A Knowledge-based Approach for Self-healing Service-oriented Applications
Angarita Arocha, Rafaël; Rukoz, Marta; Manouvrier, Maude; Cardinale, Yudith (2016), A Knowledge-based Approach for Self-healing Service-oriented Applications, in Chbeir, Richard; Agrawal, Rajeev; Biskri, Ismail, MEDES 16 - Proceedings of the 8th International Conference on Management of Digital EcoSystems, ACM Press : New York, p. 1-8. 10.1145/3012071.3012100
Type
Communication / ConférenceDate
2016Conference title
8th International Conference on Management of Digital EcoSystems (MEDES 16)Conference date
2016-11Conference city
BiarritzConference country
FranceBook title
MEDES 16 - Proceedings of the 8th International Conference on Management of Digital EcoSystemsBook author
Chbeir, Richard; Agrawal, Rajeev; Biskri, IsmailPublisher
ACM Press
Published in
New York
ISBN
978-1-4503-4267-4
Number of pages
236Pages
1-8
Publication identifier
Metadata
Show full item recordAuthor(s)
Angarita Arocha, RafaëlLaboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Rukoz, Marta
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Manouvrier, Maude

Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Cardinale, Yudith

Universidad Simon Bolivar [USB]
Abstract (EN)
In the context of service-oriented applications, the self-healing property provides reliable execution in order to support failures and assist automatic recovery techniques. This paper presents a knowledge-based approach for self-healing Composite Service (CS) applications. A CS is an application composed by a set of services interacting each other and invoked on the Web. Our approach is supported by Service Agents, which are in charge of the CS fault-tolerance execution control, making decisions about the selection of recovery and proactive strategies. Service Agents decisions are based on the information they have about the whole application, about themselves, and about what it is expected and what it is really happening at run-time. Hence, application knowledge for decision making comprises off-line precomputed global and local information, user QoS preferences, and propagated actual run-time information. Our approach is evaluated experimentally using a case study.Subjects / Keywords
Service Agents; Rules; Composite service executionRelated items
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