利用服务聚类优化面向过程模型的语义Web服务发现

如何快速、准确和高效地发现满足用户需求的Web服务是现阶段急需解决的关键问题之一.文中针对现有的Web服务发现机制中存在的效率低下和查准率不高的两个问题,提出了一个新的语义Web服务发现框架.在该框架下,采用Petri网作为Web服务过程描述的形式化工具.首先,利用聚类技术,从服务的功能相似和过程相似两个层面对服务进行聚类预处理,从而在很大程度上降低服务的查找空间,提高服务的查找效率.进一步,针对服务请求中可能潜在的行为约束,建立基于Petri网的过程需求模型,将其与候选服务的过程模型进行比较,对满足功能需求的可行服务进一步筛选,从而提高查找的精确度.最后,利用仿真实验对所提出的方法进行验证.

Using Service Clustering to Facilitate Process-Oriented Semantic Web Service Discovery

The discovery of suitable Web services for a given user requirement is one of the central operations in Service-oriented Architectures. With the popularization of Web services, researches on minimizing the discovery duration and improving precision ration are getting more important. This paper proposes a mechanism to support semantic Web service discovery. Petri net is adopted as a modeling language for the specification of service process model. On the one hand, the methodology of service clustering groups similar services according to the functional similarity and process similarity. The utilization of service clustering can potentially enable service matchmaker to significantly reduce the overhead, deploy the discovery of candidate services quickly. On the other hand, for a service request, a service matchmaker compares the functionality compatibility and process consistency with the candidate services. It is an extension of previous functionality-driving service matchmaking approaches, thus leading to more accurate matchmaking. In the end, some simulation results are demonstrated to show the effectiveness of the proposed method.