An Interpretation of Qos-Aware Web Service Composition Using Metaheuristics Method

Abstract

Web has become the most distributed, largest and well-accepted computing platform ever since web services existed while service composition giving ways to many more value-added services by aggregating the sets of new with the existing services. There are many candidate services with the same functionality but different quality of service (QoS) properties in satisfying the needs of requirements from the users. QoS-aware web service composition is concerned to select those candidates that best fit with the expected composition focusing on optimizing the overall QoS value of the composition. Current literature has emphasized that using bio-inspired metaheuristic methods such as Particle Swarm Optimization (PSO), Simulated Annealing (SA), Genetic Algorithms (GA), Ant Colony Optimization (ACO), Bee Algorithms (BA) and Firefly Algorithms (FA) is a promising approach in QoS-aware composition. The metaheuristic approach is very useful to the user with the diversification of the requirements that is intensified to be a near-optimal solution. Thus, this paper provides a crucial review of existing web service composition works that using the metaheuristics approach to overcome the needs and different kind of features. The reviews develop a classification of approaches based on QoS-aware web service composition using metaheuristics and discuss the future research directions.