QoS-aware peer services selection using ant colony optimisation
Web services coordinated by computational peers can be aggregated to create composite workflows that provide streamlined functionality for human users or other systems. One of the most critical challenges introduced by Peer-to-Peer (P2P) based Web services is represented by Quality of Service (QoS)-driven services composition. Since many available Peers provide overlapping or identical functionalities, though with different QoS, selections need to be quickly made to determine which peers are suitable to participate in an expected composite service. The main contribution of this paper is a heuristic approach which effectively and adaptively finds appropriate service peers for a service workflow composition, and also some uncertainties in the real ad-hoc scenarios are considered by a proper re-planning scheme. We propose to adopt Ant Colony Optimisation (ACO) to tackle the QoS-aware Peers’ composition problem in both static and dynamic situations, as ACO represents a more scalable choice, and is suitable to handle and balance generic QoS attributes by pheromones. The proposed approach is able to improve the selection performances in various service composition structures, and also can adaptively handle unexpected events. We present experimental results to illustrate the efficiency and feasibility of the proposed method.