Towards a Novel Model for Distributed Big Data Service Composition Using Functional Graph Matching

A significant number of current industrial applications rely on web services. A cornerstone task in these applications is discovering a suitable service that meets the threshold of some user needs. Then, those services can be composed to perform specific functionalities. We argue that the prevailing approaches to service composition based on the "all or nothing" paradigm is limiting and leads to exceedingly high rejection of potentially suitable services. Furthermore, contemporary models do not allow "mix and match" composition of atomic services into composite services when binary matching is not possible or desired. In this paper, we introduce a new approach for service composition based on "stratified graph summarization" and "service stitching that help remove these limitations as a work in progress.