An evolutionary model for dynamic and adaptative service composition in distributed environment

Abstract

Service composition is an important mean for integrating the individual Web services to create new value-added systems that satisfy complex requirements. Therefore, how to effectively analyze different types of services and find out the matching similarity between services to efficiently substitute failed services in a distributed and dynamic environment becomes crucial to service composition. In this paper, we propose a novel approach based on a data cell evolution model (DCEM) to support the dynamic adaptation of service compositions. The model combines data service information and biological cell behavior analysis to encapsulate data services into data cells. In order to reach optimum adaptations, we analyzed the static and dynamic structure of data cells based on bigraph theory to guarantee the consistency of service evolution. To evaluate the proposed approach, a series of simulation experiments and comparisons are conducted to demonstrate the effectiveness of service composition.