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Combinatorial algorithms for computational science and engineering

Journal of Physics: Conference Series 2008年第1期125卷

作者： Boman, E.G. Bozdag, D. Catalyurek, U.V. Devine, K.D. Gebremedhin, A.H. Hovland, P.D. Pothen, A. Discrete Algorithms and Math Department Sandia National Laboratories Albuquerque NM 87185 United States Biomedical Informatics and Electrical and Computer Engineering Ohio State University Columbus OH 43210 United States Department of Computer Sciences Computing Research Institute Purdue University West Lafayetter IN 47907 United States Mathematics and Computer Science Division Argonne National Laboratory Argonne IL 60439 United States

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The X-scale challenge

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14th European PVM/MPI Users' Group Meeting on Parallel Virtual Machine and Message Passing Interface

作者： Bosilca, George Innovative Computing Laboratory Electrical Engineering and Computer Science Department University of Tennessee Knoxville TN United States

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Energy-aware scheduling with deadline and reliability constraints in wireless networks

Energy-aware scheduling with deadline and reliability constr...

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International Conference on Broadband Networks (BroadNets)

作者： G. Sudha Anil Kumar G. Manimaran Z. Wang Real Time Computing and Networking Laboratory Department of Electrical and Computer Engineering Iowa State University Ames IA USA

ISBN: (纸本)9781424414321

In this paper, we address the problem of scheduling a set of periodic real-time messages in a wireless network with the objective of minimizing the total energy consumption while meeting deadline and reliability constraints. We formally prove that this problem is NP-hard and solve it in two stages. First, we consider a simple model that assumes that the wireless channel is completely reliable and the network is fully provisioned. Using the technique of employing multiple hop-by-hop transmissions instead of a single direct hop transmission as the basis, we prove that the strategy of choosing the hop distances such that they are equidistant is optimal in terms of energy consumption under the deadline constraint. Based on the intuition provided by the optimal strategy, we present heuristic scheduling algorithms for a more realistic wireless channel model and network condition. Our simulation results show that the proposed scheduling algorithms provide significant energy savings over the baseline algorithms

关键词： Wireless networks Energy consumption Scheduling algorithm Wireless application protocol Throughput Access protocols Streaming media Resource management Processor scheduling computer network reliability

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Energy-Aware Scheduling of real-time Tasks in Wireless Networked Embedded Systems

Energy-Aware Scheduling of Real-Time Tasks in Wireless Netwo...

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real-time Systems Symposium (RTSS)

作者： G. Sudha Anil Kumar G. Manimaran Z. Wang Real-Time Computing and Networking Laboratory Department of Electrical and Computer Engineering Iowa State University Ames IA USA

Recent technological advances have opened up several distributed real-time applications involving battery-driven embedded devices with local processing and wireless communication capabilities. Energy management is the key issue in the design and operation of such systems. In this paper, we consider a single-hop networked real-time embedded system where each node supports both dynamic voltage scaling (DVS) and dynamic modulation scaling (DMS) power management techniques to tradeoff time for energy savings. In this model, we address the problem of scheduling periodic complex tasks where each task consists of several precedence constrained message passing sub-tasks. Our contributions towards this problem are twofold. First, we analyze the system level energy-time tradeoffs considering both the computation and communication workloads by defining a novel energy gain metric. We then present static (centralized) and dynamic (distributed) energy gain based slack allocation algorithms which reduce the total energy consumption, while guaranteeing the ready time, deadline and precedence constraints. We compare the performance of the proposed algorithms with several baseline algorithms through simulation studies. Our results show that the proposed algorithms perform significantly better than the baseline algorithms for the simulated conditions. Finally, we identify several interesting energy-aware research problems in the area of networked real-time embedded systems.

关键词： real time systems Embedded system Energy management Wireless communication Dynamic voltage scaling Voltage control computer network management Power system management Power system modeling Processor scheduling

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ParalleX: A study of a new parallel computation model

ParalleX: A study of a new parallel computation model

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21st International Parallel and Distributed Processing Symposium, IPDPS 2007

作者： Gao, Guang R. Sterling, Thomas Stevens, Rick Hereld, Mark Zhu, Weirong Department of Electrical and Computer Engineering University of Delaware Center for Advanced Computing Research California Institute of Technology Department of Computer Science Louisiana State University Mathematics and Computer Science Division Argonne National Laboratory

ISBN: (纸本)1424409101

This paper proposes the study of a new computation model that attempts to address the underlying sources of performance degradation (e.g. latency, overhead, and starvation) and the difficulties of programmer productivity (e.g. explicit locality management and scheduling, performance tuning, fragmented memory, and synchronous global barriers) to dramatically enhance the broad effectiveness of parallel processing for high end computing. In this paper, we present the progress of our research on a parallel programming and execution model - mainly, ParalleX. We describe the functional elements of ParalleX, one such model being explored as part of this project. We also report our progress on the development and study of a subset of ParalleX - the LITL-X at University of Delaware. We then present a novel architecture model - Gilgamesh II - as a ParalleX processing architecture. A design point study of Gilgamesh II and the architecture concept strategy are presented. © 2007 IEEE.

关键词： Parallel processing systems

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Optimal control of class of non-linear plants using artificial immune systems: Application of the clonal selection algorithm

Optimal control of class of non-linear plants using artifici...

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2007 IEEE 22nd International Symposium on Intelligent Control, ISIC 2007

作者： Panimadai Ramaswamy, S.A. Venayagamoorthy, G.K. Balakrishnan, S.N. IEEE Department of Electrical and Computer Engineering University of Missouri Rolla MO 65409 United States Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri Rolla MO 65409 United States Department of Mechanical Aerospace and Engineering Mechanics University of Missouri Rolla MO 65409 United States

ISBN: (纸本)142440441X

The function of natural immune system is to protect the living organisms against invaders/pathogens. Artificial Immune System (AIS) is a computational intelligence paradigm inspired by the natural immune system. Diverse engineering problems have been solved in the recent past using AIS. Clonal selection is one of the few algorithms that belong to the family of AIS techniques. Clonal selection algorithm is the computational implementation of the clonal selection principle. The process of affinity maturation of the immune system is explicitly incorporated in this algorithm. This paper presents the application of AIS for the optimal control of a class of non-linear plants which are affine in control. The clonal selection algorithm is adapted for optimal control. A new mutation operator that operates on real values and one that aids in fast convergence is developed in this paper. AIS is used to obtain constant coefficient Kalman gain matrices. The validation and evaluation of the results thus obtained are carried out by comparing with standard and the widely used State Dependent Algebraic Riccati Equation (SDARE) method for the non-linear plants. In case of non-linear systems with hard state constraints, the SDARE formulation requires the use of mathematically involved expressions to incorporate these state constraints. However, the modified clonal selection algorithm developed in this paper has been used with hardly any changes to incorporate the hard state constraints and obtain the Kalman gain matrix. © 2007 IEEE.

关键词： Artificial intelligence

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Preface

Communications in Computer and Information Science

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Communications in computer and Information science 2008年 15卷 V-VI页

作者： Huang, De-Shuang Wunsch, Donald Levine, Daniel S. Jo, Kang-Hyun Institute of Intelligent Machines Intelligent Computing Laboratory Chinese Academy of Sciences HefeiAnhui230031 China Missouri University of Science & Technology Department of Electrical and Computer Engineering Applied Computational Intelligence Laboratory RollaMO65409-0040 United States University of Texas at Arlington Department of Psychology ArlingtonTX76019-0528 United States University of Ulsan Graduate School of Electrical Engineering Ulsan680-749 Korea Republic of

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Dynamic modeling of wind farms with fixed-speed wind turbine generators

Dynamic modeling of wind farms with fixed-speed wind turbine...

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2007 IEEE Power engineering Society General Meeting, PES

作者： Wei, Qiao Harley, Ronald G. Venayagamoorthy, Ganesh K. IEEE School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA 30332-0250 United States University of KwaZulu-Natal Durban South Africa Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri-Rolla Rolla MO 65409-0249 United States

ISBN: (纸本)1424412986

A wind farm typically consists of a large number of individual wind turbine generators (WTGs) connected by an internal electrical network. To study the impact of wind farms on the dynamics of the power system, an important issue is to develop appropriate wind farm models to represent the dynamics of many individual WTGs. This paper presents various dynamic models, including a detailed model and three reduced-order equivalent models, of wind farms with fixed-speed WTGs. These models are developed and compared by simulation studies in the PSCAD/EMTDC environment under different wind velocity and fluctuation conditions as well as gird fault conditions. Concluding remarks are provided on how to choose an appropriate wind farm model for power system dynamic and transient studies. © 2007 IEEE.

关键词： Power plants

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Collaborative Routing Algorithm for Wireless Sensor Network Longevity

Collaborative Routing Algorithm for Wireless Sensor Network ...

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Intelligent Sensors, Sensor Networks and Information Processing Conference (ISSNIP)

作者： Shishir Bashyal Ganesh Kumar Venayagamoorthy Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri MO USA

This study proposes a new parameter for evaluating longevity of wireless sensor networks after showing that the existing parameters do not properly evaluate the performance of algorithms in increasing longevity. This study also proposes an ant inspired Collaborative Routing Algorithm for Wireless Sensor Network Longevity (CRAWL) that has scalability and adaptability features required in most wireless sensor networks. Using the proposed longevity metrics and implementing the algorithm in simulations, it is shown that CRAWL is much more adaptive to non-uniform distribution of available energy in sensor networks. The performance of CRAWL is compared to that of a non-collaborative algorithm. Both algorithms perform equally well when the available energy distribution is uniform but when the distribution is non-uniform, CRAWL is found to have 20.2% longer network life. CRAWL performance degraded by just 10.1% when the available energy was unevenly distributed in the sensor network proving the algorithms adaptability.

关键词： Collaboration Routing Wireless sensor networks Scalability Energy resources Protocols Sensor phenomena and characterization Monitoring Intelligent sensors Energy consumption

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An Estimation of Distribution Improved Particle Swarm Optimization Algorithm

An Estimation of Distribution Improved Particle Swarm Optimi...

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Intelligent Sensors, Sensor Networks and Information Processing Conference (ISSNIP)

作者： R. V. Kulkarni G. K. Venayagamoorthy Real-Time Power and Intelligent Systems Laboratory Department of Electrical and Computer Engineering University of Missouri MO USA

PSO is a powerful evolutionary algorithm used for finding global solution to a multidimensional problem. Particles in PSO tend to re-explore already visited bad solution regions of search space because they do not learn as a whole. This is avoided by restricting particles into promising regions through probabilistic modeling of the archive of best solutions. This paper presents hybrids of estimation of distribution algorithm and two PSO variants. These algorithms are tested on benchmark functions having high dimensionalities. Results indicate that the methods strengthen the global optimization abilities of PSO and therefore, serve as attractive choices to determine solutions to optimization problems in areas including sensor networks.

关键词： Particle swarm optimization Ant colony optimization Electronic design automation and methodology Probability distribution Benchmark testing Optimization methods Equations Genetic mutations Space exploration real time systems

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