Full Solution Indexing Using Database for QoS-Aware Web Service Composition

Abstract

Automated service composition can fulfill user request by composing services automatically when no individual services meet the goal. Unfortunately, most of current automated service composition methods are in-memory methods, which are limited by expensive and volatile physical memory. In this work, we develop a relational-database approach for automatic service composition. Possible service combinations are stored in a relational database on persistence disk instead of volatile memory, and for any composition requests, solutions can be obtained by simple SQL queries. We offer three main contributions in this paper. First, pursuing earlier work, we overcome the disadvantages of in-memory composition algorithms, such as volatile and expensive, and provide a solution suitable to cloud environments. Second, compared with other pre-computing composition methods, we use a single SQL query: there is no need to eliminate spurious services iteratively. Third, we address the quality of services to maximize user's satisfaction in our system. An experimental validation is done, which shows the performance benefits of our system and proves that this system can find a valid composition solution with fewer services to maximize user satisfaction.