网络的大规模、异构、动态、分布和自治性造成了资源和服务的不确定性和欺骗性,从而导致服务交易双方风险增大,因此构建有效的信任模型是降低交易双方风险的重要途径.针对当前基于模糊理论的信任模型和基于反馈信息的信任评估方法存在的缺陷,提出了一种基于集对分析理论中联系数概念的主观信任表示方法,以克服模糊数学中用一个精确、唯一的隶属函数严格表示模糊概念的缺点,同时,在此模型中不是单纯基于用户的反馈信息来评价服务的信任度,而是结合服务资源在服务过程达到的服务能力来增加模型的客观性、实时性.将新的信任函数并入到传统的组件服务选择算法中,提出了两种基于信任的服务选择算法,并进行了实验仿真.结果表明,基于信任驱动的服务选择算法的任务执行成功率较传统方法有明显的提高.%The large-scale.heterogeneous.dynamic, distributed and autonomous network results in uncertainty and deceptive of resources and services,so an effective trust mechanism should be built to ensure transaction safety. But current trust evaluation approaches solely based on fuzzy logic and feedback are inaccurate and ineffective. This paper presented a method which is based on set pair analysis theory to overcome the shortcoming that a fuzzy concept must be denoted by a precise,only strict membership function in fuzzy math. This model considers not only the feedback information, but also the service capacity that resources can achieve. The authors proposed two algorithms of service selection based on the trust model. Simulations prove that the algorithms can efficiently increase the success rate of task executioa
展开▼
