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6th International Conference on Wireless Communications, Networking and Mobile Computing (WICOM)

作者： Wang Meihong Zeng Wenhua Xiamen Univ Software Sch Xiamen Fujian Peoples R China

ISBN: (纸本)9781424437092

The grid computational environment is very suit to meet the computational demands of large, diverse groups of tasks. And the task scheduling problem in it has been a research hotspot in recent years. Some heuristic methods have been used to optimize it and have got some good results. However, selecting the best one to use in a given environment remains a difficult problem, because comparisons are often clouded by different underlying assumptions in the original study of each algorithm. Some comparisons have been made to them, but some new algorithms are not included in the comparisons. So, in this paper, four popular researched algorithms recently are selected, implemented, and analyzed. The four heuristics are Genetic Algorithm, Ant Colony Optimization Algorithm, Particle Swarm Optimization Algorithm and Simulated Annealing Algorithm. The evaluations include the schedule creating time, the makespan and the mean response time. It shows that for the cases studied here, the PSO heuristic performs better in comparison to the other techniques.

关键词： task scheduling computational grid genetic algorithm ant colony algorithm particle swarm optimization simulated annealing algorithm

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A general model for the generation and scheduling of parameter sweep experiments in computational grid Environments

A general model for the generation and scheduling of paramet...

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International Conference on computational Science (ICCS)

作者： Diaz, Javier Reyes, Sebastian Badia, Rosa M. Nino, Alfonso Munoz-Caro, Camelia Univ Castilla La Mancha Escuela Super Informat Grp Quim Computac & Computac Alto Rendimiento Paseo Univ 4 E-13071 Ciudad Real Spain CSIC Barcelona Supercomp Ctr Spanish Natl Res Council E-08034 Barcelona Spain CSIC IIIA Artificial Intelligence Res Inst Spanish Natl Res Council E-08034 Barcelona Spain

Parameter sweep experiments (PSE) involve several issues. In this work, we consider two of them: the generation of the parameters space and the scheduling of the associated tasks. Thus, we propose a general model to generate the parameters space of any PSE applying the Nested Summation Symbol operator. On the other hand, for the scheduling of these kinds of problems, we test an adaptive scheduling approach with fault tolerance. This approach has been implemented, using the DRMAA-C version for gridWay, to allocate tasks in a grid environment. In the tests, the scheduler shows a good performance. Moreover, the CPU usage of the scheduler is quite low. (C) 2010 Published by Elsevier Ltd.

关键词： Nested Summation Symbol Adaptive Scheduling computational grid Parameter Sweep

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Influence of Geometric Scaling on Linear Cascade Aerodynamic Performance

Influence of Geometric Scaling on Linear Cascade Aerodynamic...

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Asia-Pacific International Symposium on Aerospace Technology (APISAT)

作者： Chen Fen-fen Gui Xing-min Jin Dong-hai Qiu Dao-bin Beihang Univ 37th Xueyuan Rd Beijing 100191 Peoples R China

A linear cascade has been geometrically scaled according to the similarity theory, a series of three dimensional numerical simulations are conducted on these geometric similar cascades with the CFD software. The differences of the aerodynamic performance between the original and the scaled linear cascades are investigated in details. The result shows that with the increasing of linear cascade size, the shape factor decreases at the same relative arc length position and the location of separation point moves towards trailing edge, resulting in the total pressure loss coefficient decreases and the static pressure raises coefficient increases. (C) 2015 Published by Elsevier Ltd.

关键词： geometric scaling linear cascade numerical simulation aerodynamic performance boundary layer thickness computational grid

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A general model for the generation and scheduling of parameter sweep experiments in computational grid environments

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Procedia Computer Science 2010年第1期1卷 565-572页

作者： Javier Díaz Sebastián Reyes Rosa M. Badia Alfonso Niño Camelia Muñoz-Caro Grupo de Química Computacional y Computación de Alto Rendimiento Escuela Superior de Informática Universidad de Castilla-La Mancha Paseo de la Universidad 4 13071 Ciudad Real Spain Barcelona Supercomputing Center and IIIA - Artificial Intelligence Research Institute CSIC - Spanish National Research Council Jordi Girona 29. E-08034 Barcelona Spain

关键词： Nested summation symbol Adaptive scheduling computational grid Parameter sweep

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Influence of Geometric Scaling on Linear Cascade Aerodynamic Performance

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Procedia Engineering 2015年 99卷 499-506页

作者： Chen Fen-fen Gui Xing-min Jin Dong-hai Qiu Dao-bin Beihang University 37thXueyuan Road Haidian District Beijing 100191 China

A linear cascade has been geometrically scaled according to the similarity theory,aseries of three dimensional numerical simulationsare conducted on these geometric similarcascades withthe CFD *** differences of the aerodynamic performance betweenthe original and the scaled linear cascades are investigated in *** result showsthatwith the increasing of linear cascade size,the shapefactor decreases at the same relative arc length position and the locationof separation point moves towards trailing edge,resultinginthe total pressure loss coefficient decreasesand the static pressureraises coefficient increases.

关键词： geometric scaling linear cascade numerical simulation aerodynamic performance boundary layer thickness computational grid

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Task Scheduling of computational grid Based on Particle Swarm Algorithm

Task Scheduling of Computational Grid Based on Particle Swar...

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The Third International Joint Conference on computational Science and Optimization(第三届计算科学与优化国际大会 CSO 2010)

作者： Hui Li Lifeng Wang Jianhong Liu College of Communication and Electronic Engineering Qiqihar UniversityQiqihar Heilongjiang 161006C College of Mechanical and Electrical Engineering Northeast Forestry UniversityHarbin Heilongjiang 1 College of Chemistry and Chemical Engineering Qiqihar University Qiqihar Heilongjiang 161006 China

The traditional scheduling theory can only get the approximate optimal solution of the problem, and most is to consider algorithms on a single task or independent multitask scheduling. It presents a particle swarm algorithm to solve the task scheduling problem of computational grid. It builds a task scheduling model of computational grid, changes the particle swarm algorithm in continuous space searching to an integer space searching, selects the appropriate inertia weight value, and enhances the searching capabilities of the algorithm. Through comparison with genetic algorithm, hybrid algorithm, and ant algorithm, the results show that the grid task scheduling algorithm has some advantages.

关键词： particle swarm computational grid task scheduling scheduling model

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A new fuzzy negotiation protocol for grid resource allocation

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JOURNAL OF NETWORK AND COMPUTER APPLICATIONS 2014年第Jan.期37卷 89-126页

作者： Adabi, Sepideh Movaghar, Ali Rahmani, Amir Masoud Beigy, Hamid Dastmalchy-Tabrizi, Hengameh Islamic Azad Univ North Tehran Branch Dept Comp Engn Tehran Iran Sharif Univ Technol Dept Comp Engn Tehran Iran Islamic Azad Univ Sci & Res Branch Dept Comp Engn Tehran Iran Univ Tehran Sch Elect & Comp Engn Tehran Iran

In real-life trading, relaxing decisions in the face of trading pressure is common. Similarly, in market-based grid resource allocation problem designing negotiator agents with the flexibility to relax their decision to (quickly) complete a deal in the face of intense grid Market Pressure (GMP) is essential. To make this idea possible, we design Enhanced Market- and Behavior-driven Negotiation Agents (EMBDNAs) that adopt new fuzzy negotiation protocol. The protocol focuses on both (1) enhancing Rubinstein's sequential alternating offer protocol to handle multiple trading opportunities and market competition and (2) designing two new Fuzzy grid Market Pressure Determination Systems (FGMPDSs) for both grid resource consumers and grid resource owners to guide negotiator agents in relaxing their bargaining terms under intense GMP to enhance their chance of successfully acquiring/leasing out resources. Implementing the idea in an agent-based testbed, an experiment for evaluating and comparing EMBDNA against EMDA (Enhanced Market-Driven Agent) and our previous work in name MBDNA (Market- and Behavior-driven Negotiation Agent) were carried out through stochastic simulations. While EMDA relaxes its bargaining term in the face of intense GMP by considering just two relaxation factors the MBDNA uses the same negotiation strategy as EMBDNA but does not relax its bargaining term in the face of intense GMP. The results show that adopting the new fuzzy negotiation protocol, EMBDNAs outperform MBDNAs and EMDAs. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： computational grid Resource allocation Automated negotiation Multiagent systems Intelligent agent

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Green Energy Model for grid Resource Allocation: A Graph Theoretic Approach

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INTERNATIONAL JOURNAL OF grid AND HIGH PERFORMANCE COMPUTING 2014年第2期6卷 52-73页

作者： Kaushik, Achal Vidyarthi, Deo Prakash Jawaharlal Nehru Univ Sch Comp & Syst Sci New Delhi India IP Univ Bhagwan Parshuram Inst Techonol Dept Comp Sci Engn Delhi India Banaras Hindu Univ Dept Comp Sci Varanasi Uttar Pradesh India IACSIT Singapore Singapore IAENG New Delhi India

The computational grid helps in faster execution of compute intensive jobs. Many characteristic parameters are intended to be optimized while making resource allocation for job execution in computational grid. Most often, the green energy aspect, in which one tries for better energy utilization, is ignored while allocating the grid resources to the jobs. The conventional systems, which propose energy efficient scheduling strategies, ignore other Quality of Service parameters while scheduling the jobs. The proposed work tries to optimize the energy in resource allocation to make it a green energy model. It explores how effectively the jobs submitted to the grid can be executed for optimal energy uses making no compromise on other desired related characteristic parameters. A graph theoretic model has been developed for this purpose. The performance study of the proposed green energy model has been experimentally evaluated by simulation. The result reveals the benefits and gives an insight for an energy efficient resource allocation.

关键词： computational grid Green Energy Minimum Spanning Tree (MST) Quality of Service (QoS) Resource Allocation

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Stochastic Analysis of Reaction-Diffusion Processes

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BULLETIN OF MATHEMATICAL BIOLOGY 2014年第4期76卷 854-894页

作者： Hu, Jifeng Kang, Hye-Won Othmer, Hans G. Univ Minnesota Sch Math Minneapolis MN 55455 USA Ohio State Univ Math Biosci Inst Columbus OH 43210 USA Univ Minnesota Digital Technol Ctr Minneapolis MN 55455 USA

Reaction and diffusion processes are used to model chemical and biological processes over a wide range of spatial and temporal scales. Several routes to the diffusion process at various levels of description in time and space are discussed and the master equation for spatially discretized systems involving reaction and diffusion is developed. We discuss an estimator for the appropriate compartment size for simulating reaction-diffusion systems and introduce a measure of fluctuations in a discretized system. We then describe a new computational algorithm for implementing a modified Gillespie method for compartmental systems in which reactions are aggregated into equivalence classes and computational cells are searched via an optimized tree structure. Finally, we discuss several examples that illustrate the issues that have to be addressed in general systems.

关键词： computational grid Stochastic analysis Gillespie method

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computational grid based Neural Network Ensemble Learning Platform and Its Application

Computational Grid based Neural Network Ensemble Learning Pl...

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3rd International Conference on Management of e-Commerce and e-Government

作者： Liu, Yue Teng, Zaixia Zhang, Bofeng Shanghai Univ Sch Comp Engn & Sci Shanghai Peoples R China

ISBN: (纸本)9780769537788

Neural network ensemble is a recently developed technology, which trains a few of neural networks and then combines their prediction results. The generalization ability of an ensemble can be much better than that of a single learner. However, it is time-consuming to train so many neural networks. In order to overcome this disadvantage, MPI (Message Passing Interface) technique was employed to the Parallel Implementation of the RBF neural network ensemble, which is named PDNNE in our previous work [1]. In this paper, a unified parallelization strategy based on PDNNE is proposed to reduce the complexity and improve the efficiency of the ensemble's construction for the bagging-based neural network ensembles (UPDNNE). And then a neural network ensemble learning platform (NNELP) based on the Shanghai University E-grid Platform is designed and implemented to make the user conveniently and efficiently apply the ensemble methods to solve the real-world problems furthermore. The experiments on UCI datasets and the time sequence forecasting of strong earthquakes in China's mainland demonstrate the efficiency of the NNELP.

关键词： Neural network ensemble computational grid Earthquake Prediction

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