Title: Petri nets-based method to model and analyse the self-healing web service composition

Authors: Liqiong Chen; Guisheng Fan; Huanhuan Zhang; Lizhong Xiao

Addresses: Department of Computer Science and Information Engineering, Shanghai Institute of Technology, Shanghai, China; Shanghai Key Laboratory of Computer Software Evaluating and Testing, Shanghai, China ' Department of Computer Science and Engineering, East China University of Science and Technology, Shanghai, China ' Department of Computer Science and Engineering, East China University of Science and Technology, Shanghai, China ' Department of Computer Science and Information Engineering, Shanghai Institute of Technology, Shanghai, China

Abstract: Service composition is an important means for integrating the individual web services to create new value added systems that can satisfy complex requirements. Such applications are subject to unexpected failure owing to the distributive and heterogeneous environment of web service. In this paper, we propose a Petri nets-based method to model and analyse the self-healing service composition. Aspect oriented programming is used to extract composition processes and self-healing strategy as the core and crosscutting concerns. A self-healing strategy of component and service composition is proposed, and the related operations of self-healing are abstracted as meta-objects by using reflection mechanism. Petri nets are used to construct the base layer model, meta layer model, meta-object protocol and other components, thus forming the self-healing model. The operational semantics and related theories of Petri nets help prove its effectiveness and correctness. A simulation example shows that our approach correctly describes the self-healing process of service composition, and contributes to improving the quality.

Keywords: self-healing; web services; web service composition; aspect orientation; Petri nets; reflection; modelling; semantics; simulation.

DOI: 10.1504/IJHPCN.2016.074654

International Journal of High Performance Computing and Networking, 2016 Vol.9 No.1/2, pp.8 - 18

Received: 23 Sep 2014
Accepted: 28 Oct 2014
Published online: 12 Feb 2016 *

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