Journal
ACM TRANSACTIONS ON AUTONOMOUS AND ADAPTIVE SYSTEMS
Volume 13, Issue 1, Pages -Publisher
ASSOC COMPUTING MACHINERY
DOI: 10.1145/3105748
Keywords
Self-adaptive systems; model predictive control; awareness requirements
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Funding
- ERC advanced grant Lucretius: Foundations for Software Evolution [267856]
- Swedish Foundation for Strategic Research under the project Future Factories in the Cloud (FiC) [GMT14-0032]
- FAPES [0969/2015]
- CNPq [485368/2013-7, 461777/2014-2]
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Self-adaptive software systems monitor their operation and adapt when their requirements fail due to unexpected phenomena in their environment. This article examines the case where the environment changes dynamically over time and the chosen adaptation has to take into account such changes. In control theory, this type of adaptation is known as Model Predictive Control and comes with a well-developed theory and myriad successful applications. The article focuses on modeling the dynamic relationship between requirements and possible adaptations. It then proposes a controller that exploits this relationship to optimize the satisfaction of requirements relative to a cost function. This is accomplished through a model-based framework for designing self-adaptive software systems that can guarantee a certain level of requirements satisfaction over time by dynamically composing adaptation strategies when necessary. The proposed framework is illustrated and evaluated through two simulated systems, namely, the Meeting-Scheduling exemplar and an E-Shop.
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