1 research outputs found
A Novel Model for Distributed Big Data Service Composition using Stratified 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 approach to
compose services 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 from atomic
services of different composite services when binary matching is not possible
or desired. In this paper, we propose a new model for service composition based
on "stratified graph summarization" and "service stitching". We discuss the
limitations of existing approaches with a motivating example, present our
approach to overcome these limitations, and outline a possible architecture for
service composition from atomic services. Our thesis is that, with the advent
of Big Data, our approach will reduce latency in service discovery, and will
improve efficiency and accuracy of matchmaking and composition of services.Comment: 15 page