Title: A graph-based automatic services composition based on cost estimation heuristic

Authors: Yunsu Lee; Boonserm Kulvatunyou; Minchul Lee; Yun Peng; Nenad Ivezic

Addresses: Systems Integration Division, National Institute of Standards and Technology, Gaithersburg, 20899, USA ' Systems Integration Division, National Institute of Standards and Technology, Gaithersburg, 20899, USA ' Systems Integration Division, National Institute of Standards and Technology, Gaithersburg, 20899, USA ' Computer Science and Electrical Engineering, University of Maryland, Baltimore County, Baltimore, 21250, USA ' Systems Integration Division, National Institute of Standards and Technology, Gaithersburg, 20899, USA

Abstract: Currently, both software and hardware are being virtualised and offered as services on the internet. Companies have an opportunity to improve their workflows by composing services that best suit their quality and cost requirements. However, as more services become available, computer-aided services discovery and composition become essential. Traditional service representation and planning algorithms do not adequately address non-functional characteristics, large numbers of similar operators (i.e., services), and limited numbers of objects (i.e., inputs and outputs per service). This paper analyses existing work in automatic services composition, service representation and planning algorithms and proposes a new framework to address those needs. It proves that the proposed framework provides an admissible heuristic based on cost estimations that guarantee a minimum cost solution, if one exists.

Keywords: automatic services composition; graph-based planning; service representation; function representation; AND/OR graph search algorithm; smart manufacturing; service integration.

DOI: 10.1504/IJSOI.2019.103406

International Journal of Services Operations and Informatics, 2019 Vol.10 No.2, pp.145 - 180

Received: 16 May 2019
Accepted: 28 Jun 2019

Published online: 30 Oct 2019 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article