计算机技术与发展2017，Vol.27Issue(2)：178-181,186,5.DOI:10.3969/j.issn.1673-629X.2017.02.041
混沌蚁群算法的Web服务组合优化研究
Investigation on Optimization of Web Service Composition Employing Chaos Ant Colony Algorithm
摘要
Abstract
In order to satisfy the users' increasing demands on Quality of Experience (QoE) of services,Web service composition based on QoE is proposed.On the basis of Fuzzy Expert System,the mathematical model of QoE applied to Web service composition optimizing problem is put forward.Chaos Ant Colony Optimization (CACO) is used to solve Web service composition.According to the ergodicity,randomness and regularity of chaos,the algorithm adds to the chaos disturbance to avoid falling into local optimal solution and the global optimal solution will be found.Compared with the original Artificial Bee Colony (ABC),Particle Swarm Optimazation (PSO) and Ant Colony Optimization (ACO),the experimental results show that CACO has shorter operating time,faster convergence and high stability in Web service composition problem and has a better developmental prospect.关键词
Web服务组合/模糊专家系统/用户体验质量/混沌蚁群算法Key words
Web service composition/Fuzzy Expert System/QoE/CACO分类
信息技术与安全科学引用本文复制引用
承松,周井泉,常瑞云..混沌蚁群算法的Web服务组合优化研究[J].计算机技术与发展,2017,27(2):178-181,186,5.基金项目
国家自然科学基金资助项目(61401225) （61401225）
中国博士后科学基金资助项目(2015M571790) （2015M571790）
