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A Personalized Trust-Based Approach for Service Selection in Internetwares

机译:基于个性化信任的Internetware服务选择方法

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Internetware is an abstract of the distributed software system in the open and dynamic Internet which is generally integrated by large numbers of autonomous and heterogeneous software services of various functions. The reliability of the service which acts as a component in Internetware inevitably has an effect on the collaboration in the system and users' satisfaction on the whole system. So picking the right service from the open environment is a critical problem for developers to build high confidence application systems. However, traditional test measures cannot work when facing with dynamically evolutive characters and separated interests between developers of systems and third-party services in the Internetware. Trust and reputation mechanism is a complementary approach which relies on analyzing collected recommendations from past users to evaluate the software. In this paper, we propose a personalized trust-based approach to do service selection automatically for users. It mainly deals with two problems: 1) trustworthiness: as lacking of a global monitor to record runtime performances of services, we design a recommendation collection method based on the user's social network; 2) relevance: since the formation of ratings has an impact on the recommendation, we establish a filtering process to weight information according to recommenders' expectation and capability.
机译:Internetware是开放和动态Internet中分布式软件系统的抽象,通常由大量具有各种功能的自治和异构软件服务集成。充当Internetware组件的服务的可靠性不可避免地会影响系统中的协作以及用户对整个系统的满意度。因此,从开放环境中选择合适的服务是开发人员构建高可信度应用程序系统的关键问题。但是,当面对动态演变的特征以及Internetware中的系统开发人员和第三方服务之间的利益分离时,传统的测试方法无法工作。信任和信誉机制是一种补充方法,它依赖于分析过去用户收集的推荐来评估软件。在本文中,我们提出了一种基于个性化信任的方法来自动为用户选择服务。它主要处理两个问题:1)可信度:由于缺少用于记录服务运行时性能的全局监视器,因此我们设计了一种基于用户社交网络的推荐收集方法; 2。 2)相关性:由于评级的形成会对推荐产生影响,因此我们根据推荐者的期望和能力建立对信息加权的过滤过程。

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