Abstract

Service selection based on non-functional properties (NFP) of services is one of the most important and challenging task in service-oriented computing. NFP are usually described in service-level agreements (SLA). Therefore, the problem of comparison of SLAs arises naturally if there is more than one service with the same desired functionality. SLAs are usually written in a special XML-based format (WS-Agreement, WSLA, RBSLA, etc.). They describe some rules of using the service at the proper level, set the metrics by which that service is measured, and the remedies or penalties in case the agreed-upon levels are not achieved. The paper proposes a method to find differences between SLAs using rule-based knowledge representation and first-order logic-based derivation.

Recommended Citation

Paliulionienė, L. (2014). A Rule-Based Method for Comparison of SLAs in Service-Oriented Computing. In V. Strahonja, N. Vrček., D. Plantak Vukovac, C. Barry, M. Lang, H. Linger, & C. Schneider (Eds.), Information Systems Development: Transforming Organisations and Society through Information Systems (ISD2014 Proceedings). Varaždin, Croatia: Faculty of Organization and Informatics. ISBN: 978-953-6071-43-2. http://aisel.aisnet.org/isd2014/proceedings/WebBasedSystems/2.

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A Rule-Based Method for Comparison of SLAs in Service-Oriented Computing

Service selection based on non-functional properties (NFP) of services is one of the most important and challenging task in service-oriented computing. NFP are usually described in service-level agreements (SLA). Therefore, the problem of comparison of SLAs arises naturally if there is more than one service with the same desired functionality. SLAs are usually written in a special XML-based format (WS-Agreement, WSLA, RBSLA, etc.). They describe some rules of using the service at the proper level, set the metrics by which that service is measured, and the remedies or penalties in case the agreed-upon levels are not achieved. The paper proposes a method to find differences between SLAs using rule-based knowledge representation and first-order logic-based derivation.