|Table of Contents|

Load Balance for Large E-Commerce Server Cluster Based on ImprovedCultural Particle Swarm Optimization Algorithm(PDF)

南京师范大学学报（工程技术版）[ISSN:1006-6977/CN:61-1281/TN]

Issue:
2014年03期
Page:
79-
Research Field:
Publishing date:

Info

Title:
Load Balance for Large E-Commerce Server Cluster Based on ImprovedCultural Particle Swarm Optimization Algorithm
Author(s):
Chen Hongming; Zhang Hui
College of Computer Engineering,Huaiyin Institute of Technology,Huai’an 223003,China
Keywords:
E-commerce; server cluster; load balancing; cultural algorithm; particle swarm algorithm
PACS:
TP39
DOI:
-
Abstract:
In order to solve problems of particle swarm optimization algorithm in solving the load balancing for large E-commerce server cluster,this paper proposes a large E-commerce load balance method based on improved cultural particle swarm optimization algorithm.Firstly,a main population space of particle swarm algorithm and spatial knowledge of cultural algorithm form the "dual evolution and dual promotion" mechanism to improve global search capability and efficiency; and the evolutionary mechanism of genetic algorithm is introduced to improve the knowledge space and avoid self limiting of culture algorithm,and finally,the algorithm is applied to the solution of load balancing problem for large E-commerce server cluster.The simulation results show that the proposed algorithm has improved resource utilization rate of large E-commerce server cluster system and that the load is more balanced.

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Last Update: 2014-09-30