A Personalized Trust-Based Approach for Service Selection in Internetwares

Pan Jing, Xu Feng, Xin Xianlong, Lu Jian
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引用次数: 5

Abstract

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.
基于个性化信任的互联网服务选择方法
Internet软件是在开放的、动态的Internet上对分布式软件系统的抽象,它一般是由大量具有各种功能的自治的、异构的软件服务集成而成的。服务作为互联网中的一个组成部分,其可靠性必然影响到整个系统的协同性和用户对整个系统的满意度。因此,从开放环境中选择正确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。然而,面对互联网中系统开发者与第三方服务之间的动态演化特征和利益分离,传统的测试手段已经无法发挥其作用。信任和声誉机制是一种互补的方法,它依赖于分析收集到的过去用户的推荐来评估软件。在本文中,我们提出了一种基于个性化信任的方法来为用户自动进行服务选择。主要解决两个问题:1)可信度:由于缺乏对服务运行时性能的全局监控,我们设计了一种基于用户社交网络的推荐收集方法;2)相关性:由于评分的形成对推荐有影响,我们建立了一个过滤过程,根据推荐人的期望和能力对信息进行加权。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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