Supervised Web Service Composition Integrating Multi-objective QoS Optimization and Service Quantity Minimization

The QoS of web service has been increasingly crucial due to the escalating number of services with similar or identical functionality, which leads to intensive researches on QoS-aware web service composition. Correspondingly, to optimize not only QoS but also service quantity in a composition has also been increasingly challenging. Currently, there are already many researches on service composition addressing the optimization of multiple QoS attributes, but it is still rare to take service quantity as an optimization objective as well. To address this issue, this paper proposes a novel supervised web service composition mechanism integrating multi-objective QoS optimization and the minimization of service quantity. Firstly a memory-based search algorithm is proposed to compute each single-objective optimal QoS, after which a knapsack-variant algorithm is applied to minimize the number of services without considering the QoS. Finally, a supervised multi-objective optimization is performed based on the above single-objective optimization results. Experimental results on both Web Service Challenge 2009’s datasets and substantial datasets randomly generated show that the proposed service composition method outperforms the state-of-the-arts by achieving a much better tradeoff among all the objectives.