DCEM: A data cell evolution model for service composition based on bigraph theory

Abstract

Service composition is an important means of integrating individual web services to create new value-added systems that satisfy complex requirements. Effectively analyzing different types of services and identifying the matching similarity between services is a crucial component of service composition, as it allows failed services to be efficiently substituted in a distributed and dynamic environment. In this paper, we propose a data cell evolution model (DCEM) that supports the dynamic adaptation of service compositions. DCEM combines data service information and biological cell behavior analysis to encapsulate data services into data cells. To optimize the adaptations, we analyze 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.