【作者】 童红霞；

【导师】 张申生；

【作者基本信息】 上海交通大学 ， 计算机应用技术， 2009， 博士

【摘要】 由于单个Web服务的功能有限,有必要将多个Web服务组合起来,提供更为强大的功能。Web服务组合已经成为服务计算的核心问题之一。虽然Web服务组合的研究已经取得了一定的进展,但是现有Web服务组合方法大多采用集中式处理机制,存在着单点故障和性能瓶颈问题。随着网络上可用的Web服务资源以及Web服务用户的增多,分布式Web服务组合成为了迫切的需求。本文结合Agent技术,从服务Agent模型,分布式服务组合算法、复合服务质量优化方法和服务Agent自优化机制等方面提出了基于服务Agent的Web服务组合技术。本文主要研究工作和创新点如下:(1)提出了一种服务Agent模型服务Agent模型是Web服务与Agent相融合的结果。每一个服务Agent管理着某一领域一组功能相关的Web服务集,从而能自适应地向用户提供服务。服务Agent模型具有两个方面的优点,一是服务Agent模型使用操作模板来抽象一组具有相似功能的Web服务操作的典型特征,从而屏蔽了分布式Web服务的异构性;二是服务Agent模型使用规划来描述使用操作模板完成某一业务目标的过程,从而使得普通的用户只需要关注他们所需要完成的目标,而不需要关注如何完成他们的目标。(2)提出了基于服务Agent的分布式服务组合算法在服务Agent模型的基础上,提出了基于分布式规划的服务组合算法。该算法根据服务Agent间的依赖关系将Web服务组合问题形式化为图的搜索问题,并提出了一个基于最小覆盖的搜索策略。基于服务Agent的分布式服务组合算法有两个方面的优点,一是它建立在服务Agent的分布式决策之上,从而具有良好的可扩展性;二是基于服务Agent的分布式服务组合算法具有较好的性能,它能以较小的通讯代价获得高质量的解。(3)提出了基于多目标遗传算法的复合服务质量优化方法复合服务质量优化方法建立在扩展的Web服务质量模型之上。扩展的Web服务质量模型考虑了Web服务非功能性属性的多个侧面与多种表示形式,从而具有很强的描述能力。为了满足用户多样性的服务质量需求,本文将复合服务质量优化问题形式化为带约束的多目标优化问题并提出了基于多目标遗传算法的复合服务质量优化方法,它能有效的处理Web服务质量描述和用户服务质量需求中存在的模糊性。模拟实验表明,基于遗传算法的复合服务质量优化方法能够快速有效的得到全局近似最优解。(4)基于模糊多属性群决策的服务Agent自优化机制针对Web服务性能指标描述中存在的模糊性,提出了一种基于模糊多属性群决策的服务Agent自优化算法。该算法通过运用模糊运算和群决策选择函数来综合多个决策者对Web服务性能的评价,从而为逐步提高服务Agent的性能提供了依据。本文围绕以上四个方面进行了深入的探讨,并通过原型系统验证了本文提出的理论和算法的有效性和可行性。更多还原

【Abstract】 Since the function of a single Web service is limited, it is necessary to compose multiple Web services to provide powerful function. Web service composition has been identified as one of the core problems of service oriented computing. The research of Web service composition has made progress in recent years. However, most of the Web service composition approaches are centralized, which suffers from single point of failure and performance bottlenecks. With the increase of available Web services on the Internet and the Web service requesters, distributed Web service composition is inevitable.This paper studies the agent-based Web service composition technology from the aspects including service agent model, distributed Web service composition algorithm, quality optimization of the composite Web service and self-optimization mechanism for service agent. The contributions that we have made in the paper are highlighted as follows:(1) Service agent modelThe service agent model is the integration result of Web service and agent. Each service agent manages a group of related Web services and adaptively provides services for the user. The service agent model uses the operation template to abstract the features of Web service operations with similar functions, which shields the heterogeneities of distributed Web services. Meanwhile, the service agent model uses the plan to specify the process of how to use operation templates to achieve a certain business goal. Therefore, the common users only need to focus on what they want to achieve rather than how to achieve.(2) Distributed Web service composition algorithm based on service agentBased on the service agent model, a distributed Web service composition algorithm is proposed, which formalizes the Web service composition as graph search problem according to the dependence relations among service agents and the minimal cover based search strategy is proposed. The proposed distributed Web service algorithm based on the service agent model has two distinguished features. Firstly, the distributed Web service composition algorithm is based on the distributed decision making of the autonomous service agents, which has better scalability. Secondly, the proposed distributed Web service composition algorithm is effective for its ability to produce the high quality solution at a low cost of communications.(3) An optimization approach for the composite Web service based on the multi-objective genetic algorithmThe optimization algorithm for the composite Web service is based on the extended quality model for Web service. The extended quality model takes account of various aspects and multi representation forms of non-functional attributes of web service, which has strong description ability. In order to satisfy the multifarious quality requirement, the quality optimization of the composite Web service is formalized as the problem of multi-objective optimization with constraints and an approach of multi-objective genetic algorithm is proposed. The proposed multi-objective genetic algorithm for the optimization of the composite Web service can effectively address the fuzziness existing in the Web service quality description and quality requirement. Simulation experiments demonstrate that the proposed multi-objective genetic algorithm can quickly obtain the approximate global optimal solution.(4) The self-optimization mechanism for service agent based on the fuzzy multi-attribute group decision makingA fuzzy multi-attribute group decision making algorithm for service agent self-optimization is proposed for the fuzzy description of the Web service performance. The proposed algorithm uses the fuzzy operations and social choice function to synthesize the service performance evaluation of several decision makers, which supports the improvement of service agent performance step by step.The above four aspects are are investigated deeply in this paper. Finally, a prototype system is implemented, which demonstrates the effectiveness and feasibility of the theory and algorithms proposed in this paper.更多还原