Multi-Objective Service Composition with QoS Dependencies

Service composition is popular for composing a set of existing services to provide complex services. With the increasing number of services deployed in cloud computing environments, many service providers have started to offer candidate services with equivalent functionality but different Quality of Service (QoS) levels. Therefore, QoS-aware service composition has drawn extensive attention. Most existing approaches for QoS-aware service composition assume a service’s QoS values are not correlated to those of other services. However, QoS dependency exists in real life, and impacts the overall QoS values of the composite services. In this article, we study QoS dependency-aware service composition considering multiple QoS attributes. Based on the Pareto set model, we focus on searching for a set of Pareto optimal solutions. A candidate pruning algorithm for removing the unpromising candidates is proposed, and a service composition algorithm using Vector Ordinal Optimization techniques is designed. Simulation experiments are conducted to validate the efficiency and effectiveness of our algorithms. We are the first to take advantage of Vector Ordinal Optimization techniques to search for Pareto optimal composition solutions with QoS dependency involved. The capturing of QoS dependency enables us to find truly desirable solutions. Keywords—service composition; QoS dependency; Pareto optimal solutions; Vector Ordinal Optimization; multiple QoS attributes; multi-objective optimization; candidate pruning