ReputationNet: A Reputation Engine to Enhance ServiceMap by Recommending Trusted Services

Abstract

The concept of Service Oriented Architecture (SOA) enables flexible and dynamic collaborations among different service providers. Backed up by SOA, scientific workflows can bring together various scientific computing tools and resources all offered as services to answer complex research questions. However, studies conducted on my Experiment show that although the sharing of service-based capabilities opens a gateway to resource reuse, in practice, the degree of reuse is very low. This motivates us to propose ServiceMap to provide navigation support through the network of services in building scientific workflows. In this paper, we propose an extension of ServiceMap, i.e., ReputationNet that incorporates the reputation of services/workflows and their publishers to reinforce its capability in terms of service and workflow recommendations. We develop a novel model of the reputation aspects of the services/workflows, and we propose heuristic algorithms to provide service recommendations based on reputations. Experiments have been conducted with workflows on my Experiment to evaluate the effectiveness and validity of the ReputationNet approach for service recommendations.