电子学报 ›› 2009, Vol. 37 ›› Issue (2): 272-277.

• 论文 • 上一篇    下一篇

基于并行基因表达式编程的 网格资源分配算法

邓 松, 王汝传, 张 羽, 张建风   

  1. 南京邮电大学计算机学院,江苏南京 210003
  • 收稿日期:2008-01-23 修回日期:2008-03-26 出版日期:2009-02-25 发布日期:2009-02-25

Grid Resource Allocation Algorithm Based on Parallel Gene Expression Programming

DENG Song, WANG Ru-chuan, ZHANG Yu, ZHANG Jian-feng   

  1. School of Computer,Nanjing University of Posts and Telecommunications,Nanjing,Jiangsu 210003,China
  • Received:2008-01-23 Revised:2008-03-26 Online:2009-02-25 Published:2009-02-25

摘要: 网格下的资源分配属于NP-难问题.为了更好地解决这个问题,文中首先提出了网格资源分配模型,并对资源个数与任务个数的三种不同情况进行了详细的分析,最后提出基于并行基因表达式编程的网格资源分配算法(Grid Resource Allocation Algorithm based on Parallel GEP,GRA-PGEP).该算法采用了基于资源与任务相关的非线性的编码方式和反转操作,同时应用粗粒度模型设计了该算法.仿真实验表明,GRA-PGEP算法在优化成功率、平均收敛代数以及耗时方面都要优于传统的GEP和GA算法.

关键词: 基因表达式编程, 网格, 资源分配, 粗粒度模型

Abstract: Resource allocation of grid is part of optimization and NP-hard problem.In order to optimize resource allocation of grid,in the present research,it proposes a model of grid resource allocation,analyzes three different situations of the number of resources and tasks in detail,and then puts forward on a new algorithm which is called Grid Resource Allocation Algorithm based on Parallel GEP(GRA-PGEP).It adopts a nonlinear code based on resources and tasks and inversion operation,meanwhile,a coarse-grained model is applied to design the GRA-PGEP algorithm.By simulation experiment,it is showed that optimization successful rate,average convergent generation and consumptive time of GRA-PGEP have the advantage over traditional GEP and GA.

Key words: gene expression programming, grid, resource allocation, coarse-grained model

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