一种基于划分的组合服务选取方法

组合服务选取问题是服务计算领域研究的核心问题.由于组合服务中基本服务QoS间存在着复杂的关联关系,使得某些服务一起使用时效率会较高,而某些服务一起使用时效率反而会降低,现有的服务选取算法几乎忽略了该问题,从而使得选取时所使用的Web服务QoS数据往往不准确,致使选取出的组合服务在实际执行时并不是最优的.为了解决该问题,提出了一种基于划分的组合服务选取方法.首先基于日志记载的质量信息选取那些性能优良的组合服务执行实例,在此之上发现被频繁一起使用的具体服务集合,据此产生对组合服务的划分,形成组合服务点和对应的点模式;最后把点模式集作为点的备选服务集,以点为单位进行组合服务选取.由于点模式经过了多遍执行的验证,和直接对点中各基本服务进行独立选取相比其性能往往会更高.实验表明,该方法能有效提高选取出的组合服务质量.

A Division Based Composite Service Selection Approach

Composite service selection is one of the core research issues in the service computing field.There are complex correlations among atomic service QoS in a composite service,making some atomic services become more efficient and some become less efficient if they are used together.Previous service selection algorithms almost ignored this problem,which makes the Web service QoS used to service selection be inaccurate and the selected composite service be not the optimal one in the real executing environment.To address this problem,a division based composite service selection approach is proposed in this paper.Firstly,the set of efficient composite service execution instances are extracted from the log repository.Then the concrete service sets which are frequently used together are mined.On this basis,the composite service is divided into some dots,and the corresponding dot patterns of each dot are generated.Finally,composite service selection can be done taking the divided composite service dots as selection units,and the dot patterns of each dot as its candidate service set.Because dot patterns are testified by many execution instances and represent selection experience,they are usually more efficient compared with the results of doing selection independently for each service in one dot.Experimental results show that the proposed approach can improve the quality of selected composite services effectively.