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基于粒子群的网格任务调度算法研究
引用本文:季一木,王汝传. 基于粒子群的网格任务调度算法研究[J]. 通信学报, 2007, 28(10): 60-66
作者姓名:季一木  王汝传
作者单位:1. 南京邮电大学,计算机学院,江苏,南京,210003
2. 南京邮电大学,计算机学院,江苏,南京,210003;南京大学,计算机软件新技术国家重点实验室,江苏,南京,210093
基金项目:国家自然科学基金;江苏省自然科学基金;江苏省高技术研究发展计划项目;国家高技术研究发展计划(863计划);江苏省南京市高科技项目;国家重点实验室基金;江苏省重点实验室基金
摘    要:为了更好地解决异构动态环境下的资源管理问题,提出了一种网格环境下的任务调度模型。该模型考虑了当前网格虚拟组织下的计算资源、存储资源和带宽资源,模型的最优化目标是实现三者利用率最高和代价最低,即构造min-max函数。与遗传算法相比,利用粒子群优化算法对min-max函数求解提高了资源的利用率和任务的执行效率,同时在随着迭代次数增加的情况下,搜索速度、寻优率和避免早熟方面也有明显的提高。

关 键 词:网格计算  任务调度  粒子群优化算法  遗传算法
文章编号:1000-436X(2007)10-0060-07
修稿时间:2007-03-02

Study on PSO algorithm in solving grid task scheduling
JI Yi-mu,WANG Ru-chuan. Study on PSO algorithm in solving grid task scheduling[J]. Journal on Communications, 2007, 28(10): 60-66
Authors:JI Yi-mu  WANG Ru-chuan
Affiliation:1. Department of Computer Science and Technology, Nanjing University of Posts and Telecommunications, Nanjing 210003, China; 2. State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210093, China
Abstract:In order to resolve the resources management in dynamic heterogeneous environment,a kind of task schedul-ing model for grid environment was proposed.The model considers the computing resources,storage resources and bandwidth resources of current virtual organization in grid,and the optimal target of the model is to achieve the max-ratio and the min-cost of the above three kinds of resources,viz to build the min-max function.To compare with GA(genetic algorithm),PSO(particle swarm optimization) was applied in solving the min-max function so that the ratio of using re-sources and the efficiency of scheduling task are enhanced.Meanwhile,with the rise of iterative times,the searching speed,optimization ratio and avoiding pre-maturity are also distinctly enhanced.
Keywords:grid computing  task scheduling  particle swarm optimization algorithm  genetic algorithm
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