Title: Fuzzy control-based manufacturing service composition in graph database

Authors: Ming Zhu; Guodong Fan; Aikui Tian; Lu Zhang

Addresses: College of Computer Science and Technology, Shandong University of Technology, Zibo, China ' College of Intelligence and Computing, Tianjin University, Tianjin, China ' College of Computer Science and Technology, Shandong University of Technology, Zibo, China ' Weichai Holding Group Co., Ltd., Weifang, China

Abstract: In recent years, the manufacturing industry is changing its way of production enabled by emerging technologies. Enterprises publish visualised resources as services on the cloud. To fulfil a complex manufacturing request, services can be composed together. However, how to compose proper services among a large number of services becomes a challenge. This paper presents a service composition graph model to deal with the challenge by using a graph database. Specifically, the service composition graph model is stored in the Neo4j graph database. Services and their inputs/outputs are stored as nodes in a directed bipartite graph that are connected with edges. The weights of edges are synthesised via a fuzzy control system according to the QoS of services. Possible compositions of services are calculated and pre-composed. When the manufacturing task arrives, an extended Dijkstra algorithm is used to find a solution. Experimental results show that the approach could return a solution satisfying both functional and QoS requirements within a short time.

Keywords: manufacturing service; service composition; quality of service; QoS; fuzzy control; graph database.

DOI: 10.1504/IJWET.2021.119878

International Journal of Web Engineering and Technology, 2021 Vol.16 No.3, pp.255 - 278

Received: 04 Nov 2020
Accepted: 07 Sep 2021
Published online: 22 Dec 2021 *

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