摘要
针对当前Web服务海量增加,而现有的Web服务选择算法低效、缓慢的问题,提出了一种基于云计算的粒子群优化算法的Web服务选择方法。该方法在云平台下对粒子分群映射、相似分群并行化简、适时更新分群,并且寻找与用户需求最相似、服务质量最好的策略。实验表明,该方法能有效减少流程执行过程中Web服务选择导致的时间开销,并提高Web服务选择的可靠性。
Aiming at the problem that the massive increase of the current Web services and the inefficiency and slowness of the existing Web services selection algorithm,this paper proposed a Web service selection based on particle swarm optimization algorithm under cloud computing.The method mapped the particle in cluster on the cloud platform,and parallel simplified the similar cluster,and updated the cluster timely,and looked for the strategy which was most similar to user needs and of best quality in service.The experiments show that this method can effectively reduce the time overhead of Web service selection process execution,and improve the reliability of the Web services selection.
出处
《计算机应用研究》
CSCD
北大核心
2013年第4期1069-1071,1075,共4页
Application Research of Computers
基金
江西省教育厅科技项目(GJJ12345
GJJ12349)
关键词
WEB服务
粒子群优化算法
云计算
服务选择
Web services
particle swarm optimization（PSO） algorithm
cloud computing
service selection
