基于QoS真实性与工作流模型的Web服务选择

Web service selection approach based on the authenticity of QoS data and workflow model

基于服务质量的Web服务选择方法往往假定服务提供者与使用者提供的质量数据均为真实可靠,而这一假设在实际中很难保证.为此,提出一种同时基于服务质量数据真实性与工作流模型的服务选择方法.对服务提供者发布的质量数据,根据服务运行数据的统计结果重新计算其客观质量值;对来自服务使用者的主观评价,通过工作流组织模型计算使用者间的信任度,并结合信任度计算当前用户的服务评价值.通过服务质量模型的建立,结合两种数据选出最优Web服务.实验证明该方法能够有效改善不可靠的质量数据对Web服务选择造成的影响,使服务选择结果更加准确.

The existing QoS（quality of service）-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.A service selection approach based on the authenticity of QoS data and workflow model was proposed to solve the problem.For the QoS data coming from service providers,the statistics of past runtime data to revise the providers＇ QoS data were used.For the subjective evaluation coming from users,the confidence values of users were calculated based on the workflow-organization-model,and then the evaluation was computed by using the confidence.At last,the optimal web services could be selected by combing the two values as the judgment standard.The experimental results show that this approach can effectively weaken the influence of untrustworthy QoS data on Web service selection and strengthen the accuracy of service selection.