A Context-Aware Service Selection Approach Based on Historical Records

Abstract

Due to the unstable network environment and fake quality propagation, the published service quality by service providers is not always trustable. Therefore, it becomes a necessity to evaluate the real quality of a Web service, based on the service's historical records. However, for a Web service, its multiple historical records often vary in execution context (e.g., execution time, user input, user location, etc.), which brings a great challenge to discriminate and rank all the historical records of an identical Web service. Besides, for all the candidate Web services, their historical record number (i.e., the times that a service was invoked) may be different, which may also affect the user's final service selection decision. In view of these challenges, we put forward a novel service selection approach CSS_HR (Context-aware Service Selection based on Historical Records). In CSS_HR, we first quantify the weight of each historical record, based on its context similarity with current user's service invocation; and afterwards, we quantify the weight of each candidate Web service based on its historical record number; finally, with the derived weights of historical records and weights of candidate services, we evaluate all the candidate services and select a quality-optimal one. Through a set of experiments, we validate the feasibility of our proposal.