Research and Realization of an Optimized Resource Allocation Algorithm in Grid Computing System

ZHOU Jian-hong; MA Mao-de

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Research and Realization of an Optimized Resource Allocation Algorithm in Grid Computing System

更新时间：2026-09-04

- Research and Realization of an Optimized Resource Allocation Algorithm in Grid Computing System
- Vol. 33, Issue 11, Pages: 20-24(2016)
- 作者机构：
  
  1. 中科院成都信息技术有限公司(原中国科学院机构成都计算所),四川,成都,610041
  2. 新加坡南洋理工大学, 电子电气工程学院,新加坡,639798
  3. 四川大学锦城学院电子信息工程系,四川,成都,611731
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2016
- 稿件说明：
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周建鸿, 马懋德. 优化的资源配置算法在网格计算系统中的实现[J]. 微电子学与计算机, 2016, 33(11): 20-24.

ZHOU Jian-hong, MA Mao-de. Research and Realization of an Optimized Resource Allocation Algorithm in Grid Computing System[J]. 2016, 33(11): 20-24.
周建鸿, 马懋德. 优化的资源配置算法在网格计算系统中的实现[J]. 微电子学与计算机, 2016, 33(11): 20-24. DOI：

ZHOU Jian-hong, MA Mao-de. Research and Realization of an Optimized Resource Allocation Algorithm in Grid Computing System[J]. 2016, 33(11): 20-24. DOI：

摘要

资源配置算法是影响网格计算系统性能的一个最重要的因素.本文提出了一个基于资源优化配置算法的网格计算系统

系统包含网格用户、网格broker

网格资源和网格信息服务中心四个部分.其中重点介绍了资源优化配置算法

包含了用户端的资源配置与资源端的请求排列两部分.通过这两部分算法的优化

可以将请求分配到最合适的资源并且按照用户要求被处理.最后将本算法与两个已有的资源配置算法依据请求完成成功率、完成时间、平均等待时间三个参数进行对比

体现出本系统的优越性.

Abstract

Grid computing has become one of the most popular topics in both research community and commercial companies. Allocation policy is one of the most important factors

which affect the performance of Grid Computing system. A new Grid Computing System based on an optimized resource allocation algorithm was proposed in this paper. It contains four components: Grid User

Grid Broker

Grid Resource and Grid Information Service. The optimized resource allocation algorithm

consisting of user side resource allocation and resource side job scheduling

was emphasized in this paper. With the combination of both sides efforts

the jobs will be allocated to the most appropriate resources and completed in the most suitable order to meet the requirements of users. At last

the experiments and results comparison with traditional particle swarm optimization and Max-min scheduling are presented

which proves that the proposed algorithm has better performance than the other two algorithms.

关键词

Keywords

references

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