QoS-Aware Services composition using Tabu Search and Hybrid Genetic Algorithms

In a distributed services oriented environment, having a myriad of functionally equivalent services, Quality of Service(QoS) emerges as the key differential factor. In this scenario organizations can dynamically select partners for their core business processes expressed as Composite Web Services (CWS). As a consequence, QoS-aware composition should drive an effective selection by optimizing different factors and meeting constraints according to preferences of organizations. QoS-aware composition can be formulated as a NP-hard optimization problem. In order to deal with this hard problem, different heuristic techniques (such as genetic algorithms with different solution encodings or simulated annealing) had been proposed in the literature. In this paper we apply metaheuristic optimization techniques to this problem, specifically tabu search and an hybrid genetic algorithm. We compare these techniques with other proposals using experimental results, showing that our proposals provide improvements.