History-aware, real-time risk detection in business processes

Authors:
Raffaele Conforti;Giancarlo Fortino;Marcello La Rosa;Arthur H. M. Ter Hofstede
Affiliations:
Queensland University of Technology, Australia;Università della Calabria, Italy;Queensland University of Technology, Australia;Queensland University of Technology, Australia and Eindhoven University of Technology, The Netherlands
Venue:
OTM'11 Proceedings of the 2011th Confederated international conference on On the move to meaningful internet systems - Volume Part I
Year:
2011

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Abstract

This paper proposes a novel approach for identifying risks in executable business processes and detecting them at run-time. The approach considers risks in all phases of the business process management lifecycle, and is realized via a distributed, sensor-based architecture. At design-time, sensors are defined to specify risk conditions which when fulfilled, are a likely indicator of faults to occur. Both historical and current process execution data can be used to compose such conditions. At run-time, each sensor independently notifies a sensor manager when a risk is detected. In turn, the sensor manager interacts with the monitoring component of a process automation suite to prompt the results to the user who may take remedial actions. The proposed architecture has been implemented in the YAWL system and its performance has been evaluated in practice.