Multi-objective distributed Web service composition—A link-dominance driven evolutionary approach

Abstract

Service-oriented architecture (SOA) encourages the creation of modular applications involving Web services as the reusable components. Data-intensive Web services manipulate and deal with the massive data that emerged by technological advances and their various applications. Distributed Data-intensive Web Service Composition (DWSC) includes the selection of data-intensive Web services from diverse locations on the network and composing them into a service to accomplish a complex task. Optimising Quality of Service (QoS) while satisfying the functional requirements is a fundamental challenge for service developers. The multi-objective and distributed nature of the DWSC problem demands satisfying algorithms to automatically produce the Pareto optimal set of composite services. In this paper, we propose a new Evolutionary Computation (EC) approach based on the Non-dominated Sorting Genetic Algorithm (NSGA-II) and a novel local search technique to effectively solve the multi-objective distributed DWSC problems. Our local search technique employs an innovative concept, communication link dominance, to incorporate domain-specific knowledge. The performance of our proposed link-dominance driven EC approach is evaluated on benchmark datasets. The results show that our proposed method has the highest quality with acceptable execution time for most of the composition tasks among competing algorithms.