一种考虑QoS数据可信性的服务选择方法

Service Selection Approach Considering the Trustworthiness of QoS Data

随着Internet上功能相似的Web服务的逐渐增多,在运行时刻基于服务质量(QoS)对Web服务进行查找和选择已成为研究热点.现有的基于QoS的服务选择方法通常假定服务提供者和使用者给出的QoS数据都是真实可信的,然而这一假设在实际中往往很难保证.为此,提出了一种考虑QoS数据可信性的服务选择方法.方法从QoS数据来源的角度对质量属性进行分类和计算:对于数据来自服务提供者的质量属性,使用以往运行数据统计,对提供者的QoS数据进行修正;对于数据来自服务使用者的质量属性,通过计算用户间以往反馈的相似程度权衡不同QoS反馈数据的可信程度.对此给出了实现框架,并通过一组模拟实验说明该方法能够有效地削弱不可信的QoS数据对服务选择的影响,增强了Web服务选择结果的准确性.

As the number of web services with the similar function is increasing, QoS-based service selection at runtime has become an important research topic. The existing QoS-based services selection approaches always assume that the QoS data coming from service providers and users are effective and trustworthy, which is actually impossible in reality. This paper proposes a service selection approach considering the trustworthiness of QoS data, which classifies and computes the QoS attributes according to the source of QoS data. For the QoS attributes whose data come from service providers, the statistics of past runtime data to revise the providers＇ QoS data are used. For the QoS attributes whose data come from users, feedback similarity to weigh users＇ QoS data is used. Furthermore, an implementation framework and a set of experiments are given, which show that this approach can effectively weaken the influence of untrustworthy QoS data on the services selection, thus can strengthen the accuracy of the service selection.