Ph. Leitner, J. Ferner, W. Hummer, S. Dustdar:
"Data-driven and automated prediction of service level agreement violations in service compositions";
Distributed and Parallel Databases, Volume 31 (2013), Issue 3; S. 447 - 470.

Kurzfassung englisch:
Service Level Agreements (SLAs), i.e., contractually binding agreements between service providers and clients, are gaining momentum as the main discriminating factor between service implementations. For providers, SLA compliance is of utmost importance, as violations typically lead to penalty payments or reduced customer satisfaction. In this paper, we discuss approaches to predict violations a priori. This allows operators to take timely remedial actions, and prevent SLA violations before they have occurred. We discuss data-driven, statistical approaches for both, instance-level prediction (SLA compliance prediction for an ongoing business process instance) and forecasting (compliance prediction for future instances). We present an integrated framework, and numerically evaluate our approach based on a case study from the manufacturing domain.

Service composition · Service level agreements · Quality prediction

"Offizielle" elektronische Version der Publikation (entsprechend ihrem Digital Object Identifier - DOI)

Zugeordnete Projekte:
Projektleitung Schahram Dustdar:
Erweiterte Diagnose und Testen für SOAs - Audit 4 SOAs

Projektleitung Schahram Dustdar:

Erstellt aus der Publikationsdatenbank der Technischen Universität Wien.