Memetic algorithm for web service selection

Abstract

Due to the changing nature of service-oriented environments, the ability to locate services of interest in such open, dynamic, and distributed environments has become an essential requirement. Current service-oriented architecture standards mainly rely on functional properties, however, service registries lack mechanisms for managing services' non-functional properties. Such non-functional properties are expressed in terms of quality of service (QoS) attributes. QoS for web services allows consumers to have confidence in the use of services by aiming to experience good service performance in terms of waiting time, reliability, and availability. This paper investigates the service selection process, and proposes two approaches; one that is based on a genetic algorithm, and the other is based on a memetic algorithm to match consumers with services based on QoS attributes as closely as possible. Both approaches are compared with an optimal assignment algorithm called the Munkres algorithm, as well as a Random approach. Measurements are performed to quantify the overall match score, the execution time, and the scalability of all approaches.