Self-Healing
by
Benedikt Liegener
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last modified
Apr 27, 2012 10:21
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filed under:
KnowledgeModel
Definitions
Term: Self-Healing |
Domain: Cross-cutting issues | ||||
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Engineering and Design (KM-ED) |
Adaptation and Monitoring (KM-AM) |
Quality Definition, Negotiation and
Assurance (KM-QA) |
Generic (domain independent) |
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D o m a i n : L a y e r s |
Business Process Management (KM-BPM) |
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Service Composition and
Coordination (KM-SC) |
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Service Infrastructure (KM-SI) |
Self-Healing is called the ability of a computing component to detect, diagnose and repair localized problems resulting from bugs or failures in software and hardware.[CD-IA-1.1.1][AutonomicVision] | ||||
Generic (domain independent) |
Self-Healing is the ability of a system or a SBA to repair itself without any external intervention.[CD-IA-1.1.1] A system is self-healing if is able to recover from a failed component by first detecting and isolating the failed component, and repair or replace the compoent without affecting the application. {SPC:Self-Healing system} |
A self-healing enhanced system uses both, adaptation and monitoring techniques provided by the system and integrates them into the loop (c.f., MAPE-K loop [AutonomicVision]) | Self-healing, which is linked to self-diagnosing or
self-repairing, is the capability of discovering, diagnosing, and reacting to disruptions. It can also
anticipate potential problems, and accordingly take proper actions to
prevent a failure.
Self-diagnosing refers to diagnosing errors, faults, and failures, while self-repairing focuses on
recovery from them [M. Salehie & Tahvildari, 2009]. Self-healing system should recover from the abnormal (or “unhealthy”) state and return to the normative (“healthy”) state, and function as it was prior to disruption [D. Ghosh et al, 2007]. |
Competencies
- UniDue: Engineering Adaptive Service-based Systems; http://www.sse.uni-due.de/wms/en/?go=325;
Klaus Pohl, Andreas Metzger, Andreas Gehlert
- POLIMI: Adaptive Web Services; http://home.dei.polimi.it/pernici/ws-research.html; Barbara Pernici, Maria Grazia Fugini, Danilo Ardagna, Pierluigi Plebani, Cinzia Cappiello, Marco Comuzzi
- POLIMI: Dependable Evolvable Pervasive SE; http://deepse.dei.polimi.it/; Carlo Ghezzi, Elisabetta Di Nitto, Luciano Baresi, Valentina Mazza
- SZTAKI: SLA based resource virtualization approach for on demand service provision ; http://www.lpds.sztaki.hu ; Gabor Kecskemeti, Attilla Kertesz
Scenarios
- Wine Scenario: A sensor belonging to the WSN used to observe the vineyard parameters could have faulty behavior. The system could be able to identify the faulty sensor and enact suitable actions.
References
- [CD-IA-1.1.1], Deliverable CD-IA-1.1.1 Comprehensive overview of the state of the art on service-based systems
- [AutonomicVision] J.O.Kephart, D.M. Chess: The vision of autonomic computing, IEEE Computer N 36 pp 41-50, 2003
- [M. Salehie & Tahvildari, 2009] M. Salehie and L. Tahvildari: Self-Adaptive Software: Landscape and Research Challenges, ACM Transactions on Autonomous and Adaptive Systems, Vol. 4, No. 2, Article 14, 2009.
- [D. Ghosh et al, 2007] Debanjan Ghosh, Raj Sharman, H. Raghav Rao, Shambhu Upadhyaya: Self-healing systems — survey and synthesis, Decision Support Systems 42 (2007) 2164–2185
- [PO-JRA-2.3.1] Use case description and state of the art