An efficient service recommendation using differential evolutionary contract net for migrating workflows

In a migrating workflow, agents transfer their code (specification) and their execution state to a site, negotiate services to be executed on their behalf, receive the results, and move on. The next place visited by agents, and the next service requested, is determined by both the goals of the workflow and the results of the current requests. However, the primary assumption in such workflow specifications is that the workflow designer has the ability of knowing the perfect knowledge of all the details of the process, and predicting changes of network configuration. In this paper, an efficient service recommendation strategy is suggested for migrating workflows. Services organization in our suggested strategy is based on the differential evolutionary contract net protocol. To evaluate the performance improvement achieved by our strategy, this paper uses F1 that is a well-known performance measure for recommender system. The results show that the new strategy can reduce the communication overhead and substantially improve performance in terms of global optimization and system utilization.