A clustering network-based approach to service composition in cloud manufacturing

Abstract

Cloud manufacturing (CMfg) is a new business paradigm that aims to provide manufacturing resources as services over the Internet in a convenient pay-as-you-go mode. Service composition is a critical means for achieving value adding and synergy of resources in CMfg. There are a vast number of services in a CMfg platform, which makes traditional service composition methods incapable and low efficiency in solving the problem of service composition. Most of existing research on CMfg was devoted to the optimal selection of services under a specific composition flow and a group of given candidate pools. Hence, there is a need to explore effective approaches to obtaining service composition flow and candidate sets. The network-based web service composition approach has recently drawn much attention and has been proved effective in coping with the challenge of large-scale services. Inspired by this, a novel approach called service clustering network-based service composition is proposed in this paper. In this method, services are first clustered into abstract services, and then a clustering network of the abstract services is established. In this way, service composition paths and corresponding candidate sets for fulfilling manufacturing tasks can be quickly obtained without requiring task decomposition, which decreases the difficulty and improves efficiency of service composition. Effectiveness and efficiency of the approach are verified through simulation experiments.