基于离散粒子群算法的动态Web服务组合  

Dynamic Web Service Composition Based on Discrete Particle Swarm Optimization

作　　者：张燕平[1,2] 荆紫慧 张以文[1,2] 钱付兰[1,2] 石磊[1] 

机构地区：[1]安徽大学计算机科学与技术学院,合肥230039 [2]安徽大学计算智能与信号处理教育部重点实验室,合肥230601

出　　处：《计算机科学》2015年第6期71-75,共5页Computer Science

基　　金：国家自然科学基金项目(61175046);安徽省自然科学基金项目(1408085MF132)资助

摘　　要：随着互联网中Web服务数量急剧增加,如何从大量候选服务中快速、动态地选择出满足用户QoS需求的服务组合是亟待解决的关键问题。提出一种基于离散粒子群智能优化算法的DDPSO算法,以解决动态Web服务组合问题。首先引入Skyline技术来剔除冗余候选服务,以降低服务选择时空开销。其次针对PSO易陷入早熟收敛状态,使用Trimming Operators保证粒子群多样性,增强全局搜索能力。最后通过真实数据集和随机数据集的大量仿真实验验证了本算法的可行性和有效性。With the increasing of Web services, how to choose service composition that meets user＇s QoS requirements from a large number of candidate services quickly and dynamically is the key issue. In order to solve this problem, a new DDPSO algorithm was proposed based on discrete particle swarm intelligence optimization. First, the cost of time and space was reduced by using the Skyline technology to eliminate redundant candidate services. Second, the diversity of particles was kept and the global search ability was of simulation experiments were carried on the actual ciency of the algorithms. increased by using the Trimming Operators. Finally,a large number and random data set, and the results validate the feasibility and efficiency of the algorithms.

关 键 词：服务组合 服务质量 离散PSO算法 早熟收敛处理 Skyline技术 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]