decision analysis, i.e., (1) identifying alternatives, and (2) generating information on outcomes of the alternatives, by performing a multiobjective optimization on a PRA model and reliability cost functions. The multiobjective optimization serves as the guiding principle to reliability and risk allocation. The concept of ''noninferiority'' is used in the multiobjective optimization problem. Finding the noninferior solution set is the main theme of the current approach. The final step of decision analysis, i.e., assessment of the decision maker's preferences could then be performed more easily on the noninferior solution set. Some results of the methodology applications to a nontrivial risk model are provided, and several outstanding issues such as generic allocation, preference assessment, and uncertainty are discussed. 29 refs., 44 figs., 39 tabs

A cooperative online learning scheme for resource allocation in 5G systems

KAUST Repository

Alqerm, Ismail; Shihada, Basem

2016-01-01

The demand on mobile Internet related services has increased the need for higher bandwidth in cellular networks. The 5G technology is envisioned as a solution to satisfy this demand as it provides high data rates and scalable bandwidth. The multi-tier heterogeneous structure of 5G with dense base station deployment, relays, and device-to-device (D2D) communications intends to serve users with different QoS requirements. However, the multi-tier structure causes severe interference among the multi-tier users which further complicates the resource allocation problem. In this paper, we propose a cooperative scheme to tackle the interference problem, including both cross-tier interference that affects macro users from other tiers and co-tier interference, which is among users belong to the same tier. The scheme employs an online learning algorithm for efficient spectrum allocation with power and modulation adaptation capability. Our evaluation results show that our online scheme outperforms others and achieves significant improvements in throughput, spectral efficiency, fairness, and outage ratio. © 2016 IEEE.

A cooperative online learning scheme for resource allocation in 5G systems

KAUST Repository

Alqerm, Ismail

2016-07-26

The demand on mobile Internet related services has increased the need for higher bandwidth in cellular networks. The 5G technology is envisioned as a solution to satisfy this demand as it provides high data rates and scalable bandwidth. The multi-tier heterogeneous structure of 5G with dense base station deployment, relays, and device-to-device (D2D) communications intends to serve users with different QoS requirements. However, the multi-tier structure causes severe interference among the multi-tier users which further complicates the resource allocation problem. In this paper, we propose a cooperative scheme to tackle the interference problem, including both cross-tier interference that affects macro users from other tiers and co-tier interference, which is among users belong to the same tier. The scheme employs an online learning algorithm for efficient spectrum allocation with power and modulation adaptation capability. Our evaluation results show that our online scheme outperforms others and achieves significant improvements in throughput, spectral efficiency, fairness, and outage ratio. © 2016 IEEE.

Multi-objective hierarchical genetic algorithms for multilevel redundancy allocation optimization

Energy Technology Data Exchange (ETDEWEB)

Kumar, Ranjan [Department of Aeronautics and Astronautics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan)], E-mail: ranjan.k@ks3.ecs.kyoto-u.ac.jp; Izui, Kazuhiro [Department of Aeronautics and Astronautics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan)], E-mail: izui@prec.kyoto-u.ac.jp; Yoshimura, Masataka [Department of Aeronautics and Astronautics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan)], E-mail: yoshimura@prec.kyoto-u.ac.jp; Nishiwaki, Shinji [Department of Aeronautics and Astronautics, Kyoto University, Yoshida-honmachi, Sakyo-ku, Kyoto 606-8501 (Japan)], E-mail: shinji@prec.kyoto-u.ac.jp

2009-04-15

Multilevel redundancy allocation optimization problems (MRAOPs) occur frequently when attempting to maximize the system reliability of a hierarchical system, and almost all complex engineering systems are hierarchical. Despite their practical significance, limited research has been done concerning the solving of simple MRAOPs. These problems are not only NP hard but also involve hierarchical design variables. Genetic algorithms (GAs) have been applied in solving MRAOPs, since they are computationally efficient in solving such problems, unlike exact methods, but their applications has been confined to single-objective formulation of MRAOPs. This paper proposes a multi-objective formulation of MRAOPs and a methodology for solving such problems. In this methodology, a hierarchical GA framework for multi-objective optimization is proposed by introducing hierarchical genotype encoding for design variables. In addition, we implement the proposed approach by integrating the hierarchical genotype encoding scheme with two popular multi-objective genetic algorithms (MOGAs)-the strength Pareto evolutionary genetic algorithm (SPEA2) and the non-dominated sorting genetic algorithm (NSGA-II). In the provided numerical examples, the proposed multi-objective hierarchical approach is applied to solve two hierarchical MRAOPs, a 4- and a 3-level problems. The proposed method is compared with a single-objective optimization method that uses a hierarchical genetic algorithm (HGA), also applied to solve the 3- and 4-level problems. The results show that a multi-objective hierarchical GA (MOHGA) that includes elitism and mechanism for diversity preserving performed better than a single-objective GA that only uses elitism, when solving large-scale MRAOPs. Additionally, the experimental results show that the proposed method with NSGA-II outperformed the proposed method with SPEA2 in finding useful Pareto optimal solution sets.

Multi-objective hierarchical genetic algorithms for multilevel redundancy allocation optimization

International Nuclear Information System (INIS)

Kumar, Ranjan; Izui, Kazuhiro; Yoshimura, Masataka; Nishiwaki, Shinji

2009-01-01

Multilevel redundancy allocation optimization problems (MRAOPs) occur frequently when attempting to maximize the system reliability of a hierarchical system, and almost all complex engineering systems are hierarchical. Despite their practical significance, limited research has been done concerning the solving of simple MRAOPs. These problems are not only NP hard but also involve hierarchical design variables. Genetic algorithms (GAs) have been applied in solving MRAOPs, since they are computationally efficient in solving such problems, unlike exact methods, but their applications has been confined to single-objective formulation of MRAOPs. This paper proposes a multi-objective formulation of MRAOPs and a methodology for solving such problems. In this methodology, a hierarchical GA framework for multi-objective optimization is proposed by introducing hierarchical genotype encoding for design variables. In addition, we implement the proposed approach by integrating the hierarchical genotype encoding scheme with two popular multi-objective genetic algorithms (MOGAs)-the strength Pareto evolutionary genetic algorithm (SPEA2) and the non-dominated sorting genetic algorithm (NSGA-II). In the provided numerical examples, the proposed multi-objective hierarchical approach is applied to solve two hierarchical MRAOPs, a 4- and a 3-level problems. The proposed method is compared with a single-objective optimization method that uses a hierarchical genetic algorithm (HGA), also applied to solve the 3- and 4-level problems. The results show that a multi-objective hierarchical GA (MOHGA) that includes elitism and mechanism for diversity preserving performed better than a single-objective GA that only uses elitism, when solving large-scale MRAOPs. Additionally, the experimental results show that the proposed method with NSGA-II outperformed the proposed method with SPEA2 in finding useful Pareto optimal solution sets

A high performance long-reach passive optical network with a novel excess bandwidth distribution scheme

Science.gov (United States)

Chao, I.-Fen; Zhang, Tsung-Min

2015-06-01

Long-reach passive optical networks (LR-PONs) have been considered to be promising solutions for future access networks. In this paper, we propose a distributed medium access control (MAC) scheme over an advantageous LR-PON network architecture that reroutes the control information from and back to all ONUs through an (N + 1) × (N + 1) star coupler (SC) deployed near the ONUs, thereby overwhelming the extremely long propagation delay problem in LR-PONs. In the network, the control slot is designed to contain all bandwidth requirements of all ONUs and is in-band time-division-multiplexed with a number of data slots within a cycle. In the proposed MAC scheme, a novel profit-weight-based dynamic bandwidth allocation (P-DBA) scheme is presented. The algorithm is designed to efficiently and fairly distribute the amount of excess bandwidth based on a profit value derived from the excess bandwidth usage of each ONU, which resolves the problems of previously reported DBA schemes that are either unfair or inefficient. The simulation results show that the proposed decentralized algorithms exhibit a nearly three-order-of-magnitude improvement in delay performance compared to the centralized algorithms over LR-PONs. Moreover, the newly proposed P-DBA scheme guarantees low delay performance and fairness even when under attack by the malevolent ONU irrespective of traffic loads and burstiness.

Energy-Efficient Bandwidth Allocation for Multiuser Scalable Video Streaming over WLAN

Directory of Open Access Journals (Sweden)

Lafruit Gauthier

2008-01-01

Full Text Available Abstract We consider the problem of packet scheduling for the transmission of multiple video streams over a wireless local area network (WLAN. A cross-layer optimization framework is proposed to minimize the wireless transceiver energy consumption while meeting the user required visual quality constraints. The framework relies on the IEEE 802.11 standard and on the embedded bitstream structure of the scalable video coding scheme. It integrates an application-level video quality metric as QoS constraint (instead of a communication layer quality metric with energy consumption optimization through link layer scaling and sleeping. Both energy minimization and min-max energy optimization strategies are discussed. Simulation results demonstrate significant energy gains compared to the state-of-the-art approaches.

Application of genetic algorithm for reliability allocation in nuclear power plants

International Nuclear Information System (INIS)

Yang, Joon-Eon; Hwang, Mee-Jung; Sung, Tae-Yong; Jin, Youngho

1999-01-01

Reliability allocation is an optimization process of minimizing the total plant costs subject to the overall plant safety goal constraints. Reliability allocation was applied to determine the reliability characteristics of reactor systems, subsystems, major components and plant procedures that are consistent with a set of top-level performance goals; the core melt frequency, acute fatalities and latent fatalities. Reliability allocation can be performed to improve the design, operation and safety of new and/or existing nuclear power plants. Reliability allocation is a kind of a difficult multi-objective optimization problem as well as a global optimization problem. The genetic algorithm, known as one of the most powerful tools for most optimization problems, is applied to the reliability allocation problem of a typical pressurized water reactor in this article. One of the main problems of reliability allocation is defining realistic objective functions. Hence, in order to optimize the reliability of the system, the cost for improving and/or degrading the reliability of the system should be included in the reliability allocation process. We used techniques derived from the value impact analysis to define the realistic objective function in this article

Single Allocation Hub-and-spoke Networks Design Based on Ant Colony Optimization Algorithm

Directory of Open Access Journals (Sweden)

Yang Pingle

2014-10-01

Full Text Available Capacitated single allocation hub-and-spoke networks can be abstracted as a mixed integer linear programming model equation with three variables. Introducing an improved ant colony algorithm, which has six local search operators. Meanwhile, introducing the "Solution Pair" concept to decompose and optimize the composition of the problem, the problem can become more specific and effectively meet the premise and advantages of using ant colony algorithm. Finally, location simulation experiment is made according to Australia Post data to demonstrate this algorithm has good efficiency and stability for solving this problem.

Characterizing contract-based multiagent resource allocation in networks.

Science.gov (United States)

An, Bo; Lesser, Victor

2010-06-01

We consider a multiagent resource allocation problem where individual users intend to route traffic by requesting the help of entities across a network, and a cost is incurred at each network node that depends on the amount of traffic to be routed. We propose to study contract-based network resource allocation. In our model, users and nodes in the network make contracts before nodes route traffic for the users. The problem is an interesting self-interested negotiation problem because it requires the complete assembly of a set of distinct resources, and there are multiple combinations of distinct resources that could satisfy the goal of negotiation. First, we characterize the network allocation problem and show that finding optimal allocations is NP-complete and is inapproximable. We take both Nash equilibrium and pairwise Nash equilibrium as the solution concepts to characterize the equilibrium allocations. We find that, for any resource allocation game, Nash equilibrium and pairwise Nash equilibrium always exist. In addition, socially optimal allocations are always supported by Nash equilibrium and pairwise Nash equilibrium. We introduce best-response dynamics in which each agent takes a myopic best-response strategy and interacts with each other to dynamically form contracts. We analyze the convergence of the dynamics in some special cases. We also experimentally study the convergence rate of the dynamics and how efficient the evolved allocation is as compared with the optimal allocation in a variety of environments.

A New Biobjective Model to Optimize Integrated Redundancy Allocation and Reliability-Centered Maintenance Problems in a System Using Metaheuristics

Directory of Open Access Journals (Sweden)

Shima MohammadZadeh Dogahe

2015-01-01

Full Text Available A novel integrated model is proposed to optimize the redundancy allocation problem (RAP and the reliability-centered maintenance (RCM simultaneously. A system of both repairable and nonrepairable components has been considered. In this system, electronic components are nonrepairable while mechanical components are mostly repairable. For nonrepairable components, a redundancy allocation problem is dealt with to determine optimal redundancy strategy and number of redundant components to be implemented in each subsystem. In addition, a maintenance scheduling problem is considered for repairable components in order to identify the best maintenance policy and optimize system reliability. Both active and cold standby redundancy strategies have been taken into account for electronic components. Also, net present value of the secondary cost including operational and maintenance costs has been calculated. The problem is formulated as a biobjective mathematical programming model aiming to reach a tradeoff between system reliability and cost. Three metaheuristic algorithms are employed to solve the proposed model: Nondominated Sorting Genetic Algorithm (NSGA-II, Multiobjective Particle Swarm Optimization (MOPSO, and Multiobjective Firefly Algorithm (MOFA. Several test problems are solved using the mentioned algorithms to test efficiency and effectiveness of the solution approaches and obtained results are analyzed.

Optimal allocation of international atomic energy agency inspection resources

International Nuclear Information System (INIS)

Markin, J.T.

1987-01-01

Each year the Department of Safeguards of the International Atomic Energy Agency (IAEA) conducts inspections to confirm that nuclear materials and facilities are employed for peaceful purposes. Because of limited inspection resources, however, the IAEA cannot fully attain its safeguards goals either quantitatively as measured by the inspection effort negotiated in the facility attachments or qualitatively as measured by the IAEA criteria for evaluating attainment of safeguards goals. Under current IAEA procedures the allocation of inspection resources assigns essentially equal inspection effort to facilities of the same type. An alternative approach would incorporate consideration of all material categories and facilities to be assigned inspection resources when allocating effort to a particular facility. One such method for allocating inspection resources is based on the IAEA criteria. The criteria provide a framework for allocating inspection effort that includes a ranking of material types according to their safeguards importance, an implicit definition of inspection activities for each material and facility type, and criteria for judging the attainment of safeguards goals in terms of the quality and frequency of these inspection activities. This framework is applicable to resource allocation for an arbitrary group of facilities such as a state's fuel cycle, the facilities inspected by an operations division, or all of the facilities inspected by the IAEA

Redundancy allocation problem of a system with increasing failure rates of components based on Weibull distribution: A simulation-based optimization approach

International Nuclear Information System (INIS)

Guilani, Pedram Pourkarim; Azimi, Parham; Niaki, S.T.A.; Niaki, Seyed Armin Akhavan

2016-01-01

The redundancy allocation problem (RAP) is a useful method to enhance system reliability. In most works involving RAP, failure rates of the system components are assumed to follow either exponential or k-Erlang distributions. In real world problems however, many systems have components with increasing failure rates. This indicates that as time passes by, the failure rates of the system components increase in comparison to their initial failure rates. In this paper, the redundancy allocation problem of a series–parallel system with components having an increasing failure rate based on Weibull distribution is investigated. An optimization method via simulation is proposed for modeling and a genetic algorithm is developed to solve the problem. - Highlights: • The redundancy allocation problem of a series–parallel system is aimed. • Components possess an increasing failure rate based on Weibull distribution. • An optimization method via simulation is proposed for modeling. • A genetic algorithm is developed to solve the problem.

Optimal Time Allocation in Backscatter Assisted Wireless Powered Communication Networks

Science.gov (United States)

Lyu, Bin; Yang, Zhen; Gui, Guan; Sari, Hikmet

2017-01-01

This paper proposes a wireless powered communication network (WPCN) assisted by backscatter communication (BackCom). This model consists of a power station, an information receiver and multiple users that can work in either BackCom mode or harvest-then-transmit (HTT) mode. The time block is mainly divided into two parts corresponding to the data backscattering and transmission periods, respectively. The users first backscatter data to the information receiver in time division multiple access (TDMA) during the data backscattering period. When one user works in the BackCom mode, the other users harvest energy from the power station. During the data transmission period, two schemes, i.e., non-orthogonal multiple access (NOMA) and TDMA, are considered. To maximize the system throughput, the optimal time allocation policies are obtained. Simulation results demonstrate the superiority of the proposed model. PMID:28587171

Participation behavior and social welfare in repeated task allocations

NARCIS (Netherlands)

Ye, Q.C.; Zhang, Y.

2016-01-01

Task allocation problems have focused on achieving one-shot optimality. In practice, many task allocation problems are of repeated nature, where the allocation outcome of previous rounds may influence the participation of agents in subsequent rounds, and consequently, the quality of the allocations

Improved Cat Swarm Optimization for Simultaneous Allocation of DSTATCOM and DGs in Distribution Systems

Directory of Open Access Journals (Sweden)

Neeraj Kanwar

2015-01-01

Full Text Available This paper addresses a new methodology for the simultaneous optimal allocation of DSTATCOM and DG in radial distribution systems to maximize power loss reduction while maintaining better node voltage profiles under multilevel load profile. Cat Swarm Optimization (CSO is one of the recently developed powerful swarm intelligence-based optimization techniques that mimics the natural behavior of cats but usually suffers from poor convergence and accuracy while subjected to large dimension problem. Therefore, an Improved CSO (ICSO technique is proposed to efficiently solve the problem where the seeking mode of CSO is modified to enhance its exploitation potential. In addition, the problem search space is virtually squeezed by suggesting an intelligent search approach which smartly scans the problem search space. Further, the effect of network reconfiguration has also been investigated after optimally placing DSTATCOMs and DGs in the distribution network. The suggested measures enhance the convergence and accuracy of the algorithm without loss of diversity. The proposed method is investigated on 69-bus test distribution system and the application results are very promising for the operation of smart distribution systems.

On capital allocation for stochastic arrangement increasing actuarial risks

Directory of Open Access Journals (Sweden)

Pan Xiaoqing

2017-01-01

Full Text Available This paper studies the increasing convex ordering of the optimal discounted capital allocations for stochastic arrangement increasing risks with stochastic arrangement decreasing occurrence times. The application to optimal allocation of policy limits is presented as an illustration as well.

Perbandingan Metode Simple Queues Dan Queues Tree Untuk Optimasi Manajemen Bandwidth Jaringan Komputer Di STMIK PPKIA Pradnya Paramita Malang

OpenAIRE

Syaifuddin, Aris; Yunus, Mahmud; Sundari, Retno

2013-01-01

This research resulted in a comparison between the Simple Queues method and Queues Tree using Mikrotik router that takes a case study in STMIK PPKIA PRADNYA PARAMITA MALANG has been tested to determine which method is the most optimal deal of bandwidth sharing on computer networks. After finding out where the most optimal method will be applied in STMIK PPKIA PRADNYA PARAMITA MALANG to maximize network performance and bandwidth sharing in place, the results of the study lead to the conclusion...

An Empirical Study on the Driving Path of Optimizing the Resources Allocation of Foreign Trade Enterprises from the Perspective of Energy Supply-side Reform

Science.gov (United States)

You, Yu-cong; Yi, Lu-xia

2017-11-01

From the perspective of energy supply-side reform, this paper, by conducting an empirical study on foreign trade enterprises, conducts a research on the cross-role effect of optimizing the resources allocation and enhancing the energy efficiency. Methodologically, this paper creatively introduces the HILE's probabilistic structured property into Granger causality test analysis, forming an HILE-Granger (H-G) model, so as to empirically estimate both the short-term and long-term causal relationship effects between the energy efficiency and resources allocation. Conclusion is drawn that optimization of resources allocation is positively proportional with the energy efficiency enhancement. This paper is to provide a decision-making reference for the supply side reform strategy of foreign trade enterprises under the background of green energy economy.

Twelve fundamental life histories evolving through allocation-dependent fecundity and survival.

Science.gov (United States)

Johansson, Jacob; Brännström, Åke; Metz, Johan A J; Dieckmann, Ulf

2018-03-01

An organism's life history is closely interlinked with its allocation of energy between growth and reproduction at different life stages. Theoretical models have established that diminishing returns from reproductive investment promote strategies with simultaneous investment into growth and reproduction (indeterminate growth) over strategies with distinct phases of growth and reproduction (determinate growth). We extend this traditional, binary classification by showing that allocation-dependent fecundity and mortality rates allow for a large diversity of optimal allocation schedules. By analyzing a model of organisms that allocate energy between growth and reproduction, we find twelve types of optimal allocation schedules, differing qualitatively in how reproductive allocation increases with body mass. These twelve optimal allocation schedules include types with different combinations of continuous and discontinuous increase in reproduction allocation, in which phases of continuous increase can be decelerating or accelerating. We furthermore investigate how this variation influences growth curves and the expected maximum life span and body size. Our study thus reveals new links between eco-physiological constraints and life-history evolution and underscores how allocation-dependent fitness components may underlie biological diversity.

A 750MHz and a 8GHz High Bandwidth Digital FFT Spectrometer, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — The scope of this project is to to develop a wide bandwidth, low power, and compact single board digital Fast Fourier Transform spectrometer (FFTS) optimized for the...

Harbor porpoise clicks do not have conditionally minimum time bandwidth product

DEFF Research Database (Denmark)

Beedholm, Kristian

2008-01-01

The hypothesis that odontocete clicks have minimal time frequency product given their delay and center frequency values is tested by using an in-phase averaged porpoise click compared with a pure tone weighted with the same envelope. These signals have the same delay and the same center frequency...... values but the time bandwidth product of the artificial click is only 0.76 that of the original. Therefore signals with the same parameters exist that have a lower time bandwidth product. The observation that porpoise clicks are in fact minimum phase is confirmed for porpoise clicks and this property...... is argued to be incompatible with optimal reception, if auditory filters are also minimum phase....

Distributed Task Rescheduling With Time Constraints for the Optimization of Total Task Allocations in a Multirobot System.

Science.gov (United States)

Turner, Joanna; Meng, Qinggang; Schaefer, Gerald; Whitbrook, Amanda; Soltoggio, Andrea

2017-09-28

This paper considers the problem of maximizing the number of task allocations in a distributed multirobot system under strict time constraints, where other optimization objectives need also be considered. It builds upon existing distributed task allocation algorithms, extending them with a novel method for maximizing the number of task assignments. The fundamental idea is that a task assignment to a robot has a high cost if its reassignment to another robot creates a feasible time slot for unallocated tasks. Multiple reassignments among networked robots may be required to create a feasible time slot and an upper limit to this number of reassignments can be adjusted according to performance requirements. A simulated rescue scenario with task deadlines and fuel limits is used to demonstrate the performance of the proposed method compared with existing methods, the consensus-based bundle algorithm and the performance impact (PI) algorithm. Starting from existing (PI-generated) solutions, results show up to a 20% increase in task allocations using the proposed method.

Stochastic Resource Allocation for Energy-Constrained Systems

Directory of Open Access Journals (Sweden)

Sachs DanielGrobe

2009-01-01

Full Text Available Battery-powered wireless systems running media applications have tight constraints on energy, CPU, and network capacity, and therefore require the careful allocation of these limited resources to maximize the system's performance while avoiding resource overruns. Usually, resource-allocation problems are solved using standard knapsack-solving techniques. However, when allocating conservable resources like energy (which unlike CPU and network remain available for later use if they are not used immediately knapsack solutions suffer from excessive computational complexity, leading to the use of suboptimal heuristics. We show that use of Lagrangian optimization provides a fast, elegant, and, for convex problems, optimal solution to the allocation of energy across applications as they enter and leave the system, even if the exact sequence and timing of their entrances and exits is not known. This permits significant increases in achieved utility compared to heuristics in common use. As our framework requires only a stochastic description of future workloads, and not a full schedule, we also significantly expand the scope of systems that can be optimized.

Energy-Efficient Power Allocation for Cognitive MIMO Channels

KAUST Repository

Sboui, Lokman

2017-03-20

Due to the massive data traffic in wireless networks, energy consumption has become a crucial concern, especially with the limited power supply of the mobile terminals and the increasing CO2 emission of the cellular industry. In this context, we study the energy efficiency (EE) of MIMO spectrum sharing cognitive radio (CR) systems under power and interference constraints. We present an energy-efficient power allocation framework based on maximizing the average EE per parallel channel resulting from the singular value decomposition (SVD) eigenmode transmission. We also present a sub-optimal low-complexity power allocation scheme based on the water-filling power allocation. In the numerical results, we show that the sub-optimal power allocation achieves at least 95% of the optimal performance. In addition, we show that adopting more antennas is more energy efficient for a given power budget. Finally, we show that the interference threshold has a significant effect on both the EE and the spectral efficiency at high-power regime.

Intelligent tactical asset allocation support system

OpenAIRE

Hiemstra, Y.

1995-01-01

This paper presents an advanced support system for Tactical Asset Allocation. Asset allocation explains over 90% of portfolio performance (Brinson, Hood and Beebower, 1988). Tactical asset allocation adjusts a strategic portfolio on the basis of short term market outlooks. The system includes aprediction model that forecasts quarterly excess returns on the S and PSOO, an optimization model that adjusts a user-specified strategic portfolio on thebasis of the excess return forecast, and a compo...

Dynamic Allocation of SPM Based on Time-Slotted Cache Conflict Graph for System Optimization

Science.gov (United States)

Wu, Jianping; Ling, Ming; Zhang, Yang; Mei, Chen; Wang, Huan

This paper proposes a novel dynamic Scratch-pad Memory allocation strategy to optimize the energy consumption of the memory sub-system. Firstly, the whole program execution process is sliced into several time slots according to the temporal dimension; thereafter, a Time-Slotted Cache Conflict Graph (TSCCG) is introduced to model the behavior of Data Cache (D-Cache) conflicts within each time slot. Then, Integer Nonlinear Programming (INP) is implemented, which can avoid time-consuming linearization process, to select the most profitable data pages. Virtual Memory System (VMS) is adopted to remap those data pages, which will cause severe Cache conflicts within a time slot, to SPM. In order to minimize the swapping overhead of dynamic SPM allocation, a novel SPM controller with a tightly coupled DMA is introduced to issue the swapping operations without CPU's intervention. Last but not the least, this paper discusses the fluctuation of system energy profit based on different MMU page size as well as the Time Slot duration quantitatively. According to our design space exploration, the proposed method can optimize all of the data segments, including global data, heap and stack data in general, and reduce the total energy consumption by 27.28% on average, up to 55.22% with a marginal performance promotion. And comparing to the conventional static CCG (Cache Conflicts Graph), our approach can obtain 24.7% energy profit on average, up to 30.5% with a sight boost in performance.

Market-Based Resource Allocation in a Wirelessly Integrated Naval Engineering Plant

Science.gov (United States)

2009-12-01

available wireless nodes will be developed. Using a multi-agent approach based on free market economics (termed market based control) will be explored...as battery power, data storage capacity, MPU time, wireless bandwidth, etc.) required to perform complex computational tasks are available only in a...network. One approach to this problem is to apply free-market economics to help allocate these resources. Free-market economies can be thought of as

Optimal Resource Allocation for NOMA-TDMA Scheme with α-Fairness in Industrial Internet of Things.

Science.gov (United States)

Sun, Yanjing; Guo, Yiyu; Li, Song; Wu, Dapeng; Wang, Bin

2018-05-15

In this paper, a joint non-orthogonal multiple access and time division multiple access (NOMA-TDMA) scheme is proposed in Industrial Internet of Things (IIoT), which allowed multiple sensors to transmit in the same time-frequency resource block using NOMA. The user scheduling, time slot allocation, and power control are jointly optimized in order to maximize the system α -fair utility under transmit power constraint and minimum rate constraint. The optimization problem is nonconvex because of the fractional objective function and the nonconvex constraints. To deal with the original problem, we firstly convert the objective function in the optimization problem into a difference of two convex functions (D.C.) form, and then propose a NOMA-TDMA-DC algorithm to exploit the global optimum. Numerical results show that the NOMA-TDMA scheme significantly outperforms the traditional orthogonal multiple access scheme in terms of both spectral efficiency and user fairness.

Optimized Autonomous Space In-situ Sensor-Web for volcano monitoring

Science.gov (United States)

Song, W.-Z.; Shirazi, B.; Kedar, S.; Chien, S.; Webb, F.; Tran, D.; Davis, A.; Pieri, D.; LaHusen, R.; Pallister, J.; Dzurisin, D.; Moran, S.; Lisowski, M.

2008-01-01

In response to NASA's announced requirement for Earth hazard monitoring sensor-web technology, a multidisciplinary team involving sensor-network experts (Washington State University), space scientists (JPL), and Earth scientists (USGS Cascade Volcano Observatory (CVO)), is developing a prototype dynamic and scaleable hazard monitoring sensor-web and applying it to volcano monitoring. The combined Optimized Autonomous Space -In-situ Sensor-web (OASIS) will have two-way communication capability between ground and space assets, use both space and ground data for optimal allocation of limited power and bandwidth resources on the ground, and use smart management of competing demands for limited space assets. It will also enable scalability and seamless infusion of future space and in-situ assets into the sensor-web. The prototype will be focused on volcano hazard monitoring at Mount St. Helens, which has been active since October 2004. The system is designed to be flexible and easily configurable for many other applications as well. The primary goals of the project are: 1) integrating complementary space (i.e., Earth Observing One (EO-1) satellite) and in-situ (ground-based) elements into an interactive, autonomous sensor-web; 2) advancing sensor-web power and communication resource management technology; and 3) enabling scalability for seamless infusion of future space and in-situ assets into the sensor-web. To meet these goals, we are developing: 1) a test-bed in-situ array with smart sensor nodes capable of making autonomous data acquisition decisions; 2) efficient self-organization algorithm of sensor-web topology to support efficient data communication and command control; 3) smart bandwidth allocation algorithms in which sensor nodes autonomously determine packet priorities based on mission needs and local bandwidth information in real-time; and 4) remote network management and reprogramming tools. The space and in-situ control components of the system will be

Using linear integer programming for multi-site land-use allocation

NARCIS (Netherlands)

Aerts, J.C.J.H.; Eisinger, E.; Heuvelink, G.B.M.; Stewart, Th.J.

2003-01-01

Research in the area of spatial decision support (SDS) and resource allocation has recently generated increased attention for integrating optimization techniques with GIS. In this paper we address the use of spatial optimization techniques for solving multi-site land-use allocation (MLUA) problems,

Improved-Bandwidth Transimpedance Amplifier

Science.gov (United States)

Chapsky, Jacob

2009-01-01

The widest available operational amplifier, with the best voltage and current noise characteristics, is considered for transimpedance amplifier (TIA) applications where wide bandwidth is required to handle fast rising input signals (as for time-of-flight measurement cases). The added amplifier inside the TIA feedback loop can be configured to have slightly lower voltage gain than the bandwidth reduction factor.

Research advances on thereasonable water resources allocation in irrigation district

DEFF Research Database (Denmark)

Xuebin, Qi; Zhongdong, Huang; Dongmei, Qiao

2015-01-01

The rational allocation of water resources for irrigation is important to improve the efficiency in utilization of water resources and ensuring food security, but also effective control measures need to be in place for the sustainable utilization of water resources in an irrigation area. The prog......The rational allocation of water resources for irrigation is important to improve the efficiency in utilization of water resources and ensuring food security, but also effective control measures need to be in place for the sustainable utilization of water resources in an irrigation area...... mechanism of water resources is not perfect, the model for optimal water resources allocation is not practical, and the basic conditions for optimal allocation of water resources is relatively weak. In order to solve those problems in water resources allocation practice, six important as?pects must...... in irrigation districts, studying the water resources control technology in irrigation districts by hydrology ecological system, studying the technologies of real?time risk dispatching and intelligent management in irrigation districts, and finally studying the technology of cou?pling optimal allocation...

Joint Optimization of Power Allocation and Load Balancing for Hybrid VLC/RF Networks

KAUST Repository

Obeed, Mohanad; Salhab, Anas; Zummo, Salam A.; Alouini, Mohamed-Slim

2018-01-01

In this paper, we propose and study a new joint load balancing (LB) and power allocation (PA) scheme for a hybrid visible light communication (VLC) and radio frequency (RF) system consisting of one RF access point (AP) and multiple VLC APs. An iterative algorithm is proposed to distribute users on APs and distribute the powers of the APs on their users. In the PA subproblem, an optimization problem is formulated to allocate the power of each AP to the connected users for total achievable data rate maximization. In this subproblem, we propose a new efficient algorithm that finds optimal dual variables after formulating them in terms of each other. This new algorithm provides faster convergence and better performance than the traditional subgradient method. In addition, it does not depend on the step size or the initial values of the variables, which we look for, as the subgradient does. Then, we start with the user of the minimum data rate seeking another AP that offers a higher data rate for that user. Users with lower data rates continue reconnecting from one AP to another to balance the load only if this travel increases the summation of the achievable data rates and enhances the system fairness. Two approaches are proposed to have the joint PA and LB performed: a main approach that considers the exact interference information for all users, and a suboptimal approach that aims to decrease the complexity of the first approach by considering only the approximate interference information of users. The numerical results demonstrate that the proposed algorithms improve the system capacity and system fairness with fast convergence.

Joint Optimization of Power Allocation and Load Balancing for Hybrid VLC/RF Networks

KAUST Repository

Obeed, Mohanad

2018-04-18

In this paper, we propose and study a new joint load balancing (LB) and power allocation (PA) scheme for a hybrid visible light communication (VLC) and radio frequency (RF) system consisting of one RF access point (AP) and multiple VLC APs. An iterative algorithm is proposed to distribute users on APs and distribute the powers of the APs on their users. In the PA subproblem, an optimization problem is formulated to allocate the power of each AP to the connected users for total achievable data rate maximization. In this subproblem, we propose a new efficient algorithm that finds optimal dual variables after formulating them in terms of each other. This new algorithm provides faster convergence and better performance than the traditional subgradient method. In addition, it does not depend on the step size or the initial values of the variables, which we look for, as the subgradient does. Then, we start with the user of the minimum data rate seeking another AP that offers a higher data rate for that user. Users with lower data rates continue reconnecting from one AP to another to balance the load only if this travel increases the summation of the achievable data rates and enhances the system fairness. Two approaches are proposed to have the joint PA and LB performed: a main approach that considers the exact interference information for all users, and a suboptimal approach that aims to decrease the complexity of the first approach by considering only the approximate interference information of users. The numerical results demonstrate that the proposed algorithms improve the system capacity and system fairness with fast convergence.

Bandwidth-on-demand motion control

NARCIS (Netherlands)

Van Loon, S.J.L.M.; Hunnekens, B.G.B.; Simon, A.S.; van de Wouw, N.; Heemels, W.P.M.H.

2018-01-01

In this brief, we introduce a 'bandwidth-on-demand' variable-gain control (VGC) strategy that allows for a varying bandwidth of the feedback controller. The proposed VGC can achieve improved performance given time-varying, reference-dependent performance requirements compared with linear

Regenerative cooperative diversity networks with co-channel interference: Performance analysis and optimal energy allocation

KAUST Repository

Ikki, Salama Said

2013-02-01

A study of the effects of co-channel interference on a multirelay system with decode-and-forward (DF) protocol is presented. Orthogonal relaying is considered, and all relays that correctly decode the message in the broadcasting phase participate in the adaptive relaying phase. First, the effective signal-to-interference-plus-noise ratio (SINR) at the receiver is derived. Then, considering outage as the performance metric, we obtain exact closed-form expression for the outage probability. Simple and general asymptotic expressions for the outage probability, which explicitly show the coding and the diversity gains, are also derived and discussed. Furthermore, we present optimal energy-allocation schemes for minimizing outage under different resource constraints. Monte Carlo simulations are further provided to confirm the analytical results and illustrate the outage performance for different interference conditions and optimization schemes. © 1967-2012 IEEE.

Regenerative cooperative diversity networks with co-channel interference: Performance analysis and optimal energy allocation

KAUST Repository

Ikki, Salama Said; Pandarakkottilil, Ubaidulla; Aï ssa, Sonia

2013-01-01

A study of the effects of co-channel interference on a multirelay system with decode-and-forward (DF) protocol is presented. Orthogonal relaying is considered, and all relays that correctly decode the message in the broadcasting phase participate in the adaptive relaying phase. First, the effective signal-to-interference-plus-noise ratio (SINR) at the receiver is derived. Then, considering outage as the performance metric, we obtain exact closed-form expression for the outage probability. Simple and general asymptotic expressions for the outage probability, which explicitly show the coding and the diversity gains, are also derived and discussed. Furthermore, we present optimal energy-allocation schemes for minimizing outage under different resource constraints. Monte Carlo simulations are further provided to confirm the analytical results and illustrate the outage performance for different interference conditions and optimization schemes. © 1967-2012 IEEE.

Multiobjective optimal allocation problem with probabilistic non ...

African Journals Online (AJOL)

This paper considers the optimum compromise allocation in multivariate stratified sampling with non-linear objective function and probabilistic non-linear cost constraint. The probabilistic non-linear cost constraint is converted into equivalent deterministic one by using Chance Constrained programming. A numerical ...

Optimal Register Allocation by Augmented Left-Edge Algorithm on Arbitrary Control-Flow Structures

DEFF Research Database (Denmark)

Ruvald Pedersen, Mark; Madsen, Jan

2012-01-01

for allocation to be done using only quasi-local and local allocation - avoiding the complexity of true global allocation. As local allocation is much simpler than global allocation, this approach emphasizes efficiency and ease of implementation - at a cost of an increased number of register transfers compared...... to other allocators. Experiments show that runtime is linear for all practical purposes....

Optimal allocation of leaf epidermal area for gas exchange

OpenAIRE

de Boer, Hugo J.; Price, Charles A.; Wagner-Cremer, Friederike; Dekker, Stefan C.; Franks, Peter J.; Veneklaas, Erik J.

2016-01-01

Summary A long?standing research focus in phytology has been to understand how plants allocate leaf epidermal space to stomata in order to achieve an economic balance between the plant's carbon needs and water use. Here, we present a quantitative theoretical framework to predict allometric relationships between morphological stomatal traits in relation to leaf gas exchange and the required allocation of epidermal area to stomata. Our theoretical framework was derived from first principles of ...

Dose-optimal vaccine allocation over multiple populations

NARCIS (Netherlands)

L.E. Duijzer (Evelot); W.L. van Jaarsveld (Willem); J. Wallinga (Jacco); R. Dekker (Rommert)

2015-01-01

textabstractFor a large number of infectious diseases, vaccination is the most effective way to prevent an epidemic. However, the vaccine stockpile is hardly ever sufficient to treat the entire population, which brings about the challenge of vaccine allocation. To aid decision makers facing this

Passive Mobile Bandwidth Classification Using Short Lived TCP Connections

OpenAIRE

Michelinakis, Foivos; Kreitz, Gunnar; Petrocco, Riccardo; Zhang, Boxun; Widmer, Joerg

2015-01-01

Consumption of multimedia content is moving from a residential environment to mobile phones. Optimizing Quality of Experience—smooth, quick, and high quality playback—is more difficult in this setting, due to the highly dynamic nature of wireless links. A key requirement for achieving this goal is estimating the available bandwidth of mobile devices. Ideally, this should be done quickly and with low overhead. One challenge is that the majority of connections on mobiles are short-lived TCP con...

Bandwidth Study of the Microwave Reflectors with Rectangular Corrugations

Science.gov (United States)

Zhang, Liang; He, Wenlong; Donaldson, Craig R.; Cross, Adrian W.

2016-09-01

The mode-selective microwave reflector with periodic rectangular corrugations in the inner surface of a circular metallic waveguide is studied in this paper. The relations between the bandwidth and reflection coefficient for different numbers of corrugation sections were studied through a global optimization method. Two types of reflectors were investigated. One does not consider the phase response and the other does. Both types of broadband reflectors operating at W-band were machined and measured to verify the numerical simulations.

Optimal allocation of bulk water supplies to competing use sectors based on economic criterion - An application to the Chao Phraya River Basin, Thailand

Science.gov (United States)

Divakar, L.; Babel, M. S.; Perret, S. R.; Gupta, A. Das

2011-04-01

SummaryThe study develops a model for optimal bulk allocations of limited available water based on an economic criterion to competing use sectors such as agriculture, domestic, industry and hydropower. The model comprises a reservoir operation module (ROM) and a water allocation module (WAM). ROM determines the amount of water available for allocation, which is used as an input to WAM with an objective function to maximize the net economic benefits of bulk allocations to different use sectors. The total net benefit functions for agriculture and hydropower sectors and the marginal net benefit from domestic and industrial sectors are established and are categorically taken as fixed in the present study. The developed model is applied to the Chao Phraya basin in Thailand. The case study results indicate that the WAM can improve net economic returns compared to the current water allocation practices.

Glass Industry Bandwidth Analysis

Energy Technology Data Exchange (ETDEWEB)

Rue, David M. [Gas Technology Inst., Des Plaines, IL (United States)

2006-07-01

This is a study on energy use and potential savings, or "bandwidth" study, for several glassmaking processes. Intended to provide a realistic estimate of the potential amount of energy that can be saved in an industrial process, the "bandwidth" refers to the difference between the amount of energy that would be consumed in a process using commercially available technology versus the minimum amount of energy needed to achieve those same results.

Industrial Glass Bandwidth Analysis

Energy Technology Data Exchange (ETDEWEB)

Rue, David M. [Gas Technology Inst., Des Plaines, IL (United States); Servaites, James [Gas Technology Inst., Des Plaines, IL (United States); Wolf, Warren [Gas Technology Inst., Des Plaines, IL (United States)

2007-08-01

This is a study on energy use and potential savings, or "bandwidth" study, for several glassmaking processes. Intended to provide a realistic estimate of the potential amount of energy that can be saved in an industrial process, the "bandwidth" refers to the difference between the amount of energy that would be consumed in a process using commercially available technology versus the minimum amount of energy needed to achieve those same results.

Power Versus Bandwidth Efficiency in Wireless Communication: The Economic Perspective

OpenAIRE

Akhtman, Jos; Hanzo, Lajos

2009-01-01

We carry out a comprehensive analysis of a range of wireless network efficiency considerations. Firstly, we explore the properties and the implications of the power- versus bandwidth-efficiency criteria. Secondly, we perform a detailed top-down analysis of a typical commercial wireless network, which emphasizes the inherent differences between the aforementioned two efficiency metrics, while demonstrating that the appropriate choice of the network optimization criterion can have a profound ef...

Optimization Case Study: ISR Allocation in the Global Force Management Process

Science.gov (United States)

2016-09-01

assets available to meet the GCC requirements. The Joint Staff, in concert with USSTRATCOM, use many factors to prioritize allocation of assets to...include determining which GCC gets the assets and for how long. The decision influencers recommend a resource allocation solution based on experience...The allocation process illustrated in Figure 1 is the OV-1 diagram from the Joint Staff Global Force Management Enterprise Integration

Dynamic Intelligent Feedback Scheduling in Networked Control Systems

Directory of Open Access Journals (Sweden)

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.

Research on strategy and optimization method of PRT empty vehicles resource allocation based on traffic demand forecast

Science.gov (United States)

Xiang, Yu; Tao, Cheng

2018-05-01

During the operation of the personal rapid transit system(PRT), the empty vehicle resources is distributed unevenly because of different passenger demand. In order to maintain the balance between supply and demand, and to meet the passenger needs of the ride, PRT empty vehicle resource allocation model is constructed based on the future demand forecasted by historical demand in this paper. The improved genetic algorithm is implied in distribution of the empty vehicle which can reduce the customers waiting time and improve the operation efficiency of the PRT system so that all passengers can take the PRT vehicles in the shortest time. The experimental result shows that the improved genetic algorithm can allocate the empty vehicle from the system level optimally, and realize the distribution of the empty vehicle resources reasonably in the system.

Fund Allocation in Complex Rehabilitation Programs

Directory of Open Access Journals (Sweden)

Tarek Hegazy

2013-12-01

Full Text Available Civil Infrastructure assets require continuous renewal actions to sustain their operability and safety. Allocating limited renewal funds amongst numerous building components, however, represents a large-scale optimization problem and earlier efforts utilized genetic algorithms (GAs to optimize medium size problems yet exhibit steep performance degradation as problem size increases. In this research, after experimenting with various approaches of segmenting a large problem into multiple smaller sub-problems, clustered segmentation proved to be the most promising. The paper discusses the underlying life cycle analysis model, the various segmentation methods, and the optimization results using the improved GAs + clustered segmentation, which proved to be able to optimize asset renewals for 50,000 components with no noticeable performance degradation. The proposed method is simple and logical, and can be used on variety of asset types to improve infrastructure fund allocation. Future extension of this research is then highlighted.

Control and Optimization of Network in Networked Control System

Directory of Open Access Journals (Sweden)

Wang Zhiwen

2014-01-01

Full Text Available In order to avoid quality of performance (QoP degradation resulting from quality of service (QoS, the solution to network congestion from the point of control theory, which marks departure of our results from the existing methods, is proposed in this paper. The congestion and bandwidth are regarded as state and control variables, respectively; then, the linear time-invariant (LTI model between congestion state and bandwidth of network is established. Consequently, linear quadratic method is used to eliminate the network congestion by allocating bandwidth dynamically. At last, numerical simulation results are given to illustrate the effectiveness of this modeling approach.

Energy Efficient Resource Allocation for Cognitive Radios: A Generalized Sensing Analysis

KAUST Repository

Alabbasi, AbdulRahman; Rezki, Zouheir; Shihada, Basem

2014-01-01

In this paper, two resource allocation schemes for energy efficient cognitive radio systems are proposed. Our design considers resource allocation approaches that adopt spectrum sharing combined with soft-sensing information, adaptive sensing thresholds, and adaptive power to achieve an energy efficient system. An energy per good-bit metric is considered as an energy efficient objective function. A multi-carrier system, such as, orthogonal frequency division multiplexing, is considered in the framework. The proposed resource allocation schemes, using different approaches, are designated as sub-optimal and optimal. The sub-optimal approach is attained by optimizing over a channel inversion power policy. The optimal approach utilizes the calculus of variation theory to optimize a problem of instantaneous objective function subject to average and instantaneous constraints with respect to functional optimization variables. In addition to the analytical results, selected numerical results are provided to quantify the impact of soft-sensing information and the optimal adaptive sensing threshold on the system performance.

Energy Efficient Resource Allocation for Cognitive Radios: A Generalized Sensing Analysis

KAUST Repository

Alabbasi, Abdulrahman

2014-12-31

In this paper, two resource allocation schemes for energy efficient cognitive radio systems are proposed. Our design considers resource allocation approaches that adopt spectrum sharing combined with soft-sensing information, adaptive sensing thresholds, and adaptive power to achieve an energy efficient system. An energy per good-bit metric is considered as an energy efficient objective function. A multi-carrier system, such as, orthogonal frequency division multiplexing, is considered in the framework. The proposed resource allocation schemes, using different approaches, are designated as sub-optimal and optimal. The sub-optimal approach is attained by optimizing over a channel inversion power policy. The optimal approach utilizes the calculus of variation theory to optimize a problem of instantaneous objective function subject to average and instantaneous constraints with respect to functional optimization variables. In addition to the analytical results, selected numerical results are provided to quantify the impact of soft-sensing information and the optimal adaptive sensing threshold on the system performance.

Topology Optimized Photonic Wire Splitters

DEFF Research Database (Denmark)

Frandsen, Lars Hagedorn; Borel, Peter Ingo; Jensen, Jakob Søndergaard

2006-01-01

Photonic wire splitters have been designed using topology optimization. The splitters have been fabricated in silicon-on-insulator material and display broadband low-loss 3dB splitting in a bandwidth larger than 100 nm.......Photonic wire splitters have been designed using topology optimization. The splitters have been fabricated in silicon-on-insulator material and display broadband low-loss 3dB splitting in a bandwidth larger than 100 nm....

Banded all-optical OFDM super-channels with low-bandwidth receivers.

Science.gov (United States)

Song, Binhuang; Zhu, Chen; Corcoran, Bill; Zhuang, Leimeng; Lowery, Arthur James

2016-08-08

We propose a banded all-optical orthogonal frequency division multiplexing (AO-OFDM) transmission system based on synthesising a number of truncated sinc-shaped subcarriers for each sub-band. This approach enables sub-band by sub-band reception and therefore each receiver's electrical bandwidth can be significantly reduced compared with a conventional AO-OFDM system. As a proof-of-concept experiment, we synthesise 6 × 10-Gbaud subcarriers in both conventional and banded AO-OFDM systems. With a limited receiver electrical bandwidth, the experimental banded AO-OFDM system shows 2-dB optical signal to noise ratio (OSNR) benefit over conventional AO-OFDM at the 7%-overhead forward error correction (FEC) threshold. After transmission over 800-km of single-mode fiber, ≈3-dB improvement in Q-factor can be achieved at the optimal launch power at a cost of increasing the spectral width by 14%.

Real-Time Optimization for use in a Control Allocation System to Recover from Pilot Induced Oscillations

Science.gov (United States)

Leonard, Michael W.

2013-01-01

Integration of the Control Allocation technique to recover from Pilot Induced Oscillations (CAPIO) System into the control system of a Short Takeoff and Landing Mobility Concept Vehicle simulation presents a challenge because the CAPIO formulation requires that constrained optimization problems be solved at the controller operating frequency. We present a solution that utilizes a modified version of the well-known L-BFGS-B solver. Despite the iterative nature of the solver, the method is seen to converge in real time with sufficient reliability to support three weeks of piloted runs at the NASA Ames Vertical Motion Simulator (VMS) facility. The results of the optimization are seen to be excellent in the vast majority of real-time frames. Deficiencies in the quality of the results in some frames are shown to be improvable with simple termination criteria adjustments, though more real-time optimization iterations would be required.

Energy Efficient Power Allocation for Cognitive MIMO Channels

KAUST Repository

Sboui, Lokman

2016-01-06

Two major issues are facing today s wireless communications evolution: -Spectrum scarcity: Need for more bandwidth. As a solution, the Cognitive Radio (CR) paradigm, where secondary users (unlicensed) share the spectrum with licensed users, was introduced. -Energy consumption and CO2 emission: The ICT produces 2% of global CO2 emission (equivalent to the aviation industry emission). The cellular networks produces 0.2%. As solution energy efficient systems should be designed rather than traditional spectral efficient systems. In this work, an energy efficient power allocation framework based on maximizing the average EE per parallel channel is presented.

MDP-based resource allocation for triple-play transmission on xDSL systems

Science.gov (United States)

de Souza, Lamartine V.; de Carvalho, Glaucio H. S.; Cardoso, Diego L.; de Carvalho, Solon V.; Frances, Carlos R. L.; Costa, João C. W. A.; Riu, Jaume Rius i.

2007-09-01

Many broadband services are based on multimedia applications, such as voice over internet protocol (VoIP), video conferencing, video on demand (VoD), and internet protocol television (IPTV). The combination "triple-play" is often used with IPTV. It simply means offering voice, video and data. IPTV and others services uses digital broadband networks such as ADSL2+ (Asymmetric Digital Subscriber Line) and VDSL (Very High Rate DSL) to transmit the data. We have formulated a MDP (Markov Decision Process) for a triple-play transmission on DSL environment. In this paper, we establish the relationship between DSL transmission characteristics and its finite-state Markov model for a triple-play transmission system. This relationship can be used for a resource management for multimedia applications delivered through a broadband infrastructure. The solution to our optimization problem can be found using dynamic programming (DP) techniques, such as value iteration and its variants. Our study results in a transmission strategy that chooses the optimal resource allocation according the triple-play traffic requirements, defined in technical report TR-126 (Triple-Play Services Quality of Experience Requirements) from DSL Forum, minimizing quality of service (QoS) violations with respect to bandwidth. Three traffic classes (video, audio, and best effort internet data) are defined and analyzed. Our simulation results show parameters like as blocking probability for each class, link utilization and optimal control policies. The MDP-based approach provides a satisfactory way of resource management for a DSL system.

Improving the Bandwidth Selection in Kernel Equating

Science.gov (United States)

Andersson, Björn; von Davier, Alina A.

2014-01-01

We investigate the current bandwidth selection methods in kernel equating and propose a method based on Silverman's rule of thumb for selecting the bandwidth parameters. In kernel equating, the bandwidth parameters have previously been obtained by minimizing a penalty function. This minimization process has been criticized by practitioners…

The statistical bandwidth of Butterworth filters

Science.gov (United States)

Davy, J. L.; Dunn, I. P.

1987-06-01

The precision of standard architectural acoustic measurements is a function of the statistical bandwidth of the band pass filters used in the measurements. The International and United States Standards on octave and fractional octave-band filters which specify the band pass filters used in architectural acoustics measurements give the effective bandwidth, but unfortunately not the statistical bandwidth of the filters. Both these Standards are currently being revised and both revisions require the use of Butterworth filter characteristics. In this paper it is shown theoretically that the ratio of statistical bandwidth to effective bandwidth for an nth order Butterworth band pass filter is {2n}/{(2n-1)}. This is verified experimentally for third-octave third-order Butterworth band pass filters. It is also shown experimentally that this formula is approximately correct for some non-Butterworth third-octave third-order band pass filters. Because of the importance of Butterworth filters in the revised Standards, the theory of Butterworth filters is reviewed and the formulae for Butterworth filters given in both revised Standards are derived.

Dynamic Resource Allocation and QoS Control Capabilities of the Japanese Academic Backbone Network

Directory of Open Access Journals (Sweden)

Michihiro Aoki

2010-08-01

Full Text Available Dynamic resource control capabilities have become increasingly important for academic networks that must support big scientific research projects at the same time as less data intensive research and educational activities. This paper describes the dynamic resource allocation and QoS control capabilities of the Japanese academic backbone network, called SINET3, which supports a variety of academic applications with a wide range of network services. The article describes the network architecture, networking technologies, resource allocation, QoS control, and layer-1 bandwidth on-demand services. It also details typical services developed for scientific research, including the user interface, resource control, and management functions, and includes performance evaluations.

Risk and reliability allocation to risk control

International Nuclear Information System (INIS)

Vojnovic, D.; Kozuh, M.

1992-01-01

The risk allocation procedure is used as an analytical model to support the optimal decision making for reliability/availability improvement planning. Both levels of decision criteria, the plant risk measures and plant performance indices, are used in risk allocation procedure. Decision support system uses the multi objective decision making concept. (author) [sl

Application of an allocation methodology

International Nuclear Information System (INIS)

Youngblood, R.

1989-01-01

This paper presents a method for allocating resources to elements of a system for the purpose of achieving prescribed levels of defense-in-depth at minimal cost. The method makes extensive use of logic modelling. An analysis of a simplified high-level waste repository is used as an illustrative application of the method. It is shown that it is possible to allocate quality control costs (or demonstrate performance) in an optimal way over elements of a conceptual design

Bandwidth-Efficient Communication through 225 MHz Ka-band Relay Satellite Channel

Science.gov (United States)

Downey, Joseph; Downey, James; Reinhart, Richard C.; Evans, Michael Alan; Mortensen, Dale John

2016-01-01

The communications and navigation space infrastructure of the National Aeronautics and Space Administration (NASA) consists of a constellation of relay satellites (called Tracking and Data Relay Satellites (TDRS)) and a global set of ground stations to receive and deliver data to researchers around the world from mission spacecraft throughout the solar system. Planning is underway to enhance and transform the infrastructure over the coming decade. Key to the upgrade will be the simultaneous and efficient use of relay transponders to minimize cost and operations while supporting science and exploration spacecraft. Efficient use of transponders necessitates bandwidth efficient communications to best use and maximize data throughput within the allocated spectrum. Experiments conducted with NASA's Space Communication and Navigation (SCaN) Testbed on the International Space Station provides a unique opportunity to evaluate advanced communication techniques, such as bandwidth-efficient modulations, in an operational flight system. Demonstrations of these new techniques in realistic flight conditions provides critical experience and reduces the risk of using these techniques in future missions. Efficient use of spectrum is enabled by using high-order modulations coupled with efficient forward error correction codes. This paper presents a high-rate, bandwidth-efficient waveform operating over the 225 MHz Ka-band service of the TDRS System (TDRSS). The testing explores the application of Gaussian Minimum Shift Keying (GMSK), 248-phase shift keying (PSK) and 1632- amplitude PSK (APSK) providing over three bits-per-second-per-Hertz (3 bsHz) modulation combined with various LDPC encoding rates to maximize throughput. With a symbol rate of 200 Mbaud, coded data rates of 1000 Mbps were tested in the laboratory and up to 800 Mbps over the TDRS 225 MHz channel. This paper will present on the high-rate waveform design, channel characteristics, performance results, compensation

Energy-efficient relay selection and optimal power allocation for performance-constrained dual-hop variable-gain AF relaying

KAUST Repository

Zafar, Ammar

2013-12-01

This paper investigates the energy-efficiency enhancement of a variable-gain dual-hop amplify-and-forward (AF) relay network utilizing selective relaying. The objective is to minimize the total consumed power while keeping the end-to-end signal-to-noise-ratio (SNR) above a certain peak value and satisfying the peak power constraints at the source and relay nodes. To achieve this objective, an optimal relay selection and power allocation strategy is derived by solving the power minimization problem. Numerical results show that the derived optimal strategy enhances the energy-efficiency as compared to a benchmark scheme in which both the source and the selected relay transmit at peak power. © 2013 IEEE.

An alternative approach in operator allocation labor intensive manufacturing system: A three-phase methodology framework

Science.gov (United States)

Mat Rani, Ruzanita; Ismail, Wan Rosmanira

2013-04-01

Operator allocation is one of the most important decisions that can affect productivity in labor-intensive manufacturing system. Improper decision on operator allocation will reduce company's throughput and increase waste. Therefore, all factors such as operators' performance and operational constraints need to be considered in making the best operator allocation decision. Most of previous studies used two phases methodology. In two phases methodology, they used operational constraints and treated all operators to have the same level of performance for making decision on operator allocation. Therefore, in this paper a three-phase methodology is proposed to determine the optimal operator allocation. This methodology advances the existing approach on operator allocation by combining operators' performance and operational constraints. The methodology starts with evaluating the operators' performance. Then, it is followed with determining inputs and outputs for operator allocation alternatives and it ends with determining the optimal operator allocation. This paper will give ideas and directions to the management of the manufacturing company in determining the optimal operator allocation decision.

47 CFR 2.202 - Bandwidths.

Science.gov (United States)

2010-10-01

... three numerals and one letter. The letter occupies the position of the decimal point and represents the... quality desired Speech and music, M=4000, Bandwidth: 8000 Hz= 8 kHz 8K00A3E Sound broadcasting, single... desired Speech and music, M=4000, Bandwidth: 4000 Hz= 4 kHz 4K00R3E Sound broadcasting, single-sideband...

Energy-Efficient Power Allocation for MIMO-SVD Systems

KAUST Repository

Sboui, Lokman

2017-05-24

In this paper, we address the problem of energyefficient power allocation in MIMO systems. In fact, the widely adopted water-filling power allocation does not ensure the maximization of the energy efficiency (EE). Since the EE maximization is a non-convex problem, numerical methods based on fractional programming were introduced to find the optimal power solutions. In this paper, we present a novel and simple power allocation scheme based on the explicit expressions of the optimal power. We also present a low-complexity algorithm that complements the proposed scheme for low circuit-power regime. Furthermore, we analyze power-constrained and rate-constrained systems and present the corresponding optimal power control. In the numerical results, we show that the presented analytical expressions are accurate and that the algorithm converges within two iterations. We also show that as the number of antenna increases, the system becomes more energy-efficient. Also, a saturation of the EE is observed at high power budget and low minimal rate regimes.

An algorithm for routing optimization in DiffServ-aware MPLS networks

OpenAIRE

Luigi Atzori; Fabio D'Andreagiovanni; Carlo Mannino; Tatiana Onali

2010-01-01

This paper addresses the constrained-based routing problem in DiffServaware MPLS networks. We consider a dynamic context in which new requests appear over time, asking for reconfigurations of the previous allocation. In the classical approach, a multi-phase heuristic procedure is adopted: the new requests are evaluated considering available bandwidth; if the bandwidth is not sufficient, preemption and rerouting of one or more connections are performed in sequence. As an alternative, we propos...

Resource Allocation and Outpatient Appointment Scheduling Using Simulation Optimization

Directory of Open Access Journals (Sweden)

Carrie Ka Yuk Lin

2017-01-01

Full Text Available This paper studies the real-life problems of outpatient clinics having the multiple objectives of minimizing resource overtime, patient waiting time, and waiting area congestion. In the clinic, there are several patient classes, each of which follows different treatment procedure flow paths through a multiphase and multiserver queuing system with scarce staff and limited space. We incorporate the stochastic factors for the probabilities of the patients being diverted into different flow paths, patient punctuality, arrival times, procedure duration, and the number of accompanied visitors. We present a novel two-stage simulation-based heuristic algorithm to assess various tactical and operational decisions for optimizing the multiple objectives. In stage I, we search for a resource allocation plan, and in stage II, we determine a block appointment schedule by patient class and a service discipline for the daily operational level. We also explore the effects of the separate strategies and their integration to identify the best possible combination. The computational experiments are designed on the basis of data from a study of an ophthalmology clinic in a public hospital. Results show that our approach significantly mitigates the undesirable outcomes by integrating the strategies and increasing the resource flexibility at the bottleneck procedures without adding resources.

End-to-End Flow Control for Visual-Haptic Communication under Bandwidth Change

Science.gov (United States)

Yashiro, Daisuke; Tian, Dapeng; Yakoh, Takahiro

This paper proposes an end-to-end flow controller for visual-haptic communication. A visual-haptic communication system transmits non-real-time packets, which contain large-size visual data, and real-time packets, which contain small-size haptic data. When the transmission rate of visual data exceeds the communication bandwidth, the visual-haptic communication system becomes unstable owing to buffer overflow. To solve this problem, an end-to-end flow controller is proposed. This controller determines the optimal transmission rate of visual data on the basis of the traffic conditions, which are estimated by the packets for haptic communication. Experimental results confirm that in the proposed method, a short packet-sending interval and a short delay are achieved under bandwidth change, and thus, high-precision visual-haptic communication is realized.

Optimal allocation of energy sources for sustainable development in South Korea: Focus on the electric power generation industry

International Nuclear Information System (INIS)

Ahn, Joongha; Woo, JongRoul; Lee, Jongsu

2015-01-01

National energy planning has become increasingly complex owing to a pressing need to incorporate sustainability considerations. In this context, we applied least-cost and cost-risk optimization models to allocate energy sources for sustainable development in the Korean electric power generation industry. The least-cost model determined an electricity generation mix from 2012 to 2030 that incurs minimum generation cost to meet electricity demand. The cost-risk model determined electricity generation mixes in 2030 considering the risks associated with each energy source in order to lessen external risks. In deriving these optimal electricity generation mixes, we considered both conventional and renewable energy sources in conjunction with physical and policy constraints that realistically reflect Korean circumstances. Moreover, we accounted for CO 2 and external costs within the electricity generation costs for each energy source. For sustainable development in Korea, we conclude that a portion of the coal and gas in the electricity generation mix must be substituted with nuclear and renewable energy. Furthermore, we found that least-cost allocation is sub-optimal from cost-risk perspective and that it limits the adoption of renewables. Finally, we also discuss the implications of decisions taken by the Korean government regarding the electricity generation mix for next-generation energy planning to achieve sustainability. - Highlights: • Optimal least-cost/cost-risk energy mix for sustainable development in Korea. • We account for CO 2 and external costs of generation from each energy source. • Externalities and physical/policy constraints in Korea produce realistic energy mix. • Nuclear and renewables should replace coal and gas for sustainability in Korea. • Least-cost approach limits uptake of renewables and produces high-risk energy mix

Controlling Laser Plasma Instabilities Using Temporal Bandwidth

Science.gov (United States)

Tsung, Frank; Weaver, J.; Lehmberg, R.

2016-10-01

We are performing particle-in-cell simulations using the code OSIRIS to study the effects of laser plasma interactions in the presence of temporal bandwidth under conditions relevant to current and future experiments on the NIKE laser. Our simulations show that, for sufficiently large bandwidth (where the inverse bandwidth is comparable with the linear growth time), the saturation level, and the distribution of hot electrons, can be effected by the addition of temporal bandwidths (which can be accomplished in experiments using beam smoothing techniques such as ISI). We will quantify these effects and investigate higher dimensional effects such as laser speckles. This work is supported by DOE and NRL.

Continuous integration congestion cost allocation based on sensitivity

International Nuclear Information System (INIS)

Wu, Z.Q.; Wang, Y.N.

2004-01-01

Congestion cost allocation is a very important topic in congestion management. Allocation methods based on the Aumann-Shapley value use the discrete numerical integration method, which needs to solve the incremented OPF solution many times, and as such it is not suitable for practical application to large-scale systems. The optimal solution and its sensitivity change tendency during congestion removal using a DC optimal power flow (OPF) process is analysed. A simple continuous integration method based on the sensitivity is proposed for the congestion cost allocation. The proposed sensitivity analysis method needs a smaller computation time than the method based on using the quadratic method and inner point iteration. The proposed congestion cost allocation method uses a continuous integration method rather than discrete numerical integration. The method does not need to solve the incremented OPF solutions; which allows it use in large-scale systems. The method can also be used for AC OPF congestion management. (author)

Optimizing Water Allocation under Uncertain System Conditions for Water and Agriculture Future Scenarios in Alfeios River Basin (Greece—Part B: Fuzzy-Boundary Intervals Combined with Multi-Stage Stochastic Programming Model

Directory of Open Access Journals (Sweden)

Eleni Bekri

2015-11-01

Full Text Available Optimal water allocation within a river basin still remains a great modeling challenge for engineers due to various hydrosystem complexities, parameter uncertainties and their interactions. Conventional deterministic optimization approaches have given their place to stochastic, fuzzy and interval-parameter programming approaches and their hybrid combinations for overcoming these difficulties. In many countries, including Mediterranean countries, water resources management is characterized by uncertain, imprecise and limited data because of the absence of permanent measuring systems, inefficient river monitoring and fragmentation of authority responsibilities. A fuzzy-boundary-interval linear programming methodology developed by Li et al. (2010 is selected and applied in the Alfeios river basin (Greece for optimal water allocation under uncertain system conditions. This methodology combines an ordinary multi-stage stochastic programming with uncertainties expressed as fuzzy-boundary intervals. Upper- and lower-bound solution intervals for optimized water allocation targets and probabilistic water allocations and shortages are estimated under a baseline scenario and four water and agricultural policy future scenarios for an optimistic and a pessimistic attitude of the decision makers. In this work, the uncertainty of the random water inflows is incorporated through the simultaneous generation of stochastic equal-probability hydrologic scenarios at various inflow positions instead of using a scenario-tree approach in the original methodology.

Open-Loop Wide-Bandwidth Phase Modulation Techniques

Directory of Open Access Journals (Sweden)

Nitin Nidhi

2011-01-01

Full Text Available The ever-increasing growth in the bandwidth of wireless communication channels requires the transmitter to be wide-bandwidth and power-efficient. Polar and outphasing transmitter topologies are two promising candidates for such applications, in future. Both these architectures require a wide-bandwidth phase modulator. Open-loop phase modulation presents a viable solution for achieving wide-bandwidth operation. An overview of prior art and recent approaches for phase modulation is presented in this paper. Phase quantization noise cancellation was recently introduced to lower the out-of-band noise in a digital phase modulator. A detailed analysis on the impact of timing and quantization of the cancellation signal is presented. Noise generated by the transmitter in the receive band frequency poses another challenge for wide-bandwidth transmitter design. Addition of a noise transfer function notch, in a digital phase modulator, to reduce the noise in the receive band during phase modulation is described in this paper.

Fluid limits for Bandwidth-Sharing Networks with Impatience.

NARCIS (Netherlands)

Remerova, M.; Reed, J.; Zwart, A.P.

2014-01-01

Bandwidth-sharing networks as introduced by Roberts and Massoulié [Roberts JW, Massoulié L (1998) Bandwidth sharing and admission control for elastic traffic. Proc. ITC Specialist Seminar, Yokohama, Japan], Massoulié and Roberts [Massoulié L, Roberts JW (1999) Bandwidth sharing: Objectives and

Channel allocation and rate adaptation for relayed transmission over correlated fading channels

KAUST Repository

Hwang, Kyusung

2009-09-01

We consider, in this paper, channel allocation and rate adaptation scheme for relayed transmission over correlated fading channels via cross-layer design. Specifically, jointly considering the data link layer buffer occupancy and channel quality at both the source and relay nodes, we develop an optimal channel allocation and rate adaptation policy for a dual-hop relayed transmission. As such the overall transmit power for the relayed system is minimized while a target packet dropping rate (PDR) due to buffer over flows is guaranteed. In order to find such an optimal policy, the channel allocation and rate adaptation transmission framework is formulated as a constraint Markov decision process (CMDP). The PDR performance of the optimal policy is compared with that of two conventional suboptimal schemes, namely the channel quality based and the buffer occupancy based channel allocation schemes. Numerical results show that for a given power budget, the optimal scheme requires significantly less power than the conventional schemes in order to maintain a target PDR. ©2009 IEEE.

Practical continuous-variable quantum key distribution without finite sampling bandwidth effects.

Science.gov (United States)

Li, Huasheng; Wang, Chao; Huang, Peng; Huang, Duan; Wang, Tao; Zeng, Guihua

2016-09-05

In a practical continuous-variable quantum key distribution system, finite sampling bandwidth of the employed analog-to-digital converter at the receiver's side may lead to inaccurate results of pulse peak sampling. Then, errors in the parameters estimation resulted. Subsequently, the system performance decreases and security loopholes are exposed to eavesdroppers. In this paper, we propose a novel data acquisition scheme which consists of two parts, i.e., a dynamic delay adjusting module and a statistical power feedback-control algorithm. The proposed scheme may improve dramatically the data acquisition precision of pulse peak sampling and remove the finite sampling bandwidth effects. Moreover, the optimal peak sampling position of a pulse signal can be dynamically calibrated through monitoring the change of the statistical power of the sampled data in the proposed scheme. This helps to resist against some practical attacks, such as the well-known local oscillator calibration attack.

Equitable fund allocation, an economical approach for sustainable waste load allocation.

Science.gov (United States)

Ashtiani, Elham Feizi; Niksokhan, Mohammad Hossein; Jamshidi, Shervin

2015-08-01

This research aims to study a novel approach for waste load allocation (WLA) to meet environmental, economical, and equity objectives, simultaneously. For this purpose, based on a simulation-optimization model developed for Haraz River in north of Iran, the waste loads are allocated according to discharge permit market. The non-dominated solutions are initially achieved through multiobjective particle swarm optimization (MOPSO). Here, the violation of environmental standards based on dissolved oxygen (DO) versus biochemical oxidation demand (BOD) removal costs is minimized to find economical total maximum daily loads (TMDLs). This can save 41% in total abatement costs in comparison with the conventional command and control policy. The BOD discharge permit market then increases the revenues to 45%. This framework ensures that the environmental limits are fulfilled but the inequity index is rather high (about 4.65). For instance, the discharge permit buyer may not be satisfied about the equity of WLA. Consequently, it is recommended that a third party or institution should be in charge of reallocating the funds. It means that the polluters which gain benefits by unfair discharges should pay taxes (or funds) to compensate the losses of other polluters. This intends to reduce the costs below the required values of the lowest inequity index condition. These compensations of equitable fund allocation (EFA) may help to reduce the dissatisfactions and develop WLA policies. It is concluded that EFA in integration with water quality trading (WQT) is a promising approach to meet the objectives.

Reliable IoT Storage: Minimizing Bandwidth Use in Storage Without Newcomer Nodes

DEFF Research Database (Denmark)

Zhao, Xiaobo; Lucani Rötter, Daniel Enrique; Shen, Xiaohong

2018-01-01

This letter characterizes the optimal policies for bandwidth use and storage for the problem of distributed storage in Internet of Things (IoT) scenarios, where lost nodes cannot be replaced by new nodes as is typically assumed in Data Center and Cloud scenarios. We develop an information flow...... model that captures the overall process of data transmission between IoT devices, from the initial preparation stage (generating redundancy from the original data) to the different repair stages with fewer and fewer devices. Our numerical results show that in a system with 10 nodes, the proposed optimal...

Can observed ecosystem responses to elevated CO2 and N fertilisation be explained by optimal plant C allocation?

Science.gov (United States)

Stocker, Benjamin; Prentice, I. Colin

2016-04-01

The degree to which nitrogen availability limits the terrestrial C sink under rising CO2 is a key uncertainty in carbon cycle and climate change projections. Results from ecosystem manipulation studies and meta-analyses suggest that plant C allocation to roots adjusts dynamically under varying degrees of nitrogen availability and other soil fertility parameters. In addition, the ratio of biomass production to GPP appears to decline under nutrient scarcity. This reflects increasing plant C export into the soil and to symbionts (Cex) with decreasing nutrient availability. Cex is consumed by an array of soil organisms and may imply an improvement of nutrient availability to the plant. These concepts are left unaccounted for in Earth system models. We present a model for the coupled cycles of C and N in grassland ecosystems to explore optimal plant C allocation under rising CO2 and its implications for the ecosystem C balance. The model follows a balanced growth approach, accounting for the trade-offs between leaf versus root growth and Cex in balancing C fixation and N uptake. We further model a plant-controlled rate of biological N fixation (BNF) by assuming that Cex is consumed by N2-fixing processes if the ratio of Nup:Cex falls below the inverse of the C cost of N2-fixation. The model is applied at two temperate grassland sites (SwissFACE and BioCON), subjected to factorial treatments of elevated CO2 (FACE) and N fertilization. Preliminary simulation results indicate initially increased N limitation, evident by increased relative allocation to roots and Cex. Depending on the initial state of N availability, this implies a varying degree of aboveground growth enhancement, generally consistent with observed responses. On a longer time scale, ecosystems are progressively released from N limitation due tighter N cycling. Allowing for plant-controlled BNF implies a quicker release from N limitation and an adjustment to more open N cycling. In both cases, optimal plant

Optimizing resource allocation for breast cancer prevention and care among Hong Kong Chinese women.

Science.gov (United States)

Wong, Irene O L; Tsang, Janice W H; Cowling, Benjamin J; Leung, Gabriel M

2012-09-15

Recommendations about funding of interventions through the full spectrum of the disease often have been made in isolation. The authors of this report optimized budgetary allocations by comparing cost-effectiveness data for different preventive and management strategies throughout the disease course for breast cancer in Hong Kong (HK) Chinese women. Nesting a state-transition Markov model within a generalized cost-effectiveness analytic framework, costs and quality-adjusted life-years (QALYs) were compared to estimate average cost-effectiveness ratios for the following interventions at the population level: biennial mass mammography (ages 40-69 years or ages 40-79 years), reduced waiting time for postoperative radiotherapy (by 15% or by 25%), adjuvant endocrine therapy (either upfront aromatase inhibitor [AI] therapy or sequentially with tamoxifen followed by AI) in postmenopausal women with estrogen receptor-positive disease, targeted immunotherapy in those with tumors that over express human epidermal growth factor receptor 2, and enhanced palliative services (either at home or as an inpatient). Usual care for eligible patients in the public sector was the comparator. In descending order, the optimal allocation of additional resources for breast cancer would be the following: a 25% reduction in waiting time for postoperative radiotherapy (in US dollars: $5000 per QALY); enhanced, home-based palliative care ($7105 per QALY); adjuvant, sequential endocrine therapy ($17,963 per QALY); targeted immunotherapy ($62,092 per QALY); and mass mammography screening of women ages 40 to 69 years ($72,576 per QALY). Given the lower disease risk and different age profiles of patients in HK Chinese, among other newly emergent and emerging economies with similar transitioning epidemiologic profiles, the current findings provided direct evidence to support policy decisions that may be dissimilar to current Western practice. Copyright © 2012 American Cancer Society.

Directing Traffic: Managing Internet Bandwidth Fairly

Science.gov (United States)

Paine, Thomas A.; Griggs, Tyler J.

2008-01-01

Educational institutions today face budgetary restraints and scarce resources, complicating the decision of how to allot bandwidth for campus network users. Additionally, campus concerns over peer-to-peer networking (specifically outbound Internet traffic) have increased because of bandwidth and copyright issues. In this article, the authors…

Application of an allocation methodology

International Nuclear Information System (INIS)

Youngblood, R.; de Oliveira, L.F.S.

1989-01-01

This paper presents a method for allocating resources to elements of a system for the purpose of achieving prescribed levels of defense-in-depth at minimal cost. The method makes extensive use of logic modelling. An analysis of a simplified high-level waste repository is used as an illustrative application of the method. It is shown that it is possible to allocate quality control costs (or demonstrated performance) in an optimal way over elements of a conceptual design. 6 refs., 3 figs., 2 tabs

Optimal Dimensioning of Broadband Integrated Services Digital Network

Directory of Open Access Journals (Sweden)

Zdenka Chmelikova

2005-01-01

Full Text Available Tasks of this paper are research of input flow statistic parametres influence and parameters demands relating to VP (Virtual Path or VC (Virtual Channel dimensioning. However it is necessary to consider different time of flow arrival and differend time of holding time during connection level. Process of input flow arrival is considered as Poisson process. Holding time is considered as exponential function. Permanent allocation of VP is made by separate VP, where each of VPs enable transmitting offered laod with explicit bandwidth and explicit loss. The mathematic model was created to verify the above mentioned dependences for different types of telecomunications signals and different input flows. "Comnet III" software was selected for experimental verification of process optimization. The simulation model was based on thiss software, which simulate ATM network traffic in behalf of different input flow.

Optimal Allocation of the Irrigation Water Through a Non Linear Mathematical Model

Directory of Open Access Journals (Sweden)

P. Rubino

2008-09-01

Full Text Available A study on the optimal allocation of the irrigation water among 9 crops (autumnal and spring sugar beet, spring and summer grain maize, dry and shell bean, eggplant, pepper and processing tomato has been carried out, utilizing experimental data of yield response to irrigation obtained in different years in Southern Italy (Policoro MT, 40° 12’ Northern Lat.; 16° 40’Western Long.. Fitting Mitscherlich’s equation modified by Giardini and Borin to the experimental data of each crop, the curve response parameters have been calculated: A = maximum achievable yield in the considered area (t ha-1; b = extra-irrigation water used by the crop (m3 ha-1; c = water action factor (ha m- 3; K, calculated only for tomato crop. ,decreasing factor due to the water exceeding the optimal seasonal irrigation volume (100% of the Crop Maximum Evapotranspiration less effective rainfall, ETMlr. The A values, using the prices of the agricultural produces and the irrigation water tariffs applied by the Consorzio Irriguo della Capitanata, have been converted in Value of Production (VP less the fixed and variable irrigation costs (VPlic. The equation parameters were used in a non linear mathematical model written in GAMS (General Algebraic Modelling System, in order to define the best irrigation water allocation amongst the 9 crops across the entire range of water availability and the volume of maximum economical advantage, hypothesising that each crop occupied the same surface (1 ha. This seasonal irrigation volume, that corresponded to the maximum total VPlic, was equal to 37000 m3. Moreover, the model allowed to define the best irrigation water distribution among the crops also for total available volumes lower than that of maximum economical advantage (37000 m3. Finally, it has been underlined that the vegetable crops should be irrigated with seasonal irrigation volumes equal to 100% of the ETM, whereas the summer and spring maize and the autumnal and spring

Land use allocation model considering climate change impact

Science.gov (United States)

Lee, D. K.; Yoon, E. J.; Song, Y. I.

2017-12-01

In Korea, climate change adaptation plans are being developed for each administrative district based on impact assessments constructed in various fields. This climate change impact assessments are superimposed on the actual space, which causes problems in land use allocation because the spatial distribution of individual impacts may be different each other. This implies that trade-offs between climate change impacts can occur depending on the composition of land use. Moreover, the actual space is complexly intertwined with various factors such as required area, legal regulations, and socioeconomic values, so land use allocation in consideration of climate change can be very difficult problem to solve (Liu et al. 2012; Porta et al. 2013).Optimization techniques can generate a sufficiently good alternatives for land use allocation at the strategic level if only the fitness function of relationship between impact and land use composition are derived. It has also been noted that land use optimization model is more effective than the scenario-based prediction model in achieving the objectives for problem solving (Zhang et al. 2014). Therefore in this study, we developed a quantitative tool, MOGA (Multi Objective Genetic Algorithm), which can generate a comprehensive land use allocations considering various climate change impacts, and apply it to the Gangwon-do in Korea. Genetic Algorithms (GAs) are the most popular optimization technique to address multi-objective in land use allocation. Also, it allows for immediate feedback to stake holders because it can run a number of experiments with different parameter values. And it is expected that land use decision makers and planners can formulate a detailed spatial plan or perform additional analysis based on the result of optimization model. Acknowledgments: This work was supported by the Korea Ministry of Environment (MOE) as "Climate Change Correspondence Program (Project number: 2014001310006)"

Optimal Golomb Ruler Sequences Generation for Optical WDM Systems: A Novel Parallel Hybrid Multi-objective Bat Algorithm

Science.gov (United States)

Bansal, Shonak; Singh, Arun Kumar; Gupta, Neena

2017-02-01

In real-life, multi-objective engineering design problems are very tough and time consuming optimization problems due to their high degree of nonlinearities, complexities and inhomogeneity. Nature-inspired based multi-objective optimization algorithms are now becoming popular for solving multi-objective engineering design problems. This paper proposes original multi-objective Bat algorithm (MOBA) and its extended form, namely, novel parallel hybrid multi-objective Bat algorithm (PHMOBA) to generate shortest length Golomb ruler called optimal Golomb ruler (OGR) sequences at a reasonable computation time. The OGRs found their application in optical wavelength division multiplexing (WDM) systems as channel-allocation algorithm to reduce the four-wave mixing (FWM) crosstalk. The performances of both the proposed algorithms to generate OGRs as optical WDM channel-allocation is compared with other existing classical computing and nature-inspired algorithms, including extended quadratic congruence (EQC), search algorithm (SA), genetic algorithms (GAs), biogeography based optimization (BBO) and big bang-big crunch (BB-BC) optimization algorithms. Simulations conclude that the proposed parallel hybrid multi-objective Bat algorithm works efficiently as compared to original multi-objective Bat algorithm and other existing algorithms to generate OGRs for optical WDM systems. The algorithm PHMOBA to generate OGRs, has higher convergence and success rate than original MOBA. The efficiency improvement of proposed PHMOBA to generate OGRs up to 20-marks, in terms of ruler length and total optical channel bandwidth (TBW) is 100 %, whereas for original MOBA is 85 %. Finally the implications for further research are also discussed.

Pollution permits allocation and imperfect competition; Allocation de permis de pollution et concurrence imparfaite

Energy Technology Data Exchange (ETDEWEB)

Schwartz, S.

2004-12-15

The aim of this thesis is to highlight the imperfections on the permits markets and to analyze their consequences on markets' efficiency. More precisely, we try to identify the implications of the initial allocation of permits when such imperfections are present. We try to draw some conclusions for the regulator concerning the different forms of the permits' allocation. After having described and compared these forms, we define in which circumstances the initial allocation matters in terms of efficiency. Then, we study different forms of imperfections. First, we take into account the information asymmetry between firms and the regulator and we define an optimal mechanism to sell pollution permits. Then, we analyze a market power on a differentiated pollution permits market. At last, we study the exclusionary manipulation of pollution permits market. (author)

Optimal Plant Carbon Allocation Implies a Biological Control on Nitrogen Availability

Science.gov (United States)

Prentice, I. C.; Stocker, B. D.

2015-12-01

The degree to which nitrogen availability limits the terrestrial C sink under rising CO2 is a key uncertainty in carbon cycle and climate change projections. Results from ecosystem manipulation studies and meta-analyses suggest that plant C allocation to roots adjusts dynamically under varying degrees of nitrogen availability and other soil fertility parameters. In addition, the ratio of biomass production to GPP appears to decline under nutrient scarcity. This reflects increasing plant C exudation into the soil (Cex) with decreasing nutrient availability. Cex is consumed by an array of soil organisms and may imply an improvement of nutrient availability to the plant. Thus, N availability is under biological control, but incurs a C cost. In spite of clear observational support, this concept is left unaccounted for in Earth system models. We develop a model for the coupled cycles of C and N in terrestrial ecosystems to explore optimal plant C allocation under rising CO2 and its implications for the ecosystem C balance. The model follows a balanced growth approach, accounting for the trade-offs between leaf versus root growth and Cex in balancing C fixation and N uptake. We assume that Cex is proportional to root mass, and that the ratio of N uptake (Nup) to Cex is proportional to inorganic N concentration in the soil solution. We further assume that Cex is consumed by N2-fixing processes if the ratio of Nup:Cex falls below the inverse of the C cost of N2-fixation. Our analysis thereby accounts for the feedbacks between ecosystem C and N cycling and stoichiometry. We address the question of how the plant C economy will adjust under rising atmospheric CO2 and what this implies for the ecosystem C balance and the degree of N limitation.

An optimized approach for simultaneous horizontal data fragmentation and allocation in Distributed Database Systems (DDBSs).

Science.gov (United States)

Amer, Ali A; Sewisy, Adel A; Elgendy, Taha M A

2017-12-01

With the substantial ever-upgrading advancement in data and information management field, Distributed Database System (DDBS) is still proven to be the most growingly-demanded tool to handle the accompanied constantly-piled volumes of data. However, the efficiency and adequacy of DDBS is profoundly correlated with the reliability and precision of the process in which DDBS is set to be designed. As for DDBS design, thus, several strategies have been developed, in literature, to be used in purpose of promoting DDBS performance. Off these strategies, data fragmentation, data allocation and replication, and sites clustering are the most immensely-used efficacious techniques that otherwise DDBS design and rendering would be prohibitively expensive. On one hand, an accurate well-architected data fragmentation and allocation is bound to incredibly increase data locality and promote the overall DDBS throughputs. On the other hand, finding a practical sites clustering process is set to contribute remarkably in reducing the overall Transmission Costs (TC). Consequently, consolidating all these strategies into one single work is going to undoubtedly satisfy a massive growth in DDBS influence. In this paper, therefore, an optimized heuristic horizontal fragmentation and allocation approach is meticulously developed. All the drawn-above strategies are elegantly combined into a single effective approach so as to an influential solution for DDBS productivity promotion is set to be markedly fulfilled. Most importantly, an internal and external evaluations are extensively illustrated. Obviously, findings of conducted experiments have maximally been recorded to be in favor of DDBS performance betterment.

Learn-and-Adapt Stochastic Dual Gradients for Network Resource Allocation

OpenAIRE

Chen, Tianyi; Ling, Qing; Giannakis, Georgios B.

2017-01-01

Network resource allocation shows revived popularity in the era of data deluge and information explosion. Existing stochastic optimization approaches fall short in attaining a desirable cost-delay tradeoff. Recognizing the central role of Lagrange multipliers in network resource allocation, a novel learn-and-adapt stochastic dual gradient (LA-SDG) method is developed in this paper to learn the sample-optimal Lagrange multiplier from historical data, and accordingly adapt the upcoming resource...

Near optimal power allocation algorithm for OFDM-based cognitive using adaptive relaying strategy

KAUST Repository

Soury, Hamza; Bader, Faouzi; Shaat, Musbah M R; Alouini, Mohamed-Slim

2012-01-01

Relayed transmission increases the coverage and achievable capacity of communication systems. Adaptive relaying scheme is a relaying technique by which the benefits of the amplifying or decode and forward techniques can be achieved by switching the forwarding technique according to the quality of the signal. A cognitive Orthogonal Frequency-Division Multiplexing (OFDM) based adaptive relaying protocol is considered in this paper. The objective is to maximize the capacity of the cognitive radio system while ensuring that the interference introduced to the primary user is below the tolerated limit. A Near optimal power allocation in the source and the relay is presented for two pairing techniques such that the matching and random pairing. The simulation results confirm the efficiency of the proposed adaptive relaying protocol, and the consequence of choice of pairing technique. © 2012 ICST.

A Novel Optimal Joint Resource Allocation Method in Cooperative Multicarrier Networks: Theory and Practice

Directory of Open Access Journals (Sweden)

Yuan Gao

2016-04-01

Full Text Available With the increasing demands for better transmission speed and robust quality of service (QoS, the capacity constrained backhaul gradually becomes a bottleneck in cooperative wireless networks, e.g., in the Internet of Things (IoT scenario in joint processing mode of LTE-Advanced Pro. This paper focuses on resource allocation within capacity constrained backhaul in uplink cooperative wireless networks, where two base stations (BSs equipped with single antennae serve multiple single-antennae users via multi-carrier transmission mode. In this work, we propose a novel cooperative transmission scheme based on compress-and-forward with user pairing to solve the joint mixed integer programming problem. To maximize the system capacity under the limited backhaul, we formulate the joint optimization problem of user sorting, subcarrier mapping and backhaul resource sharing among different pairs (subcarriers for users. A novel robust and efficient centralized algorithm based on alternating optimization strategy and perfect mapping is proposed. Simulations show that our novel method can improve the system capacity significantly under the constraint of the backhaul resource compared with the blind alternatives.

Joint Power Allocation for Multicast Systems with Physical-Layer Network Coding

Directory of Open Access Journals (Sweden)

Zhu Wei-Ping

2010-01-01

Full Text Available This paper addresses the joint power allocation issue in physical-layer network coding (PLNC of multicast systems with two sources and two destinations communicating via a large number of distributed relays. By maximizing the achievable system rate, a constrained optimization problem is first formulated to jointly allocate powers for the source and relay terminals. Due to the nonconvex nature of the cost function, an iterative algorithm with guaranteed convergence is developed to solve the joint power allocation problem. As an alternative, an upper bound of the achievable rate is also derived to modify the original cost function in order to obtain a convex optimization solution. This approximation is shown to be asymptotically optimal in the sense of maximizing the achievable rate. It is confirmed through Monte Carlo simulations that the proposed joint power allocation schemes are superior to the existing schemes in terms of achievable rate and cumulative distribution function (CDF.

Resource Allocation and Cluster Formation for Imperfect NOMA in DL/UL Decoupled HetNets

KAUST Repository

Celik, Abdulkadir; Radaydeh, Redha; Al-Qahtani, Fawaz; Abd El-Malek, Ahmed H.; Alouini, Mohamed-Slim

2017-01-01

Being capable of serving multiple users with the same radio resource, non-orthogonal multiple access (NOMA) can provide desirable performance enhancements in a fair and spectral efficient manner. In this paper, we investigate the resource allocation (RA) and cluster formation (CF) aspects of NOMA for downlink (DL) uplink (UL) decoupled (DUDe) heterogeneous networks (HetNets). A non-ideal NOMA scheme is considered with power disparity and sensitivity constraints (PDSCs), delay tolerance, and residual interference after cancellation. Taking the PDSCs into account, we analytically show that using the DL decoding order limits UL-NOMA performance by that of OMA, while employing an inverse order result in a performance gain that is mainly determined by the channel gain disparity of users. Thereafter, a generic CF method is proposed for any type of user graph, which iteratively forms clusters using Blossom algorithm. Finally, highly non-convex RA problem is converted into a convex form by employing geometric programming (GP) where power and bandwidth are optimized to maximize network sumrate and max-min fairness objectives.

Resource Allocation and Cluster Formation for Imperfect NOMA in DL/UL Decoupled HetNets

KAUST Repository

Celik, Abdulkadir

2017-04-15

Being capable of serving multiple users with the same radio resource, non-orthogonal multiple access (NOMA) can provide desirable performance enhancements in a fair and spectral efficient manner. In this paper, we investigate the resource allocation (RA) and cluster formation (CF) aspects of NOMA for downlink (DL) uplink (UL) decoupled (DUDe) heterogeneous networks (HetNets). A non-ideal NOMA scheme is considered with power disparity and sensitivity constraints (PDSCs), delay tolerance, and residual interference after cancellation. Taking the PDSCs into account, we analytically show that using the DL decoding order limits UL-NOMA performance by that of OMA, while employing an inverse order result in a performance gain that is mainly determined by the channel gain disparity of users. Thereafter, a generic CF method is proposed for any type of user graph, which iteratively forms clusters using Blossom algorithm. Finally, highly non-convex RA problem is converted into a convex form by employing geometric programming (GP) where power and bandwidth are optimized to maximize network sumrate and max-min fairness objectives.

Allocating Resources to Enhance Resilience, with Application to Superstorm Sandy and an Electric Utility.

Science.gov (United States)

MacKenzie, Cameron A; Zobel, Christopher W

2016-04-01

This article constructs a framework to help a decisionmaker allocate resources to increase his or her organization's resilience to a system disruption, where resilience is measured as a function of the average loss per unit time and the time needed to recover full functionality. Enhancing resilience prior to a disruption involves allocating resources from a fixed budget to reduce the value of one or both of these characteristics. We first look at characterizing the optimal resource allocations associated with several standard allocation functions. Because the resources are being allocated before the disruption, however, the initial loss and recovery time may not be known with certainty. We thus also apply the optimal resource allocation model for resilience to three models of uncertain disruptions: (1) independent probabilities, (2) dependent probabilities, and (3) unknown probabilities. The optimization model is applied to an example of increasing the resilience of an electric power network following Superstorm Sandy. © 2015 Society for Risk Analysis.

A practical approach for solving multi-objective reliability redundancy allocation problems using extended bare-bones particle swarm optimization

International Nuclear Information System (INIS)

Zhang, Enze; Wu, Yifei; Chen, Qingwei

2014-01-01

This paper proposes a practical approach, combining bare-bones particle swarm optimization and sensitivity-based clustering for solving multi-objective reliability redundancy allocation problems (RAPs). A two-stage process is performed to identify promising solutions. Specifically, a new bare-bones multi-objective particle swarm optimization algorithm (BBMOPSO) is developed and applied in the first stage to identify a Pareto-optimal set. This algorithm mainly differs from other multi-objective particle swarm optimization algorithms in the parameter-free particle updating strategy, which is especially suitable for handling the complexity and nonlinearity of RAPs. Moreover, by utilizing an approach based on the adaptive grid to update the global particle leaders, a mutation operator to improve the exploration ability and an effective constraint handling strategy, the integrated BBMOPSO algorithm can generate excellent approximation of the true Pareto-optimal front for RAPs. This is followed by a data clustering technique based on difference sensitivity in the second stage to prune the obtained Pareto-optimal set and obtain a small, workable sized set of promising solutions for system implementation. Two illustrative examples are presented to show the feasibility and effectiveness of the proposed approach

Climate, Agriculture, Energy and the Optimal Allocation of Global Land Use

Science.gov (United States)

Steinbuks, J.; Hertel, T. W.

2011-12-01

The allocation of the world's land resources over the course of the next century has become a pressing research question. Continuing population increases, improving, land-intensive diets amongst the poorest populations in the world, increasing production of biofuels and rapid urbanization in developing countries are all competing for land even as the world looks to land resources to supply more environmental services. The latter include biodiversity and natural lands, as well as forests and grasslands devoted to carbon sequestration. And all of this is taking place in the context of faster than expected climate change which is altering the biophysical environment for land-related activities. The goal of the paper is to determine the optimal profile for global land use in the context of growing commercial demands for food and forest products, increasing non-market demands for ecosystem services, and more stringent GHG mitigation targets. We then seek to assess how the uncertainty associated with the underlying biophysical and economic processes influences this optimal profile of land use, in light of potential irreversibility in these decisions. We develop a dynamic long-run, forward-looking partial equilibrium framework in which the societal objective function being maximized places value on food production, liquid fuels (including biofuels), timber production, forest carbon and biodiversity. Given the importance of land-based emissions to any GHG mitigation strategy, as well as the potential impacts of climate change itself on the productivity of land in agriculture, forestry and ecosystem services, we aim to identify the optimal allocation of the world's land resources, over the course of the next century, in the face of alternative GHG constraints. The forestry sector is characterized by multiple forest vintages which add considerable computational complexity in the context of this dynamic analysis. In order to solve this model efficiently, we have employed the

High-bandwidth memory interface

CERN Document Server

Kim, Chulwoo; Song, Junyoung

2014-01-01

This book provides an overview of recent advances in memory interface design at both the architecture and circuit levels. Coverage includes signal integrity and testing, TSV interface, high-speed serial interface including equalization, ODT, pre-emphasis, wide I/O interface including crosstalk, skew cancellation, and clock generation and distribution. Trends for further bandwidth enhancement are also covered.   • Enables readers with minimal background in memory design to understand the basics of high-bandwidth memory interface design; • Presents state-of-the-art techniques for memory interface design; • Covers memory interface design at both the circuit level and system architecture level.

Dose-optimal vaccine allocation over multiple populations

OpenAIRE

Duijzer, Evelot; Jaarsveld, Willem; Wallinga, Jacco; Dekker, Rommert

2015-01-01

textabstractFor a large number of infectious diseases, vaccination is the most effective way to prevent an epidemic. However, the vaccine stockpile is hardly ever sufficient to treat the entire population, which brings about the challenge of vaccine allocation. To aid decision makers facing this challenge, we provide insights into the structure of this problem. We first investigate the dependence of health benefit on the fraction of people that receive vaccination, where we define health bene...

Bandwidth Assessment for MultiRotor UAVs

Directory of Open Access Journals (Sweden)

Ferrarese Gastone

2017-06-01

Full Text Available This paper is a technical note about the theoretical evaluation of the bandwidth of multirotor helicopters. Starting from a mathematical linear model of the dynamics of a multirotor aircraft, the transfer functions of the state variables that deeply affect the stability characteristics of the aircraft are obtained. From these transfer functions, the frequency response analysis of the system is effected. After this analysis, the bandwidth of the system is defined. This result is immediately utilized for the design of discrete PID controllers for hovering flight stabilization. Numeric simulations are shown to demonstrate that the knowledge of the bandwidth is a valid aid in the design of flight control systems of these machines.

New resource allocation scheme for cognitive relay networks with opportunistic access

KAUST Repository

Zafar, Ammar

2012-06-01

In this paper, a new resource allocation scheme to minimize Symbol Error rate (SER) for relay assisted cognitive radio networks is studied. A cognitive relay network with amplify-and-forward (AF) fixed gain relays and opportunistic access to the licensed spectrum is considered. The SER objective function and the optimization constraints are derived first. The resource allocation algorithm is then derived using the Langrangian multiplier method. Closed form expressions are derived for the source and relay powers and, symbol time. Analytical results show that the optimal power allocation follows an extended water-filling solution. © 2012 IEEE.

Designing equitable antiretroviral allocation strategies in resource-constrained countries.

Directory of Open Access Journals (Sweden)

David P Wilson

2005-02-01

Full Text Available Recently, a global commitment has been made to expand access to antiretrovirals (ARVs in the developing world. However, in many resource-constrained countries the number of individuals infected with HIV in need of treatment will far exceed the supply of ARVs, and only a limited number of health-care facilities (HCFs will be available for ARV distribution. Deciding how to allocate the limited supply of ARVs among HCFs will be extremely difficult. Resource allocation decisions can be made on the basis of many epidemiological, ethical, or preferential treatment priority criteria.Here we use operations research techniques, and we show how to determine the optimal strategy for allocating ARVs among HCFs in order to satisfy the equitable criterion that each individual infected with HIV has an equal chance of receiving ARVs. We present a novel spatial mathematical model that includes heterogeneity in treatment accessibility. We show how to use our theoretical framework, in conjunction with an equity objective function, to determine an optimal equitable allocation strategy (OEAS for ARVs in resource-constrained regions. Our equity objective function enables us to apply the egalitarian principle of equity with respect to access to health care. We use data from the detailed ARV rollout plan designed by the government of South Africa to determine an OEAS for the province of KwaZulu-Natal. We determine the OEAS for KwaZulu-Natal, and we then compare this OEAS with two other ARV allocation strategies: (i allocating ARVs only to Durban (the largest urban city in KwaZulu-Natal province and (ii allocating ARVs equally to all available HCFs. In addition, we compare the OEAS to the current allocation plan of the South African government (which is based upon allocating ARVs to 17 HCFs. We show that our OEAS significantly improves equity in treatment accessibility in comparison with these three ARV allocation strategies. We also quantify how the size of the

An integrated model for part-operation allocation and investments in CNC technology

NARCIS (Netherlands)

Bokhorst, J.A.C.; Slomp, J.; Suresh, N.

2002-01-01

This study addresses the issue of investment appraisal of new technology, specifically computer numerical control (CNC) machine tools in conjunction with optimal allocation of parts and operations on CNC machines as the investments take place. Part-operation allocation is the allocation of parts and

On the power and offset allocation for rate adaptation of spatial multiplexing in optical wireless MIMO channels

KAUST Repository

Park, Kihong

2011-07-01

Visible light communication (VLC) using optical sources which can be simultaneously utilized for illumination and communication is currently an attractive option for wireless personal area network. Improving the data rate in optical wireless communication system is challenging due to the limited bandwidth of the optical sources. In this paper, we design the singular value decomposition (SVD)- based multiplexing multiple-input multiple-output (MIMO) system to support two data streams in optical wireless channels. Noting that the conventional allocation method in radio frequency (RF) MIMO channels cannot be applied directly to the optical intensity channels, we propose a novel method to allocate the optical power, the offset value and the modulation size for maximum sum rate under the constraints of the nonnegativity of the modulated signals, the aggregate optical power and the bit error rate (BER) requirement. The simulation results show that the proposed allocation method gives the better performance than the method to allocate the optical power equally for each data stream. © 2011 IEEE.

Physically Connected Stacked Patch Antenna Design with 100% Bandwidth

KAUST Repository

Klionovski, Kirill; Shamim, Atif

2017-01-01

Typically, stacked patch antennas are parasitically coupled and provide larger bandwidth than a single patch antenna. Here, we show a stacked patch antenna design where square patches with semi-circular cutouts are physically connected to each other. This arrangement provides 100% bandwidth from 23.9–72.2 GHz with consistent high gain (5 dBi or more) across the entire bandwidth. In another variation, a single patch loaded with a superstrate provides 83.5% bandwidth from 25.6–62.3 GHz. The mechanism of bandwidth enhancement is explained through electromagnetic simulations. Measured reflection coefficient, radiation patterns and gain results confirm the extremely wideband performance of the design.

Physically Connected Stacked Patch Antenna Design with 100% Bandwidth

KAUST Repository

Klionovski, Kirill

2017-11-01

Typically, stacked patch antennas are parasitically coupled and provide larger bandwidth than a single patch antenna. Here, we show a stacked patch antenna design where square patches with semi-circular cutouts are physically connected to each other. This arrangement provides 100% bandwidth from 23.9–72.2 GHz with consistent high gain (5 dBi or more) across the entire bandwidth. In another variation, a single patch loaded with a superstrate provides 83.5% bandwidth from 25.6–62.3 GHz. The mechanism of bandwidth enhancement is explained through electromagnetic simulations. Measured reflection coefficient, radiation patterns and gain results confirm the extremely wideband performance of the design.

Optimal JPWL Forward Error Correction Rate Allocation for Robust JPEG 2000 Images and Video Streaming over Mobile Ad Hoc Networks

Directory of Open Access Journals (Sweden)

Benoit Macq

2008-07-01

Full Text Available Based on the analysis of real mobile ad hoc network (MANET traces, we derive in this paper an optimal wireless JPEG 2000 compliant forward error correction (FEC rate allocation scheme for a robust streaming of images and videos over MANET. The packet-based proposed scheme has a low complexity and is compliant to JPWL, the 11th part of the JPEG 2000 standard. The effectiveness of the proposed method is evaluated using a wireless Motion JPEG 2000 client/server application; and the ability of the optimal scheme to guarantee quality of service (QoS to wireless clients is demonstrated.

Power Allocation based on Certain Equivalent Margin Applicable to Wireless Communication Systems Limited by Interference

Directory of Open Access Journals (Sweden)

Tadeu Junior Gross

2015-10-01

Full Text Available This paper analyzes the method of power allocation for wireless communication networks, limited by multiple access interference under fading Rayleigh channels. The method takes into account the statistical variation of the desired and interfering signals power and optimally and dynamically allocates the power resources in the system. This allocation is made being taken into account the restrictions imposed by the outage probability for each receiver/transmitter pair. Based on the Perron-Frobenius eigenvalue and geometric programming (GP theories, some interesting results were found for the optimization problem analyzed. A GP is a special type of optimization problem that can be transformed in a non-linear convex optimization problem simply by the change of variables, and then to be globally solved. Also, an iterative method for fast convergence was shown to find the optimally power allocation seeking to minimize the outage probability in the communication.

On the power and offset allocation for rate adaptation of spatial multiplexing in optical wireless MIMO channels

KAUST Repository

Park, Kihong

2013-04-01

In this paper, we consider resource allocation method in the visible light communication. It is challenging to achieve high data rate due to the limited bandwidth of the optical sources. In order to increase the spectral efficiency, we design a suitable multiple-input multiple-output (MIMO) system utilizing spatial multiplexing based on singular value decomposition and adaptive modulation. More specifically, after explaining why the conventional allocation method in radio frequency MIMO channels cannot be applied directly to the optical intensity channels, we theoretically derive a power allocation method for an arbitrary number of transmit and receive antennas for optical wireless MIMO systems. Based on three key constraints: the nonnegativity of the intensity-modulated signal, the aggregate optical power budget, and the bit error rate requirement, we propose a novel method to allocate the optical power, the offset value, and the modulation size. Based on some selected simulation results, we show that our proposed allocation method gives a better spectral efficiency at the expense of an increased computational complexity in comparison to a simple method that allocates the optical power equally among all the data streams. © 2013 IEEE.

On the power and offset allocation for rate adaptation of spatial multiplexing in optical wireless MIMO channels

KAUST Repository

Park, Kihong; Ko, Youngchai; Alouini, Mohamed-Slim

2013-01-01

In this paper, we consider resource allocation method in the visible light communication. It is challenging to achieve high data rate due to the limited bandwidth of the optical sources. In order to increase the spectral efficiency, we design a suitable multiple-input multiple-output (MIMO) system utilizing spatial multiplexing based on singular value decomposition and adaptive modulation. More specifically, after explaining why the conventional allocation method in radio frequency MIMO channels cannot be applied directly to the optical intensity channels, we theoretically derive a power allocation method for an arbitrary number of transmit and receive antennas for optical wireless MIMO systems. Based on three key constraints: the nonnegativity of the intensity-modulated signal, the aggregate optical power budget, and the bit error rate requirement, we propose a novel method to allocate the optical power, the offset value, and the modulation size. Based on some selected simulation results, we show that our proposed allocation method gives a better spectral efficiency at the expense of an increased computational complexity in comparison to a simple method that allocates the optical power equally among all the data streams. © 2013 IEEE.

Advances in broad bandwidth light sources for ultrahigh resolution optical coherence tomography

International Nuclear Information System (INIS)

Unterhuber, A; Povazay, B; Bizheva, K; Hermann, B; Sattmann, H; Stingl, A; Le, T; Seefeld, M; Menzel, R; Preusser, M; Budka, H; Schubert, Ch; Reitsamer, H; Ahnelt, P K; Morgan, J E; Cowey, A; Drexler, W

2004-01-01

Novel ultra-broad bandwidth light sources enabling unprecedented sub-2 μm axial resolution over the 400 nm-1700 nm wavelength range have been developed and evaluated with respect to their feasibility for clinical ultrahigh resolution optical coherence tomography (UHR OCT) applications. The state-of-the-art light sources described here include a compact Kerr lens mode locked Ti:sapphire laser (λ c = 785 nm, Δλ = 260 nm, P out = 50 mW) and different nonlinear fibre-based light sources with spectral bandwidths (at full width at half maximum) up to 350 nm at λ c = 1130 nm and 470 nm at λ c = 1375 nm. In vitro UHR OCT imaging is demonstrated at multiple wavelengths in human cancer cells, animal ganglion cells as well as in neuropathologic and ophthalmic biopsies in order to compare and optimize UHR OCT image contrast, resolution and penetration depth

Methodology for reliability allocation based on fault tree analysis and dualistic contrast

Institute of Scientific and Technical Information of China (English)

TONG Lili; CAO Xuewu

2008-01-01

Reliability allocation is a difficult multi-objective optimization problem.This paper presents a methodology for reliability allocation that can be applied to determine the reliability characteristics of reactor systems or subsystems.The dualistic contrast,known as one of the most powerful tools for optimization problems,is applied to the reliability allocation model of a typical system in this article.And the fault tree analysis,deemed to be one of the effective methods of reliability analysis,is also adopted.Thus a failure rate allocation model based on the fault tree analysis and dualistic contrast is achieved.An application on the emergency diesel generator in the nuclear power plant is given to illustrate the proposed method.

Bandwidth-Efficient Communication through 225 MHz Ka-band Relay Satellite Channel

Science.gov (United States)

Downey, Joseph A.; Downey, James M.; Reinhart, Richard C.; Evans, Michael A.; Mortensen, Dale J.

2016-01-01

The communications and navigation space infrastructure of the National Aeronautics and Space Administration (NASA) consists of a constellation of relay satellites (called Tracking and Data Relay Satellites (TDRS)) and a global set of ground stations to receive and deliver data to researchers around the world from mission spacecraft throughout the solar system. Planning is underway to enhance and transform the infrastructure over the coming decade. Key to the upgrade will be the simultaneous and efficient use of relay transponders to minimize cost and operations while supporting science and exploration spacecraft. Efficient use of transponders necessitates bandwidth efficient communications to best use and maximize data throughput within the allocated spectrum. Experiments conducted with NASA's Space Communication and Navigation (SCaN) Testbed on the International Space Station provides a unique opportunity to evaluate advanced communication techniques, such as bandwidth-efficient modulations, in an operational flight system. Demonstrations of these new techniques in realistic flight conditions provides critical experience and reduces the risk of using these techniques in future missions. Efficient use of spectrum is enabled by using high-order modulations coupled with efficient forward error correction codes. This paper presents a high-rate, bandwidth-efficient waveform operating over the 225 MHz Ka-band service of the TDRS System (TDRSS). The testing explores the application of Gaussian Minimum Shift Keying (GMSK), 2/4/8-phase shift keying (PSK) and 16/32- amplitude PSK (APSK) providing over three bits-per-second-per-Hertz (3 b/s/Hz) modulation combined with various LDPC encoding rates to maximize through- put. With a symbol rate of 200 M-band, coded data rates of 1000 Mbps were tested in the laboratory and up to 800 Mbps over the TDRS 225 MHz channel. This paper will present on the high-rate waveform design, channel characteristics, performance results

Third degree waiting time discrimination: optimal allocation of a public sector healthcare treatment under rationing by waiting.

Science.gov (United States)

Gravelle, Hugh; Siciliani, Luigi

2009-08-01

In many public healthcare systems treatments are rationed by waiting time. We examine the optimal allocation of a fixed supply of a given treatment between different groups of patients. Even in the absence of any distributional aims, welfare is increased by third degree waiting time discrimination: setting different waiting times for different groups waiting for the same treatment. Because waiting time imposes dead weight losses on patients, lower waiting times should be offered to groups with higher marginal waiting time costs and with less elastic demand for the treatment.

Radio resource allocation over fading channels under statistical delay constraints

CERN Document Server

Le-Ngoc, Tho

2017-01-01

This SpringerBrief presents radio resource allocation schemes for buffer-aided communications systems over fading channels under statistical delay constraints in terms of upper-bounded average delay or delay-outage probability. This Brief starts by considering a source-destination communications link with data arriving at the source transmission buffer. The first scenario, the joint optimal data admission control and power allocation problem for throughput maximization is considered, where the source is assumed to have a maximum power and an average delay constraints. The second scenario, optimal power allocation problems for energy harvesting (EH) communications systems under average delay or delay-outage constraints are explored, where the EH source harvests random amounts of energy from renewable energy sources, and stores the harvested energy in a battery during data transmission. Online resource allocation algorithms are developed when the statistical knowledge of the random channel fading, data arrivals...

EMG-Torque Dynamics Change With Contraction Bandwidth.

Science.gov (United States)

Golkar, Mahsa A; Jalaleddini, Kian; Kearney, Robert E

2018-04-01

An accurate model for ElectroMyoGram (EMG)-torque dynamics has many uses. One of its applications which has gained high attention among researchers is its use, in estimating the muscle contraction level for the efficient control of prosthesis. In this paper, the dynamic relationship between the surface EMG and torque during isometric contractions at the human ankle was studied using system identification techniques. Subjects voluntarily modulated their ankle torque in dorsiflexion direction, by activating their tibialis anterior muscle, while tracking a pseudo-random binary sequence in a torque matching task. The effects of contraction bandwidth, described by torque spectrum, on EMG-torque dynamics were evaluated by varying the visual command switching time. Nonparametric impulse response functions (IRF) were estimated between the processed surface EMG and torque. It was demonstrated that: 1) at low contraction bandwidths, the identified IRFs had unphysiological anticipatory (i.e., non-causal) components, whose amplitude decreased as the contraction bandwidth increased. We hypothesized that this non-causal behavior arose, because the EMG input contained a component due to feedback from the output torque, i.e., it was recorded from within a closed-loop. Vision was not the feedback source since the non-causal behavior persisted when visual feedback was removed. Repeating the identification using a nonparametric closed-loop identification algorithm yielded causal IRFs at all bandwidths, supporting this hypothesis. 2) EMG-torque dynamics became faster and the bandwidth of system increased as contraction modulation rate increased. Thus, accurate prediction of torque from EMG signals must take into account the contraction bandwidth sensitivity of this system.

Electrical Energy Forecasting and Optimal Allocation of ESS in a Hybrid Wind-Diesel Power System

Directory of Open Access Journals (Sweden)

Hai Lan

2017-02-01

Full Text Available Due to the increasingly serious energy crisis and environmental pollution problem, traditional fossil energy is gradually being replaced by renewable energy in recent years. However, the introduction of renewable energy into power systems will lead to large voltage fluctuations and high capital costs. To solve these problems, an energy storage system (ESS is employed into a power system to reduce total costs and greenhouse gas emissions. Hence, this paper proposes a two-stage method based on a back-propagation neural network (BPNN and hybrid multi-objective particle swarm optimization (HMOPSO to determine the optimal placements and sizes of ESSs in a transmission system. Owing to the uncertainties of renewable energy, a BPNN is utilized to forecast the outputs of the wind power and load demand based on historic data in the city of Madison, USA. Furthermore, power-voltage (P-V sensitivity analysis is conducted in this paper to improve the converge speed of the proposed algorithm, and continuous wind distribution is discretized by a three-point estimation method. The Institute of Electrical and Electronic Engineers (IEEE 30-bus system is adopted to perform case studies. The simulation results of each case clearly demonstrate the necessity for optimal storage allocation and the efficiency of the proposed method.

Sharing the 620-790 MHz band allocated to terrestrial television with an audio-bandwidth social service satellite system

Science.gov (United States)

Smith, E. K.; Reinhart, E. E.

1977-01-01

A study was carried out to identify the optimum uplink and downlink frequencies for audio-bandwidth channels for use by a satellite system distributing social services. The study considered functional-user-need models for five types of social services and identified a general baseline system that is appropriate for most of them. Technical aspects and costs of this system and of the frequency bands that it might use were reviewed, leading to the identification of the 620-790 MHz band as a perferred candidate for both uplink and downlink transmissions for nonmobile applications. The study also led to some ideas as to how to configure the satellite system.

A novel power and offset allocation method for spatial multiplexing MIMO Systems in optical wireless channels

KAUST Repository

Park, Kihong

2011-12-01

We consider optical wireless communication which can be utilized for illumination and communication by relying on lighting devices. Due to the limited bandwidth of optical sources, it is challenging to achieve high data rate in optical wireless systems. In order to obtain a multiplexing gain and high spectral efficiency, we design an optical multi-input multi-output (MIMO) system utilizing a singular value decomposition-based spatial multiplexing and adaptive modulation. We note that the conventional allocation method in radio frequency MIMO channels cannot be applied directly to the optical intensity channels. In this paper, we generalize the result of power allocation method in [1] for arbitrary number of transmit and receive antennas in optical wireless MIMO systems. Based on three constraints, namely, the nonnegativity, the aggregate optical power, and the bit error rate requirement, we propose a novel method to allocate the optical power, the offset value, and the modulation size for maximum sum rate. From some selected simulation results, we show that our proposed allocation method gives a better spectral efficiency than the method that allocates the optical power equally for each data stream. © 2011 IEEE.

Cutter Connectivity Bandwidth Study

Science.gov (United States)

2002-10-01

The goal of this study was to determine how much bandwidth is required for cutters to meet emerging data transfer requirements. The Cutter Connectivity Business Solutions Team with guidance front the Commandant's 5 Innovation Council sponsored this study. Today, many Coast Guard administrative and business functions are being conducted via electronic means. Although our larger cutters can establish part-time connectivity using commercial satellite communications (SATCOM) while underway, there are numerous complaints regarding poor application performance. Additionally, smaller cutters do not have any standard means of underway connectivity. The R&D study shows the most important factor affecting web performance and enterprise applications onboard cutters was latency. Latency describes the time it takes the signal to reach the satellite and come back down through space. The latency due to use of higher orbit satellites is causing poor application performance and inefficient use of expensive SATCOM links. To improve performance, the CC must, (1) reduce latency by using alternate communications links such as low-earth orbit satellites, (2) tailor applications to the SATCOM link and/or (3) optimize protocols used for data communication to minimize time required by present applications to establish communications between the user and the host systems.

Optimal resource allocation to survival and reproduction in parasitic wasps foraging in fragmented habitats.

Directory of Open Access Journals (Sweden)

Eric Wajnberg

Full Text Available Expansion and intensification of human land use represents the major cause of habitat fragmentation. Such fragmentation can have dramatic consequences on species richness and trophic interactions within food webs. Although the associated ecological consequences have been studied by several authors, the evolutionary effects on interacting species have received little research attention. Using a genetic algorithm, we quantified how habitat fragmentation and environmental variability affect the optimal reproductive strategies of parasitic wasps foraging for hosts. As observed in real animal species, the model is based on the existence of a negative trade-off between survival and reproduction resulting from competitive allocation of resources to either somatic maintenance or egg production. We also asked to what degree plasticity along this trade-off would be optimal, when plasticity is costly. We found that habitat fragmentation can indeed have strong effects on the reproductive strategies adopted by parasitoids. With increasing habitat fragmentation animals should invest in greater longevity with lower fecundity; yet, especially in unpredictable environments, some level of phenotypic plasticity should be selected for. Other consequences in terms of learning ability of foraging animals were also observed. The evolutionary consequences of these results are discussed.

Optimized autonomous space in-situ sensor web for volcano monitoring

Science.gov (United States)

Song, W.-Z.; Shirazi, B.; Huang, R.; Xu, M.; Peterson, N.; LaHusen, R.; Pallister, J.; Dzurisin, D.; Moran, S.; Lisowski, M.; Kedar, S.; Chien, S.; Webb, F.; Kiely, A.; Doubleday, J.; Davies, A.; Pieri, D.

2010-01-01

In response to NASA's announced requirement for Earth hazard monitoring sensor-web technology, a multidisciplinary team involving sensor-network experts (Washington State University), space scientists (JPL), and Earth scientists (USGS Cascade Volcano Observatory (CVO)), have developed a prototype of dynamic and scalable hazard monitoring sensor-web and applied it to volcano monitoring. The combined Optimized Autonomous Space In-situ Sensor-web (OASIS) has two-way communication capability between ground and space assets, uses both space and ground data for optimal allocation of limited bandwidth resources on the ground, and uses smart management of competing demands for limited space assets. It also enables scalability and seamless infusion of future space and in-situ assets into the sensor-web. The space and in-situ control components of the system are integrated such that each element is capable of autonomously tasking the other. The ground in-situ was deployed into the craters and around the flanks of Mount St. Helens in July 2009, and linked to the command and control of the Earth Observing One (EO-1) satellite. ?? 2010 IEEE.

On semidefinite programming bounds for graph bandwidth

NARCIS (Netherlands)

de Klerk, E.; Nagy, M.; Sotirov, R.

2013-01-01

In this paper, we propose two new lower bounds on graph bandwidth and cyclic bandwidth based on semidefinite programming (SDP) relaxations of the quadratic assignment problem. We compare the new bounds with two other SDP bounds reported in [A. Blum, G. Konjevod, R. Ravi, and S. Vempala,

47 CFR 74.535 - Emission and bandwidth.

Science.gov (United States)

2010-10-01

... digital modulation in paragraph (a) of this section, the resolution bandwidth (BRES) of the measuring...), adjusted upward to the nearest greater resolution bandwidth available on the measuring equipment. In all... frequency energy outside the assigned channel. Upon notice by the FCC to the station licensee that...

Experiences in Traceroute and Bandwidth Change Analysis

Energy Technology Data Exchange (ETDEWEB)

Logg, C

2004-06-23

SLAC has been studying end-to-end WAN bandwidth availability and achievability for 2.5 years via IEPM-BW [1]. IEPM-BW performs network intensive tests every 90 minutes. Based on that experience we have also developed a light weight available bandwidth (ABwE [2]) measurement tool that can make a measurement within a second. We are now extending this to a WAN measurement and detection system (IEPM-LITE) aimed at more quickly detecting and troubleshooting network performance problems and also to be more friendly on lower performance paths. IEPM-LITE uses ping, forward traceroutes, and ABwE sensors to monitor, in close to real-time, Round Trip Times (RTT), changes in available bandwidth and routes to and from target hosts. This paper discusses the experiences, techniques and algorithms used to detect and report on significant traceroute and bandwidth changes. The ultimate aim is to develop a lightweight WAN network performance monitoring system that can detect, in near real time, significant changes and generate alerts.

Experiences in Traceroute and Bandwidth Change Analysis

International Nuclear Information System (INIS)

Logg, C

2004-01-01

SLAC has been studying end-to-end WAN bandwidth availability and achievability for 2.5 years via IEPM-BW [1]. IEPM-BW performs network intensive tests every 90 minutes. Based on that experience we have also developed a light weight available bandwidth (ABwE [2]) measurement tool that can make a measurement within a second. We are now extending this to a WAN measurement and detection system (IEPM-LITE) aimed at more quickly detecting and troubleshooting network performance problems and also to be more friendly on lower performance paths. IEPM-LITE uses ping, forward traceroutes, and ABwE sensors to monitor, in close to real-time, Round Trip Times (RTT), changes in available bandwidth and routes to and from target hosts. This paper discusses the experiences, techniques and algorithms used to detect and report on significant traceroute and bandwidth changes. The ultimate aim is to develop a lightweight WAN network performance monitoring system that can detect, in near real time, significant changes and generate alerts

Sperm competition and sex allocation in simultaneous hermaphrodites : A new look at Charnov's invariance principle

NARCIS (Netherlands)

Pen, I.R.; Weissing, F.J.

Recently, Charnov (1996) investigated the consequences of sperm competition for optimal sex allocation in simultaneous hermaphrodites. Charnov argued that the optimal sex allocation strategy can be derived on the basis of the 'sperm displacement rule'; that is, the function describing the

Critical phenomena in communication/computation networks with various topologies and suboptimal to optimal resource allocation

Science.gov (United States)

Cogoni, Marco; Busonera, Giovanni; Anedda, Paolo; Zanetti, Gianluigi

2015-01-01

We generalize previous studies on critical phenomena in communication networks [1,2] by adding computational capabilities to the nodes. In our model, a set of tasks with random origin, destination and computational structure is distributed on a computational network, modeled as a graph. By varying the temperature of a Metropolis Montecarlo, we explore the global latency for an optimal to suboptimal resource assignment at a given time instant. By computing the two-point correlation function for the local overload, we study the behavior of the correlation distance (both for links and nodes) while approaching the congested phase: a transition from peaked to spread g(r) is seen above a critical (Montecarlo) temperature Tc. The average latency trend of the system is predicted by averaging over several network traffic realizations while maintaining a spatially detailed information for each node: a sharp decrease of performance is found over Tc independently of the workload. The globally optimized computational resource allocation and network routing defines a baseline for a future comparison of the transition behavior with respect to existing routing strategies [3,4] for different network topologies.

Efficient power allocation for fixed-gain amplify-and-forward relaying in rayleigh fading

KAUST Repository

Zafar, Ammar

2013-06-01

In this paper, we study power allocation strategies for a fixed-gain amplify-and-forward relay network employing multiple relays. We consider two optimization problems for the relay network: 1) optimal power allocation to maximize the end-to-end signal-to-noise ratio (SNR) and 2) minimizing the total consumed power while maintaining the end-to-end SNR over a threshold value. We assume that the relays have knowledge of only the channel statistics of all the links. We show that the SNR maximization problem is concave and the power minimization problem is convex. Hence, we solve the problems through convex programming. Numerical results show the benefit of allocating power optimally rather than uniformly. © 2013 IEEE.

Efficient Bandwidth Management for Ethernet Passive Optical Networks

KAUST Repository

Elrasad, Amr

2016-01-01

The increasing bandwidth demands in access networks motivates network operators, networking devices manufacturers, and standardization institutions to search for new approaches for access networks. These approaches should support higher bandwidth

Power Allocation and Outage Probability Analysis for SDN-based Radio Access Networks

Science.gov (United States)

Zhao, Yongxu; Chen, Yueyun; Mai, Zhiyuan

2018-01-01

In this paper, performance of Access network Architecture based SDN (Software Defined Network) is analyzed with respect to the power allocation issue. A power allocation scheme PSO-PA (Particle Swarm Optimization-power allocation) algorithm is proposed, the proposed scheme is subjected to constant total power with the objective of minimizing system outage probability. The entire access network resource configuration is controlled by the SDN controller, then it sends the optimized power distribution factor to the base station source node (SN) and the relay node (RN). Simulation results show that the proposed scheme reduces the system outage probability at a low complexity.

Engine Yaw Augmentation for Hybrid-Wing-Body Aircraft via Optimal Control Allocation Techniques

Science.gov (United States)

Taylor, Brian R.; Yoo, Seung Yeun

2011-01-01

Asymmetric engine thrust was implemented in a hybrid-wing-body non-linear simulation to reduce the amount of aerodynamic surface deflection required for yaw stability and control. Hybrid-wing-body aircraft are especially susceptible to yaw surface deflection due to their decreased bare airframe yaw stability resulting from the lack of a large vertical tail aft of the center of gravity. Reduced surface deflection, especially for trim during cruise flight, could reduce the fuel consumption of future aircraft. Designed as an add-on, optimal control allocation techniques were used to create a control law that tracks total thrust and yaw moment commands with an emphasis on not degrading the baseline system. Implementation of engine yaw augmentation is shown and feasibility is demonstrated in simulation with a potential drag reduction of 2 to 4 percent. Future flight tests are planned to demonstrate feasibility in a flight environment.

Decision tables and rule engines in organ allocation systems for optimal transparency and flexibility

NARCIS (Netherlands)

Schaafsma, M.; Deijl, W. van der; Smits, J.M.M.; Rahmel, A.O.; Vries Robbé, P.F. de; Hoitsma, A.J.

2011-01-01

Organ allocation systems have become complex and difficult to comprehend. We introduced decision tables to specify the rules of allocation systems for different organs. A rule engine with decision tables as input was tested for the Kidney Allocation System (ETKAS). We compared this rule engine with

Multi-robot Task Allocation for Search and Rescue Missions

International Nuclear Information System (INIS)

Hussein, Ahmed; Adel, Mohamed; Bakr, Mohamed; Shehata, Omar M; Khamis, Alaa

2014-01-01

Many researchers from academia and industry are attracted to investigate how to design and develop robust versatile multi-robot systems by solving a number of challenging and complex problems such as task allocation, group formation, self-organization and much more. In this study, the problem of multi-robot task allocation (MRTA) is tackled. MRTA is the problem of optimally allocating a set of tasks to a group of robots to optimize the overall system performance while being subjected to a set of constraints. A generic market-based approach is proposed in this paper to solve this problem. The efficacy of the proposed approach is quantitatively evaluated through simulation and real experimentation using heterogeneous Khepera-III mobile robots. The results from both simulation and experimentation indicate the high performance of the proposed algorithms and their applicability in search and rescue missions

Chemical Industry Bandwidth Study

Energy Technology Data Exchange (ETDEWEB)

none,

2006-12-01

The Chemical Bandwidth Study provides a snapshot of potentially recoverable energy losses during chemical manufacturing. The advantage of this study is the use of "exergy" analysis as a tool for pinpointing inefficiencies.

SDNManager: A Safeguard Architecture for SDN DoS Attacks Based on Bandwidth Prediction

Directory of Open Access Journals (Sweden)

Tao Wang

2018-01-01

Full Text Available Software-Defined Networking (SDN has quickly emerged as a promising technology for future networks and gained much attention. However, the centralized nature of SDN makes the system vulnerable to denial-of-services (DoS attacks, especially for the currently widely deployed multicontroller system. Due to DoS attacks, SDN multicontroller model may additionally face the risk of the cascading failures of controllers. In this paper, we propose SDNManager, a lightweight and fast denial-of-service detection and mitigation system for SDN. It has five components: monitor, forecast engine, checker, updater, and storage service. It typically follows a control loop of reading flow statistics, forecasting flow bandwidth changes based on the statistics, and accordingly updating the network. It is worth noting that the forecast engine employs a novel dynamic time-series (DTS model which greatly improves bandwidth prediction accuracy. What is more, to further optimize the defense effect, we also propose a controller dynamic scheduling strategy to ensure the global network state optimization and improve the defense efficiency. We evaluate SDNManager through a prototype implementation tested in a real SDN network environment. The results show that SDNManager is effective with adding only a minor overhead into the entire SDN/OpenFlow infrastructure.

Fund allocation using capacitated vehicle routing problem

Science.gov (United States)

Mamat, Nur Jumaadzan Zaleha; Jaaman, Saiful Hafizah; Ahmad, Rokiah Rozita; Darus, Maslina

2014-09-01

In investment fund allocation, it is unwise for an investor to distribute his fund into several assets simultaneously due to economic reasons. One solution is to allocate the fund into a particular asset at a time in a sequence that will either maximize returns or minimize risks depending on the investor's objective. The vehicle routing problem (VRP) provides an avenue to this issue. VRP answers the question on how to efficiently use the available fleet of vehicles to meet a given service demand, subjected to a set of operational requirements. This paper proposes an idea of using capacitated vehicle routing problem (CVRP) to optimize investment fund allocation by employing data of selected stocks in the FTSE Bursa Malaysia. Results suggest that CRVP can be applied to solve the issue of investment fund allocation and increase the investor's profit.

Minimizing Sum-MSE Implies Identical Downlink and Dual Uplink Power Allocations

OpenAIRE

Tenenbaum, Adam J.; Adve, Raviraj S.

2009-01-01

In the multiuser downlink, power allocation for linear precoders that minimize the sum of mean squared errors under a sum power constraint is a non-convex problem. Many existing algorithms solve an equivalent convex problem in the virtual uplink and apply a transformation based on uplink-downlink duality to find a downlink solution. In this letter, we analyze the optimality criteria for the power allocation subproblem in the virtual uplink, and demonstrate that the optimal solution leads to i...

Fairness-Aware and Energy Efficiency Resource Allocation in Multiuser OFDM Relaying System

Directory of Open Access Journals (Sweden)

Guangjun Liang

2016-01-01

Full Text Available A fairness-aware resource allocation scheme in a cooperative orthogonal frequency division multiple (OFDM network is proposed based on jointly optimizing the subcarrier pairing, power allocation, and channel-user assignment. Compared with traditional OFDM relaying networks, the source is permitted to retransfer the same data transmitted by it in the first time slot, further improving the system capacity performance. The problem which maximizes the energy efficiency (EE of the system with total power constraint and minimal spectral efficiency constraint is formulated into a mixed-integer nonlinear programming (MINLP problem which has an intractable complexity in general. The optimization model is simplified into a typical fractional programming problem which is testified to be quasiconcave. Thus we can adopt Dinkelbach method to deal with MINLP problem proposed to achieve the optimal solution. The simulation results show that the joint resource allocation method proposed can achieve an optimal EE performance under the minimum system service rate requirement with a good global convergence.

A Method for Optimal Allocation between Instream and Offstream Uses in the Maipo River in Central Chile

Science.gov (United States)

Génova, P. P.; Olivares, M. A.

2016-12-01

Minimum instream flows (MIF) have been established in Chile with the aim of protecting aquatic ecosystems. In practice, since current water law only allocates water rights to offstream water uses, MIF becomes the only instrument for instream water allocation. However, MIF do not necessarily maintain an adequate flow for instream uses. Moreover, an efficient allocation of water for instream uses requires the quantification of the benefits obtained from those uses, so that tradeoffs between instream and offstream water uses are properly considered. A model of optimal allocation between instream and offstream uses is elaborated. The proposed method combines two pieces of information. On one hand, benefits of instream use are represented by qualitative recreational benefit curves as a function of instream flow. On the other hand, the opportunity cost given by lost benefits of offstream uses is employed to develop a supply curve for instream flows. We applied this method to the case of the Maipo River, where the main water uses are recreation, hydropower production and drinking water. Based on available information we obtained the qualitative benefits of various recreational activities as a function of flow attributes. Then we developed flow attributes curves as a function of instream flow for a representative number of sections in the river. As a result we obtained the qualitative recreational benefit curve for each section. The marginal cost curve for instream flows was developed from the benefit functions of hydropower production interfering with recreation in the Maipo River. The purpose of this supply curve is to find a range of instream flow that will provide a better quality condition for recreation experience at a lower opportunity cost. Results indicate that offstream uses adversely influence recreational activities in the Maipo River in certain months of the year, significantly decreasing the quality of these in instream uses. As expected, the impact depends

Energy-Efficient Power Allocation for Fixed-Gain Amplify-and-Forward Relay Networks with Partial Channel State Information

KAUST Repository

Zafar, Ammar

2012-06-01

In this report, energy-efficient transmission and power allocation for fixed-gain amplify-and-forward relay networks with partial channel state information (CSI) are studied. In the energy-efficiency problem, the total power consumed is minimized while keeping the signal-to-noise-ratio (SNR) above a certain threshold. In the dual problem of power allocation, the end-to-end SNR is maximized under individual and global power constraints. Closed-form expressions for the optimal source and relay powers and the Lagrangian multiplier are obtained. Numerical results show that the optimal power allocation with partial CSI provides comparable performance as optimal power allocation with full CSI at low SNR.

Energy-Efficient Power Allocation for Fixed-Gain Amplify-and-Forward Relay Networks with Partial Channel State Information

KAUST Repository

Zafar, Ammar

2012-09-16

In this letter, energy-efficient transmission and power allocation for fixed-gain amplify-and-forward relay networks with partial channel state information (CSI) are studied. In the energy-efficiency problem, the total power consumed is minimized while keeping the signal-to-noise-ratio (SNR) above a certain threshold. In the dual problem of power allocation, the end-to-end SNR is maximized under individual and global power constraints. Closed-form expressions for the optimal source and relay powers and the Lagrangian multiplier are obtained. Numerical results show that the optimal power allocation with partial CSI provides comparable performance as optimal power allocation with full CSI at low SNR. © 2012 IEEE.

Large bandwidth RGC transimpedance preamplifier design in SCA

International Nuclear Information System (INIS)

Wang Ke; Wang Zheng; Liu Zhen'an; Wei Wei; Lu Weiguo; Gary Varner

2009-01-01

A Large Bandwidth RGC Transimpedance Preamplifier is designed for amplifying the high-fidelity timing signal in Switch Capacitance Array chip application. This amplifier have characteristics of low input impedance, large bandwidth, high transimpedance. It will be made under TSMC 0.25μm CMOS technology, and the supply voltage is single 2.5 V. Simulation results indicate: the transimpedance is 5000 ohm, -3dB BW is 953 MHz, and the detector output capacitance have litter effect on the bandwidth in some range. (authors)

Land Use Allocation Based on a Multi-Objective Artificial Immune Optimization Model: An Application in Anlu County, China

Directory of Open Access Journals (Sweden)

Xiaoya Ma

2015-11-01

Full Text Available As the main feature of land use planning, land use allocation (LUA optimization is an important means of creating a balance between the land-use supply and demand in a region and promoting the sustainable utilization of land resources. In essence, LUA optimization is a multi-objective optimization problem under the land use supply and demand constraints in a region. In order to obtain a better sustainable multi-objective LUA optimization solution, the present study proposes a LUA model based on the multi-objective artificial immune optimization algorithm (MOAIM-LUA model. The main achievements of the present study are as follows: (a the land-use supply and demand factors are analyzed and the constraint conditions of LUA optimization problems are constructed based on the analysis framework of the balance between the land use supply and demand; (b the optimization objectives of LUA optimization problems are defined and modeled using ecosystem service value theory and land rent and price theory; and (c a multi-objective optimization algorithm is designed for solving multi-objective LUA optimization problems based on the novel immune clonal algorithm (NICA. On the basis of the aforementioned achievements, MOAIM-LUA was applied to a real case study of land-use planning in Anlu County, China. Compared to the current land use situation in Anlu County, optimized LUA solutions offer improvements in the social and ecological objective areas. Compared to the existing models, such as the non-dominated sorting genetic algorithm-II, experimental results demonstrate that the model designed in the present study can obtain better non-dominated solution sets and is superior in terms of algorithm stability.

PIC Simulation of Laser Plasma Interactions with Temporal Bandwidths

Science.gov (United States)

Tsung, Frank; Weaver, J.; Lehmberg, R.

2015-11-01

We are performing particle-in-cell simulations using the code OSIRIS to study the effects of laser plasma interactions in the presence of temperal bandwidths under conditions relevant to current and future shock ignition experiments on the NIKE laser. Our simulations show that, for sufficiently large bandwidth, the saturation level, and the distribution of hot electrons, can be effected by the addition of temporal bandwidths (which can be accomplished in experiments using smoothing techniques such as SSD or ISI). We will show that temporal bandwidth along play an important role in the control of LPI's in these lasers and discuss future directions. This work is conducted under the auspices of NRL.

Statistical Power and Optimum Sample Allocation Ratio for Treatment and Control Having Unequal Costs Per Unit of Randomization

Science.gov (United States)

Liu, Xiaofeng

2003-01-01

This article considers optimal sample allocation between the treatment and control condition in multilevel designs when the costs per sampling unit vary due to treatment assignment. Optimal unequal allocation may reduce the cost from that of a balanced design without sacrificing any power. The optimum sample allocation ratio depends only on the…

Optimal allocation of physical water resources integrated with virtual water trade in water scarce regions: A case study for Beijing, China.

Science.gov (United States)

Ye, Quanliang; Li, Yi; Zhuo, La; Zhang, Wenlong; Xiong, Wei; Wang, Chao; Wang, Peifang

2018-02-01

This study provides an innovative application of virtual water trade in the traditional allocation of physical water resources in water scarce regions. A multi-objective optimization model was developed to optimize the allocation of physical water and virtual water resources to different water users in Beijing, China, considering the trade-offs between economic benefit and environmental impacts of water consumption. Surface water, groundwater, transferred water and reclaimed water constituted the physical resource of water supply side, while virtual water flow associated with the trade of five major crops (barley, corn, rice, soy and wheat) and three livestock products (beef, pork and poultry) in agricultural sector (calculated by the trade quantities of products and their virtual water contents). Urban (daily activities and public facilities), industry, environment and agriculture (products growing) were considered in water demand side. As for the traditional allocation of physical water resources, the results showed that agriculture and urban were the two predominant water users (accounting 54% and 28%, respectively), while groundwater and surface water satisfied around 70% water demands of different users (accounting 36% and 34%, respectively). When considered the virtual water trade of eight agricultural products in water allocation procedure, the proportion of agricultural consumption decreased to 45% in total water demand, while the groundwater consumption decreased to 24% in total water supply. Virtual water trade overturned the traditional components of water supplied from different sources for agricultural consumption, and became the largest water source in Beijing. Additionally, it was also found that environmental demand took a similar percentage of water consumption in each water source. Reclaimed water was the main water source for industrial and environmental users. The results suggest that physical water resources would mainly satisfy the consumption

Supplier Portfolio Selection and Optimum Volume Allocation: A Knowledge Based Method

NARCIS (Netherlands)

Aziz, Romana; Aziz, R.; van Hillegersberg, Jos; Kersten, W.; Blecker, T.; Luthje, C.

2010-01-01

Selection of suppliers and allocation of optimum volumes to suppliers is a strategic business decision. This paper presents a decision support method for supplier selection and the optimal allocation of volumes in a supplier portfolio. The requirements for the method were gathered during a case

Delegated Portfolio Management and Optimal Allocation of Portfolio Managers

DEFF Research Database (Denmark)

Christensen, Michael; Vangsgaard Christensen, Michael; Gamskjaer, Ken

2015-01-01

In this article, we investigate whether the application of the mean-variance framework on portfolio manager allocation offers any out-of-sample benefits compared to a naïve strategy of equal weighting. Based on an exclusive data-set of high-net-worth (HNW) investors, we utilize a wide variety of ...

Optimization of broadband semiconductor chirped mirrors with genetic algorithm

OpenAIRE

Dems, M.; Wnuk, P.; Wasylczyk, P.; Zinkiewicz, L.; Wojcik-Jedlinska, A.; Reginski, K.; Hejduk, K.; Jasik, A.

2016-01-01

Genetic algorithm was applied for optimization of dispersion properties in semiconductor Bragg reflectors for applications in femtosecond lasers. Broadband, large negative group-delay dispersion was achieved in the optimized design: The group-delay dispersion (GDD) as large as −3500 fs2 was theoretically obtained over a 10-nm bandwidth. The designed structure was manufactured and tested, providing GDD −3320 fs2 over a 7-nm bandwidth. The mirror performance was ...

Optimal Pricing and Power Allocation for Collaborative Jamming with Full Channel Knowledge in Wireless Sensor Networks.

Science.gov (United States)

Jeong, Dae-Kyo; Kim, Insook; Kim, Dongwoo

2017-11-22

This paper presents a price-searching model in which a source node (Alice) seeks friendly jammers that prevent eavesdroppers (Eves) from snooping legitimate communications by generating interference or noise. Unlike existing models, the distributed jammers also have data to send to their respective destinations and are allowed to access Alice's channel if it can transmit sufficient jamming power, which is referred to as collaborative jamming in this paper. For the power used to deliver its own signal, the jammer should pay Alice. The price of the jammers' signal power is set by Alice and provides a tradeoff between the signal and the jamming power. This paper presents, in closed-form, an optimal price that maximizes Alice's benefit and the corresponding optimal power allocation from a jammers' perspective by assuming that the network-wide channel knowledge is shared by Alice and jammers. For a multiple-jammer scenario where Alice hardly has the channel knowledge, this paper provides a distributed and interactive price-searching procedure that geometrically converges to an optimal price and shows that Alice by a greedy selection policy achieves certain diversity gain, which increases log-linearly as the number of (potential) jammers grows. Various numerical examples are presented to illustrate the behavior of the proposed model.

Optimal Pricing and Power Allocation for Collaborative Jamming with Full Channel Knowledge in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Dae-Kyo Jeong

2017-11-01

Full Text Available This paper presents a price-searching model in which a source node (Alice seeks friendly jammers that prevent eavesdroppers (Eves from snooping legitimate communications by generating interference or noise. Unlike existing models, the distributed jammers also have data to send to their respective destinations and are allowed to access Alice’s channel if it can transmit sufficient jamming power, which is referred to as collaborative jamming in this paper. For the power used to deliver its own signal, the jammer should pay Alice. The price of the jammers’ signal power is set by Alice and provides a tradeoff between the signal and the jamming power. This paper presents, in closed-form, an optimal price that maximizes Alice’s benefit and the corresponding optimal power allocation from a jammers’ perspective by assuming that the network-wide channel knowledge is shared by Alice and jammers. For a multiple-jammer scenario where Alice hardly has the channel knowledge, this paper provides a distributed and interactive price-searching procedure that geometrically converges to an optimal price and shows that Alice by a greedy selection policy achieves certain diversity gain, which increases log-linearly as the number of (potential jammers grows. Various numerical examples are presented to illustrate the behavior of the proposed model.

Comparing two socially optimal work allocation rules when having a profit optimizing subcontractor with ample capacity

DEFF Research Database (Denmark)

Larsen, Christian

We study a service system modelled as a single server queueing system where requests for service either can be processed at the service system or by a subcontractor. In the former case the subcontractor is incurred waiting costs but the service is free, while in the latter case the customer must...... pay for the service but there is no waiting time, hence no waiting costs. Under the premises that the subcontractor prices his services in order to maximize his profit, we study two work allocation rules, which given the príce of the subcontractor seek to allocate work such that the costs...

Teleoperation over low bandwidth communication links

International Nuclear Information System (INIS)

Fryer, R.J.; Mair, G.M.; Clark, N.; Heng, J.

1996-01-01

Teleoperation is well established for many areas of hazardous environment working. Where such environments are well structured and contained, such as within a working plant, communications bandwidths need not be a constraining factor. However where the worksite is remote, large, poorly structured or damaged communications rapidly become a critical factor in the efficient deployment and use of teleoperation equipment. The paper justifies and describes means which we are exploring to reduce the required communications bandwidth for teleoperation whist retaining full functionality. Techniques involved include incorporation of local intelligence at the worksite, with bandwidth devoted to high-level up-link control signals and down-link feedback, and the use of highly compressed video feeding 'virtual reality type' HMDs to provide maximum system transparency for the operator. The work is drawing on previous experience with an 'anthropomorphic robot heat' for telepresence work, and proprietary algorithms capable of compressing full colour video to standard telephone modem data rates. (Author)

Fluid Limits for Bandwidth-Sharing Networks in Overload.

NARCIS (Netherlands)

Borst, S.; Egorova, R.; Zwart, A.P.

2014-01-01

Bandwidth-sharing networks as considered by Roberts and Massoulié [28] (Roberts JW, Massoulié L (1998) Bandwidth sharing and admission control for elastic traffic. Proc. ITC Specialist Seminar, Yokohama, Japan) provide a natural modeling framework for describing the dynamic flow-level interaction

Fluid limits for bandwidth-sharing networks in overload

NARCIS (Netherlands)

Borst, S.C.; Egorova, R.R.; Zwart, B.

2014-01-01

Bandwidth-sharing networks as considered by Roberts and Massoulié [28] (Roberts JW, Massoulié L (1998) Bandwidth sharing and admission control for elastic traffic. Proc. ITC Specialist Seminar, Yokohama, Japan) provide a natural modeling framework for describing the dynamic flow-level interaction

Reliability-oriented multi-resource allocation in a stochastic-flow network

International Nuclear Information System (INIS)

Hsieh, C.-C.; Lin, M.-H.

2003-01-01

A stochastic-flow network consists of a set of nodes, including source nodes which supply various resources and sink nodes at which resource demands take place, and a collection of arcs whose capacities have multiple operational states. The network reliability of such a stochastic-flow network is the probability that resources can be successfully transmitted from source nodes through multi-capacitated arcs to sink nodes. Although the evaluation schemes of network reliability in stochastic-flow networks have been extensively studied in the literature, how to allocate various resources at source nodes in a reliable means remains unanswered. In this study, a resource allocation problem in a stochastic-flow network is formulated that aims to determine the optimal resource allocation policy at source nodes subject to given resource demands at sink nodes such that the network reliability of the stochastic-flow network is maximized, and an algorithm for computing the optimal resource allocation is proposed that incorporates the principle of minimal path vectors. A numerical example is given to illustrate the proposed algorithm

Bandwidth based methodology for designing a hybrid energy storage system for a series hybrid electric vehicle with limited all electric mode

Science.gov (United States)

Shahverdi, Masood

The cost and fuel economy of hybrid electrical vehicles (HEVs) are significantly dependent on the power-train energy storage system (ESS). A series HEV with a minimal all-electric mode (AEM) permits minimizing the size and cost of the ESS. This manuscript, pursuing the minimal size tactic, introduces a bandwidth based methodology for designing an efficient ESS. First, for a mid-size reference vehicle, a parametric study is carried out over various minimal-size ESSs, both hybrid (HESS) and non-hybrid (ESS), for finding the highest fuel economy. The results show that a specific type of high power battery with 4.5 kWh capacity can be selected as the winning candidate to study for further minimization. In a second study, following the twin goals of maximizing Fuel Economy (FE) and improving consumer acceptance, a sports car class Series-HEV (SHEV) was considered as a potential application which requires even more ESS minimization. The challenge with this vehicle is to reduce the ESS size compared to 4.5 kWh, because the available space allocation is only one fourth of the allowed battery size in the mid-size study by volume. Therefore, an advanced bandwidth-based controller is developed that allows a hybridized Subaru BRZ model to be realized with a light ESS. The result allows a SHEV to be realized with 1.13 kWh ESS capacity. In a third study, the objective is to find optimum SHEV designs with minimal AEM assumption which cover the design space between the fuel economies in the mid-size car study and the sports car study. Maximizing FE while minimizing ESS cost is more aligned with customer acceptance in the current state of market. The techniques applied to manage the power flow between energy sources of the power-train significantly affect the results of this optimization. A Pareto Frontier, including ESS cost and FE, for a SHEV with limited AEM, is introduced using an advanced bandwidth-based control strategy teamed up with duty ratio control. This controller

Kalai-Smorodinsky bargaining solution for optimal resource allocation over wireless DS-CDMA visual sensor networks

Science.gov (United States)

Pandremmenou, Katerina; Kondi, Lisimachos P.; Parsopoulos, Konstantinos E.

2012-01-01

Surveillance applications usually require high levels of video quality, resulting in high power consumption. The existence of a well-behaved scheme to balance video quality and power consumption is crucial for the system's performance. In the present work, we adopt the game-theoretic approach of Kalai-Smorodinsky Bargaining Solution (KSBS) to deal with the problem of optimal resource allocation in a multi-node wireless visual sensor network (VSN). In our setting, the Direct Sequence Code Division Multiple Access (DS-CDMA) method is used for channel access, while a cross-layer optimization design, which employs a central processing server, accounts for the overall system efficacy through all network layers. The task assigned to the central server is the communication with the nodes and the joint determination of their transmission parameters. The KSBS is applied to non-convex utility spaces, efficiently distributing the source coding rate, channel coding rate and transmission powers among the nodes. In the underlying model, the transmission powers assume continuous values, whereas the source and channel coding rates can take only discrete values. Experimental results are reported and discussed to demonstrate the merits of KSBS over competing policies.

Downlink resource allocation for multichannel TDMA visible light communications

KAUST Repository

Abdelhady, Amr Mohamed Abdelaziz; Amin, Osama; Chaaban, Anas; Alouini, Mohamed-Slim

2017-01-01

Optical wireless communications (OWC) in general and resource allocation in OWC networks particularly have gained lots of attention recently. In this work, we consider the resource allocation problem of a visible light communication downlink transmission system based on time division multiple access with the objective of maximizing spectral efficiency (SE). As for the operational conditions, we impose constraints on the average optical intensity, the energy consumption and the quality-of-service. To solve the non-convex problem, we transform the objective function into a difference of concave functions by solving a second order differential inequality. Then, we propose a low-complexity algorithm to solve the resource allocation problem. Finally, we show by simulations the SE performance gains achieved by optimizing the power allocation over equal power allocation in the considered system. Numerical results show the SE gains achieved by using this solution.

Downlink resource allocation for multichannel TDMA visible light communications

KAUST Repository

Abdelhady, Amr Mohamed Abdelaziz

2017-05-12

Optical wireless communications (OWC) in general and resource allocation in OWC networks particularly have gained lots of attention recently. In this work, we consider the resource allocation problem of a visible light communication downlink transmission system based on time division multiple access with the objective of maximizing spectral efficiency (SE). As for the operational conditions, we impose constraints on the average optical intensity, the energy consumption and the quality-of-service. To solve the non-convex problem, we transform the objective function into a difference of concave functions by solving a second order differential inequality. Then, we propose a low-complexity algorithm to solve the resource allocation problem. Finally, we show by simulations the SE performance gains achieved by optimizing the power allocation over equal power allocation in the considered system. Numerical results show the SE gains achieved by using this solution.

MARKET ALLOCATION RULES FOR NONPRICE PROMOTION WITH FARM PROGRAMS: U.S. COTTON

OpenAIRE

Ding, Lily; Kinnucan, Henry W.

1996-01-01

Rules are derived to indicate the optimal allocation of a fixed promotion budget between domestic and export markets when the commodity in question represents a significant portion of world trade and is protected in the domestic market by a deficiency-payment program. Optimal allocation decisions are governed by advertising elasticities in the domestic and export markets and the export market share. PromotionÂ’'s ability to lower deficiency payments is inversely related to the absolute value ...

Optimal Allocation of Restoration Practices Using Indexes for Stream Health

Science.gov (United States)

Methodologies that allocate the placement of agricultural and urban green infrastructure management practices with the intent to achieve both economic and environmental objectives typically use objectives related to individual intermediary environmental outputs, yet guidance is n...

A Risk Management Approach to Optimal Asset Allocation

OpenAIRE

Thomas J. Flavin; Michael R. Wickens

2001-01-01

This paper extends the tactical asset allocation strategy of Flavin and Wickens(1998) to incorporate the effects of macroeconomic variables in the analysis. Using a VAR in mean with a M-GARCH error structure, we can jointly model financial asset returns and macroeconomic variables, thereby exploiting any predictability in either the first- or second-order moments. Taking a set of UK\\ financial assets and the change in domestic inflation as an illustration, we find a much stronger impact on th...

Comparing two socially optimal work allocation rules when having a profit optimizing subcontractor with ample capacity

DEFF Research Database (Denmark)

Larsen, Christian

2005-01-01

We study a service system modelled as a single server queuing system where request for service either can be processed at the service system or by a subcontractor. In the former case the customer is incurred waiting costs but the service is free, while in the latter case the customer must pay...... for the service but there is no waiting time, hence no waiting costs. Under the premises that the subcontractor prices his services in order to maximize his profit, we study two work allocation rules, which given the price of subcontractor seek to allocate work such that the costs of the customers are minimized...

Comparing two socially optimal work allocation rules when having a profit optimizing subcontractor with ample capacity

DEFF Research Database (Denmark)

Larsen, Christian

2003-01-01

We study a service system modelled as a single server queueing system where request for service either can be processed at the service system or by a subcontractor. In the former case the customer is incurred waiting costs but the service is free, while in the latter case the customer must pay...... for the service but there is no waiting time, hence no waiting costs. Under the premises that the subcontractor prices his services in order to maximize his profit, we study two work allocation rules, which given the price of the subcontractor seek to allocate work such that the costs of the customers...

A Spectrum Allocation Mechanism Based on HJ-DQPSO for Cognitive Radio Networks

Directory of Open Access Journals (Sweden)

Zhu Jiang

2015-11-01

Full Text Available In cognitive radio network model consisting of secondary users and primary users, in order to solve the difficult multi-objective spectrum allocation issue about maximizing network efficiency and users’ fairness to access network, this paper proposes a new discrete multi-objective combinatorial optimization mechanism—HJ-DQPSO based on Hooke Jeeves (HJ and Quantum Particle Swarm Optimization (QPSO algorithm. The mechanism adopts HJ algorithm to local search to prevent falling into the local optimum, and proposes a discrete QPSO algorithm to match the discrete spectrum assignment model. The mechanism has the advantages of approximating optimal solution, rapid convergence, less parameters, avoiding falling into local optimum. Compared with existing spectrum assignment algorithms, the simulation results show that according to different optimization objectives, the HJ-DQPSO optimization mechanism for multi-objective optimization can better approximate optimal solution and　converge fast. We can obtain a reasonable spectrum allocation scheme in the case of satisfying multiple optimization objectives.

Motion-related resource allocation in dynamic wireless visual sensor network environments.

Science.gov (United States)

Katsenou, Angeliki V; Kondi, Lisimachos P; Parsopoulos, Konstantinos E

2014-01-01

This paper investigates quality-driven cross-layer optimization for resource allocation in direct sequence code division multiple access wireless visual sensor networks. We consider a single-hop network topology, where each sensor transmits directly to a centralized control unit (CCU) that manages the available network resources. Our aim is to enable the CCU to jointly allocate the transmission power and source-channel coding rates for each node, under four different quality-driven criteria that take into consideration the varying motion characteristics of each recorded video. For this purpose, we studied two approaches with a different tradeoff of quality and complexity. The first one allocates the resources individually for each sensor, whereas the second clusters them according to the recorded level of motion. In order to address the dynamic nature of the recorded scenery and re-allocate the resources whenever it is dictated by the changes in the amount of motion in the scenery, we propose a mechanism based on the particle swarm optimization algorithm, combined with two restarting schemes that either exploit the previously determined resource allocation or conduct a rough estimation of it. Experimental simulations demonstrate the efficiency of the proposed approaches.

A Stochastic Flows Approach for Asset Allocation with Hidden Economic Environment

Directory of Open Access Journals (Sweden)

Tak Kuen Siu

2015-01-01

Full Text Available An optimal asset allocation problem for a quite general class of utility functions is discussed in a simple two-state Markovian regime-switching model, where the appreciation rate of a risky share changes over time according to the state of a hidden economy. As usual, standard filtering theory is used to transform a financial model with hidden information into one with complete information, where a martingale approach is applied to discuss the optimal asset allocation problem. Using a martingale representation coupled with stochastic flows of diffeomorphisms for the filtering equation, the integrand in the martingale representation is identified which gives rise to an optimal portfolio strategy under some differentiability conditions.

Bandwidth selection in smoothing functions | Kibua | East African ...

African Journals Online (AJOL)

... inexpensive and, hence, worth adopting. We argue that the bandwidth parameter is determined by two factors: the kernel function and the length of the smoothing region. We give an illustrative example of its application using real data. Keywords: Kernel, Smoothing functions, Bandwidth > East African Journal of Statistics ...

Reconstitution of Low Bandwidth Reaction History

International Nuclear Information System (INIS)

May, M.; Clancy, T.; Fittinghoff, D.; Gennaro, P.; Hagans, K.; Halvorson, G.; Lowry, M.; Perry, T.; Roberson, P.; Smith, D.; Teruya, A.; Blair, J.; Davis, B.; Hunt, E.; Emkeit, B.; Galbraith, J.; Kelly, B.; Montoya, R.; Nickel, G.; Ogle, J.; Wilson, K.; Wood, M.

2004-01-01

The goal of the Test Readiness Program is to transition to a 24 month test readiness posture and if approved move to an 18-month posture. One of the key components of the Test Readiness Program necessary to meet this goal is the reconstitution of the important diagnostics. Since the end of nuclear testing, the ability to field diagnostics on a nuclear test has deteriorated. Reconstitution of diagnostics before those who had experience in nuclear testing either retire or leave is essential to achieving a shorter test readiness posture. Also, the data recording systems have not been used since the end of testing. This report documents the reconstitution of one vital diagnostic: the low bandwidth reaction history diagnostic for FY04. Reaction history is one of the major diagnostics that has been used on all LLNL and LANL tests since the early days of nuclear testing. Reaction history refers to measuring the time history of the gamma and neutron output from a nuclear test. This gives direct information on the nuclear reactions taking place in the device. The reaction history measurements are one of the prime measurements the nuclear weapon scientists use to validate their models of device performance. All tests currently under consideration require the reaction history diagnostic. Thus moving to a shorter test readiness posture requires the reconstitution of the ability to make reaction history measurements. Reconstitution of reaction history was planned to be in two steps. Reaction history measurements that have been used in the past can be broadly placed into two categories. The most common type of reaction history and the one that has been performed on virtually all nuclear tests is termed low bandwidth reaction history. This measurement has a time response that is limited by the bandpass of kilometer length coaxial cables. When higher bandwidth has been required for specific measurements, fiber optic techniques have been used. This is referred to as high-bandwidth

Capital Allocation Effects of Financial Reporting Regulation

NARCIS (Netherlands)

Koenigsgruber, R.

2012-01-01

This paper analyses the effects of stricter financial reporting enforcement on capital allocation and reporting quality in a game-theoretic model and derives conclusions about optimal enforcement strictness. Analysis of the model shows that reporting quality strictly increases with tighter

Optimal Frequency Ranges for Sub-Microsecond Precision Pulsar Timing

Science.gov (United States)

Lam, Michael Timothy; McLaughlin, Maura; Cordes, James; Chatterjee, Shami; Lazio, Joseph

2018-01-01

Precision pulsar timing requires optimization against measurement errors and astrophysical variance from the neutron stars themselves and the interstellar medium. We investigate optimization of arrival time precision as a function of radio frequency and bandwidth. We find that increases in bandwidth that reduce the contribution from receiver noise are countered by the strong chromatic dependence of interstellar effects and intrinsic pulse-profile evolution. The resulting optimal frequency range is therefore telescope and pulsar dependent. We demonstrate the results for five pulsars included in current pulsar timing arrays and determine that they are not optimally observed at current center frequencies. We also find that arrival-time precision can be improved by increases in total bandwidth. Wideband receivers centered at high frequencies can reduce required overall integration times and provide significant improvements in arrival time uncertainty by a factor of $\\sim$$\\sqrt{2}$ in most cases, assuming a fixed integration time. We also discuss how timing programs can be extended to pulsars with larger dispersion measures through the use of higher-frequency observations.

Mum, why do you keep on growing? Impacts of environmental variability on optimal growth and reproduction allocation strategies of annual plants.

Science.gov (United States)

De Lara, Michel

2006-05-01

In their 1990 paper Optimal reproductive efforts and the timing of reproduction of annual plants in randomly varying environments, Amir and Cohen considered stochastic environments consisting of i.i.d. sequences in an optimal allocation discrete-time model. We suppose here that the sequence of environmental factors is more generally described by a Markov chain. Moreover, we discuss the connection between the time interval of the discrete-time dynamic model and the ability of the plant to rebuild completely its vegetative body (from reserves). We formulate a stochastic optimization problem covering the so-called linear and logarithmic fitness (corresponding to variation within and between years), which yields optimal strategies. For "linear maximizers'', we analyse how optimal strategies depend upon the environmental variability type: constant, random stationary, random i.i.d., random monotonous. We provide general patterns in terms of targets and thresholds, including both determinate and indeterminate growth. We also provide a partial result on the comparison between ;"linear maximizers'' and "log maximizers''. Numerical simulations are provided, allowing to give a hint at the effect of different mathematical assumptions.

Game-theoretic approaches to optimal risk sharing

NARCIS (Netherlands)

Boonen, T.J.

2014-01-01

This Ph.D. thesis studies optimal risk capital allocation and optimal risk sharing. The first chapter deals with the problem of optimally allocating risk capital across divisions within a financial institution. To do so, an asymptotic approach is used to generalize the well-studied Aumann-Shapley

Wide-bandwidth bilateral control using two-stage actuator system

International Nuclear Information System (INIS)

Kokuryu, Saori; Izutsu, Masaki; Kamamichi, Norihiro; Ishikawa, Jun

2015-01-01

This paper proposes a two-stage actuator system that consists of a coarse actuator driven by a ball screw with an AC motor (the first stage) and a fine actuator driven by a voice coil motor (the second stage). The proposed two-stage actuator system is applied to make a wide-bandwidth bilateral control system without needing expensive high-performance actuators. In the proposed system, the first stage has a wide moving range with a narrow control bandwidth, and the second stage has a narrow moving range with a wide control bandwidth. By consolidating these two inexpensive actuators with different control bandwidths in a complementary manner, a wide bandwidth bilateral control system can be constructed based on a mechanical impedance control. To show the validity of the proposed method, a prototype of the two-stage actuator system has been developed and basic performance was evaluated by experiment. The experimental results showed that a light mechanical impedance with a mass of 10 g and a damping coefficient of 2.5 N/(m/s) that is an important factor to establish good transparency in bilateral control has been successfully achieved and also showed that a better force and position responses between a master and slave is achieved by using the proposed two-stage actuator system compared with a narrow bandwidth case using a single ball screw system. (author)

Irrational time allocation in decision-making.

Science.gov (United States)

Oud, Bastiaan; Krajbich, Ian; Miller, Kevin; Cheong, Jin Hyun; Botvinick, Matthew; Fehr, Ernst

2016-01-13

Time is an extremely valuable resource but little is known about the efficiency of time allocation in decision-making. Empirical evidence suggests that in many ecologically relevant situations, decision difficulty and the relative reward from making a correct choice, compared to an incorrect one, are inversely linked, implying that it is optimal to use relatively less time for difficult choice problems. This applies, in particular, to value-based choices, in which the relative reward from choosing the higher valued item shrinks as the values of the other options get closer to the best option and are thus more difficult to discriminate. Here, we experimentally show that people behave sub-optimally in such contexts. They do not respond to incentives that favour the allocation of time to choice problems in which the relative reward for choosing the best option is high; instead they spend too much time on problems in which the reward difference between the options is low. We demonstrate this by showing that it is possible to improve subjects' time allocation with a simple intervention that cuts them off when their decisions take too long. Thus, we provide a novel form of evidence that organisms systematically spend their valuable time in an inefficient way, and simultaneously offer a potential solution to the problem. © 2016 The Author(s).

Ramsey waits: allocating public health service resources when there is rationing by waiting.

Science.gov (United States)

Gravelle, Hugh; Siciliani, Luigi

2008-09-01

The optimal allocation of a public health care budget across treatments must take account of the way in which care is rationed within treatments since this will affect their marginal value. We investigate the optimal allocation rules for public health care systems where user charges are fixed and care is rationed by waiting. The optimal waiting time is higher for treatments with demands more elastic to waiting time, higher costs, lower charges, smaller marginal welfare loss from waiting by treated patients, and smaller marginal welfare losses from under-consumption of care. The results hold for a wide range of welfarist and non-welfarist objective functions and for systems in which there is also a private health care sector. They imply that allocation rules based purely on cost effectiveness ratios are suboptimal because they assume that there is no rationing within treatments.

Energy Efficient Resource Allocation for Phantom Cellular Networks

KAUST Repository

Abdelhady, Amr

2016-04-01

Multi-tier heterogeneous networks have become an essential constituent for next generation cellular networks. Meanwhile, energy efficiency (EE) has been considered a critical design criterion along with the traditional spectral efficiency (SE) metric. In this context, we study power and spectrum allocation for the recently proposed two-tier network architecture known as phantom cellular networks. The optimization framework includes both EE and SE. First, we consider sparsely deployed cells experiencing negligible interference and assume perfect channel state information (CSI). For this setting, we propose an algorithm that finds the SE and EE resource allocation strategies. Then, we compare the performance of both design strategies versus number of users, and phantom cells share of the total available resource units (RUs). We aim to investigate the effect of some system parameters to achieve improved SE performance at a non-significant loss in EE performance, or vice versa. It is found that increasing phantom cells share of RUs decreases the SE performance loss due to EE optimization when compared with the optimized SE performance. Second, we consider the densely deployed phantom cellular networks and model the EE optimization problem having into consideration the inevitable interference and imperfect channel estimation. To this end, we propose three resource allocation strategies aiming at optimizing the EE performance metric of this network. Furthermore, we investigate the effect of changing some of the system parameters on the performance of the proposed strategies, such as phantom cells share of RUs, number of deployed phantom cells within a macro cell coverage, number of pilots and the maximum power available for transmission by the phantom cells BSs. It is found that increasing the number of pilots deteriorates the EE performance of the whole setup, while increasing maximum power available for phantom cells transmissions reduces the EE of the whole setup in a

What money can't buy: allocations with priority lists, lotteries and queues

OpenAIRE

Daniele Condorelli

2009-01-01

I study the welfare optimal allocation of a number of identical and indivisible objects to a set of heterogeneous risk-neutral agents under the hypothesis that money is not available. Agents have independent private values, which represent the maximum time that they are will- ing to wait in line to obtain a good. A priority list, which ranks agents according to their expected values, is optimal when hazard rates of the distributions of values are increasing. Queues, which allocates the ob- je...

Centralized Allocation in Multiple Markets

DEFF Research Database (Denmark)

Monte, Daniel; Tumennasan, Norovsambuu

The problem of allocating indivisible objects to different agents, where each indi vidual is assigned at most one object, has been widely studied. Pápai (2000) shows that the set of strategy-proof, nonbossy, Pareto optimal and reallocation-proof rules are hierarchical exchange rules | generalizat...... and nonbossy rules are sequential dictatorships, a special case of Pápai's hierarchical exchange rules....

Design, Performance and Optimization for Multimodal Radar Operation

Directory of Open Access Journals (Sweden)

Surendra S. Bhat

2012-09-01

Full Text Available This paper describes the underlying methodology behind an adaptive multimodal radar sensor that is capable of progressively optimizing its range resolution depending upon the target scattering features. It consists of a test-bed that enables the generation of linear frequency modulated waveforms of various bandwidths. This paper discusses a theoretical approach to optimizing the bandwidth used by the multimodal radar. It also discusses the various experimental results obtained from measurement. The resolution predicted from theory agrees quite well with that obtained from experiments for different target arrangements.

Optimum fuel allocation in parallel steam generator systems

International Nuclear Information System (INIS)

Bollettini, U.; Cangioli, E.; Cerri, G.; Rome Univ. 'La Sapienza'; Trento Univ.

1991-01-01

An optimization procedure was developed to allocate fuels into parallel steam generators. The procedure takes into account the level of performance deterioration connected with the loading history (fossil fuel allocation and maintenance) of each steam generator. The optimization objective function is the system hourly cost, overall steam demand being satisfied. Costs are due to fuel and electric power supply and to plant depreciation and maintenance as well. In order to easily updata the state of each steam generator, particular care was put in the general formulation of the steam production function by adopting a special efficiency-load curve description based on a deterioration scaling parameter. The influence of the characteristic time interval length on the optimum operation result is investigated. A special implementation of the method based on minimum cost paths is suggested

The fundamental optimal relations of the allocation, cost and effectiveness of the heat exchangers of a Carnot-like power plant

Energy Technology Data Exchange (ETDEWEB)

Aragon-Gonzalez, G; Canales-Palma, A; Leon-Galicia, A; Rivera-Camacho, J M [PDPA, UAM-Azcapotzalco, Av San Pablo 180, Col. Reynosa, Azcapotzalco, 02200 Mexico, DF (Mexico)], E-mail: gag@correo.azc.uam.mx