  Despite all the progress in Web service selection, the need for an approach
with a better optimality and performance still remains. This paper presents a
genetic algorithm by adopting the Pareto principle that is called GAP2WSS for
selecting a Web service for each task of a composite Web service from a pool of
candidate Web services. In contrast to the existing approaches, all global QoS
constraints, interservice constraints, and transactional constraints are
considered simultaneously. At first, all candidate Web services are scored and
ranked per each task using the proposed mechanism. Then, the top 20 percent of
the candidate Web services of each task are considered as the candidate Web
services of the corresponding task to reduce the problem search space. Finally,
the Web service selection problem is solved by focusing only on these 20
percent candidate Web services of each task using a genetic algorithm.
Empirical studies demonstrate this approach leads to a higher efficiency and
efficacy as compared with the case that all the candidate Web services are
considered in solving the problem.
