Grid Resource Allocation Algorithm Based on Parallel Gene Expression Programming

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

您当前的位置：

首页 >

文章列表页 >

Grid Resource Allocation Algorithm Based on Parallel Gene Expression Programming

更新时间：2025-07-16

- Grid Resource Allocation Algorithm Based on Parallel Gene Expression Programming
- Acta Electronica Sinica Vol. 37, Issue 2, Pages: 272-277(2009)
- 作者机构：
  
  南京邮电大学计算机学院,江苏,南京,210003
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP301
- Published：2009
- 稿件说明：
移动端阅览
DENG Song, WANG Ru-chuan, ZHANG Yu, et al. Grid Resource Allocation Algorithm Based on Parallel Gene Expression Programming[J]. Acta Electronica Sinica, 2009, 37(2): 272-277.
DOI：

DENG Song, WANG Ru-chuan, ZHANG Yu, et al. Grid Resource Allocation Algorithm Based on Parallel Gene Expression Programming[J]. Acta Electronica Sinica, 2009, 37(2): 272-277. DOI：

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.

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.

关键词

Keywords

references

Views

1200

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Grid Resource Allocation Based on the Combinatorial Double Auction

Joint Optimization of Distributed Intelligent Content Caching and User Association for CF-mMIMO

Robust Resource Allocation Algorithm for Secure Communication in LEO-Based Satellite Communication Systems

Random User Characteristics-Oriented Joint UAV Deployment and Resource Allocation Algorithm

A Learning-Inspired Resource Allocation for Energy Harvesting-Powered Cognitive M2M Communications

Related Author

LI Li

LIU Yuan-an

MA Xiao-lei

LI Yun

ZHANG Cheng-yu

YAO Zhi-xiu

XIA Shi-chao

TAN Zhen

Related Institution

Key Laboratory of Universal Wireless Communications,Ministry of Education,Beijing University of Posts and Telecommunications

School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications

School of Computer and Technology, Chongqing University of Posts and Telecommunications

No.15 Institute of China Electronics Technology Group Corporation

Aerospace New Generation Communications Co., Ltd.

⁰