Replicating web contents using a hybrid particle swarm optimization

作者:

Highlights:

摘要

We consider the problem of placing copies of objects in a distributed web server system to minimize the cost of serving read and write requests when the web servers have limited storage capacities. We formulate the problem as a 0–1 optimization problem and present a hybrid particle swarm optimization algorithm to solve it. The proposed hybrid algorithm makes use of the strong global search ability of particle swarm optimization (PSO) and the strong local search ability of tabu search to obtain high quality solutions. The effectiveness of the proposed algorithm is demonstrated by comparing it with the genetic algorithm (GA), simple PSO, tabu search, and random placement algorithm on a variety of test cases. The simulation results indicate that the proposed hybrid approach outperforms the GA, simple PSO, and tabu search.

论文关键词:Object replication,Web,Distributed web server system,Data placement,Internet

论文评审过程:Received 24 January 2008, Revised 22 December 2008, Accepted 24 June 2009, Available online 26 July 2009.

论文官网地址:https://doi.org/10.1016/j.ipm.2009.06.006