Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/142454
Title: Modeling self-adaptive software systems by fuzzy rules and Petri nets
Authors: Ding, Zuohua
Zhou, Yuan
Zhou, Mengchu
Keywords: Engineering::Computer science and engineering
Issue Date: 2017
Source: Ding, Z., Zhou, Y., & Zhou, M. (2018). Modeling self-adaptive software systems by fuzzy rules and Petri nets. IEEE Transactions on Fuzzy Systems, 26(2), 967-984. doi:10.1109/TFUZZ.2017.2700286
Journal: IEEE Transactions on Fuzzy Systems
Abstract: A self-adaptive software system is one that can autonomously modify its behavior at runtime in response to changes in the system and its environment. It is a challenge to model such a kind of systems since it is hard to predict runtime environmental changes at the design phase. In this paper, a formal model called intelligent Petri net (I-PN) is proposed to model a self-adaptive software system. I-PN is formed by incorporating fuzzy rules to a regular Petri net. The proposed net has the following advantages. 1) Since fuzzy rules can express the behavior of a system in an interpretable way and their variables can be reconfigured by the runtime data, the proposed model can model runtime environment and system behavior. 2) Since a fuzzy inference system with well-defined semantics can be used in a complementary way with other model languages for the analysis, thus the proposed model can be analyzed, even though it is described in two different languages: component behaviors in Petri nets while logic control in fuzzy rules. 3) The proposed model has self-adaption ability and can make adaptive decisions at runtime with the help of fuzzy inference reasoning. We adopt a manufacturing system to show the feasibility of the proposed model.
URI: https://hdl.handle.net/10356/142454
ISSN: 1063-6706
DOI: 10.1109/TFUZZ.2017.2700286
Rights: © 2017 IEEE. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Journal Articles

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