An approach to optimize mashup based on QoS-Skyline and transactional properties

Mashup aims to glue together existing services into entirely new applications. With the growing number of alternative services in the open service environment, users have put forwards new demands that bind the runtime of services, which requires as much short computation time as possible. This paper addresses the issue of service mashup not only according to functional requirements but also to QoS characteristics and transactional properties. We propose a mashup optimization method based on QoS-Skyline and transactional properties. This method first adopts skyline approaches to improve the efficiency of selection by using the dominance relationship of skyline to prune services, then employs adaptive particle swarm optimization to select service from amount of candidates. The experimental results show that the mashup optimization method based on QoS-Skyline and transactional properties is feasible and effective.