| 1. |
- Gerostathopoulos, Ilias, et al.
(författare)
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Architectural Homeostasis in Self-Adaptive Software-Intensive Cyber-Physical Systems
- 2016
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Ingår i: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). - Cham : Springer International Publishing. - 1611-3349 .- 0302-9743. - 9783319489919 ; 9839 LNCS, s. 113-128
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Konferensbidrag (refereegranskat)abstract
- Self-adaptive software-intensive cyber-physical systems (sasiCPS) en-counter a high level of run-time uncertainty. State-of-the-art architecture-based self-adaptation approaches assume designing against a fixed set of situations that warrant self-adaptation; as a result, failures may appear when sasiCPS operate in environment conditions they are not specifically designed for. In response, we propose to increase the homeostasis of sasiCPS, i.e., the capacity to maintain an operational state despite run-time uncertainty, by introducing run-time changes to the architecture-based self-adaptation strategies according to environment stimuli. In addition to articulating the main idea of architectural homeostasis, we describe three mechanisms that reify the idea: (i) collaborative sensing, (ii) faulty component isolation from adaptation, and (iii) enhancing mode switching. More-over, our experimental evaluation of the three mechanisms confirms that allowing a complex system to change its self-adaptation strategies helps the system recover from runtime errors and abnormalities and keep it in an operational state.
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| 2. |
- Gerostathopoulos, Ilias, et al.
(författare)
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Tuning self-adaptation in cyber-physical systems through architectural homeostasis
- 2019
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Ingår i: Journal of Systems and Software. - : Elsevier BV. - 0164-1212. ; 148, s. 37-55
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Tidskriftsartikel (refereegranskat)abstract
- Self-adaptive software-intensive cyber-physical systems (sasiCPS) encounter a high level of run-time uncertainty. State-of-the-art architecture-based self-adaptation approaches assume designing against a fixed set of situations that warrant self-adaptation. As a result, failures may appear when sasiCPS operate in environment conditions they are not specifically designed for. In response, we propose to increase the homeostasis of sasiCPS, i.e., the capacity to maintain an operational state despite run-time uncertainty, by introducing run-time changes to the architecture-based self-adaptation strategies according to environment stimuli. In addition to articulating the main idea of architectural homeostasis, we introduce four mechanisms that reify the idea: (i) collaborative sensing, (ii) faulty component isolation from adaptation, (iii) enhancing mode switching, and (iv) adjusting guards in mode switching. Moreover, our experimental evaluation of the four mechanisms in two different case studies confirms that allowing a complex system to change its self-adaptation strategies helps the system recover from run-time errors and abnormalities and keep it in an operational state.
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