Reliable web service selection via QoS uncertainty computing

Abstract

Performance of web services may fluctuate owing to the dynamic internet environment, which makes the Quality–of–Service (QoS) of web services inherently uncertain. With the increase in web services in the internet, selecting the optimal service from a set of functionally equivalent candidates becomes an important research problem. In this paper, we propose an efficient and effective approach for reliable web service selection. Our approach first employs cloud model to compute the QoS uncertainty for pruning redundant services while extracting reliable services. Then, based on QoS uncertainty computing, Mixed Integer Programming (MIP) is used to select optimal services. We evaluate our approach experimentally on real–world web services as well as randomly generated QoS values. The experimental results show that our approach can provide reliable and efficient service selection for users.