Publications in Scientific Journals:

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; 447 - 470.

English abstract:
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

"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)

Related Projects:
Project Head Schahram Dustdar:
Erweiterte Diagnose und Testen für SOAs - Audit 4 SOAs

Project Head Schahram Dustdar:

Created from the Publication Database of the Vienna University of Technology.