An Approach to Web Service Selection Based on Composite Qos Parameters

Abstract

Quality of service (QoS) is an important attribute for selecting a service during the service composition process. Although availability and reliability have been considered as the predominant factors for estimating reputation, two aspects are missing in the literature. First, their use is limited to composite service level and does not count on the atomic level. Second, their combined effect is not evaluated. Better estimation of QoS can be done with both factors considered together, whereas when taken separately for computing reputation, availability will give the probability of a service being up/running and reliability will analyze the change in failure trend of that service. In this research, a mathematical modeling of predominant QoS factors, availability and reliability of atomic services using Markov Chain model and Weibull analysis respectively, are suggested. Also importance of modeling reputation as an aggregation of availability and reliability has been explained. This research concludes two results. First, counting on probability of a service being up/running and its failure trend, together, results in a better estimation of its behavior and helps selecting the most appropriate one. Second, this resulted in selection of a service with higher reputation but lower usage cost, as opposed to using a single factor that resulted in higher reputation with higher cost.

SOADIWA: A Service-oriented Architecture for Data Interoperability in Web Applications

“…An enhanced composition model based on web services was also proposed by [30]. A mathematical modelling of predominant QoS factors, availability and reliability of atomic services using Markov chain model and Weibull analysis respectively was also presented in [31] and based on test result, the combined effect of availability and reliability enhanced better estimation of QoS. A location-aware web service recommender system which helps users to select services with optimal QoS performance was proposed by [32], the web service QoS data set promoted future research and make experimental study reproducible.…”