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A systematic survey on the design of self-adaptive software systems using control engineering approaches
List of Titles
A systematic survey on the design of self-adaptive software systems using control engineering approaches
Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.3/221474
- Title
- A systematic survey on the design of self-adaptive software systems using control engineering approaches
- Author(s)
- Patikirikorala, Tharindu; Colman, Alan; Han, Jun; Wang, Liuping
- Abstract
- Control engineering approaches have been identified as a promising tool to integrate self-adaptive capabilities into software systems. Introduction of the feedback loop and controller into the management system potentially enables the software systems to achieve the runtime performance objectives and maintain the integrity of the system when they arc operating in unpredictable and dynamic environments. There is a large body of literature that has proposed control engineering solutions for different application domains, handling different performance variables and control objectives. However, the relevant literature is scattered over different conference proceedings, journals and research communities. Consequently, conducting a survey to analyze and classify the existing literature is a useful, yet a challenging task. This paper presents the results of a systematic survey that includes classification and analysis of 161 papers in the existing literature. In order to capture the characteristics of the control solutions proposed in these papers we introduce a taxonomy as a basis for classification of all articles. Finally, survey results are presented, including quantitative, cross and trend analysis.
- Publication type
- Conference paper
- Research centre
- Swinburne University of Technology
- Source
- Proceedings of the 7th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2012), Zurich, Switzerland, 04-05 June 2012, pp. 33-42
- Publication year
- 2012
- Keyword(s)
- Adaptation models; Control engineering; Data mining; Software systems; Systematics; Taxonomy
- Publisher
- IEEE
- ISBN
- 9781467317870
- Publisher URL
- http://dx.doi.org/10.1109/SEAMS.2012.6224389
- Copyright
- Copyright © 2012 IEEE.
- Peer reviewed
