基于组合服务执行信息的服务选取方法研究

组合服务选取问题是服务计算领域的一个研究热点问题,已往的选取方法大多基于难以准确获取的服务QoS信息,且算法思路复杂.文中提出了一种基于组合服务执行信息的服务选取方法.该方法分为3个阶段:数据生成阶段、数据挖掘阶段和服务选取阶段,分别进行组合服务执行信息的记载和相关数据集的生成、路径分支关联规则和服务执行顺序序列模式的挖掘以及基于挖掘产生的知识模式进行服务选取.文中首先给出一种可以方便记载日志的服务组合系统架构;然后提出一种基于时间加权的算法模型,以有效地进行路径分支关联规则和顺序序列模式的挖掘;最后对文中的组合服务选取方法进行描述.实验结果表明:文中方法在选取出的组合服务健壮性方面要优于基于QoS的方法.

Research on Service Selection Approach Based on Composite Service Execution Information

Composite service selection has received increasing attention by the research community in the past few years. Most selection approaches are based on service QoS information which is difficult to acquire accurately, and the corresponding algorithms are complex. In this paper, a composite service execution information based service selection approach is proposed. This approach includes three steps: (1) data producing step: recording the execution information of composite services into a log repository, and extracting related datasets; (2) data mining step: discovering path fork association rules and service execution sequential sequence patterns by data mining; (3) service selecting step: selecting proper services based on the discovered knowledge. In this paper, a composite service system architecture which can record the log easily is presented firstly. Then, a time weighted algorithm mode is proposed to discover the path fork association rules and the service execution sequential sequence patterns. At last, the service selection approach based on composite service execution information is described. Experimental results show that the new selection approach is better than the QoS based approaches on the robustness of the selected composite services.