摘要
大数据环境下随着用户需求越来越复杂,单个Web服务的不确定性增加,导致服务组合的难度增加.提出一种基于混合遗传聚类的可靠Web服务组合优化模型.该模型首先通过混沌映射产生初始组合服务集,并借助置信度表对服务集进行一次筛选,以提高组合可靠性.在此基础上利用遗传算法优化服务集,并以二次聚类为基础建立服务组合优化模型,最终收敛于全局最优解.实验结果表明,与传统优化方法相比,所提模型在提高可靠性的同时改善了组合优化度.
With the increasing complexity of users'requirements and the increasing uncertainty of individual web services in large data environment,service composition becomes more and more difficult.A reliable web service composition optimization model based on hybrid genetic clustering is proposed.Firstly,the model generates the initial composite service set by chaotic mapping,and then filters the service set with the help of confidence table to improve the reliability of the combination.On this basis,the genetic algorithm is used to optimize the service set,the service composition optimization model is established based on quadratic clustering,and finally converges to the global optimal solution.The experimental results show that compared with traditional optimization methods,the proposed model improves both reliability index and combinatorial optimization degree.
作者
张苑蕾
邵清
李刘静
鲁建斌
张程斌
ZHANG Yuan-lei;SHAO Qing;LI Liu-jing;LU Jian-bin;ZHANG Cheng-bin(School of Optoelectronic Information and Computer Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China)
出处
《小型微型计算机系统》
CSCD
北大核心
2020年第5期1030-1035,共6页
Journal of Chinese Computer Systems
基金
国家自然科学基金项目(61703278)资助
上海市科委科研计划项目(17511107203)资助.
关键词
WEB服务组合
遗传算法
二次聚类
可靠性
Web service composition
genetic algorithms
quadratic clustering
reliability
