Web Service Composition based on Meta-heuristics

Progress of communication and information technology is reinforcing the role of the internet in business. Information sharing, customer support, and marketing support are a few areas where use of internet increasing day by day. Internet impact on business is now affecting economic, social, and technical changes around the world, which are transforming their approach to interact with customers. Web Services are an essential component that helps the business in this regard. But it is very complex to discover the best one from the vast web services pool. The proliferation of services that deliver similar functionalities is rising exponentially. With the advent of meta-heuristic computing, several models have been developed based living on the behavior of many living organisms. These models have been used either alone or in association with other algorithms to solve many optimization problems. Web Service selection is one such application where these models have been used. In this approach, a grey wolf algorithm is proposed to solve the problem of web service selection which has been formulated as a constraint-based selection task. Experimental result shows that the suggested approach provides an improved solution in execution time.