Conference Proceedings
History-Aware, Real-Time Risk Detection in Business Processes
Raffaele Conforti, Giancarlo Fortino, Marcello La Rosa, Arthur HM ter Hofstede, R Meersman (ed.), T Dillon (ed.), P Herrero (ed.), A Kumar (ed.), M Reichert (ed.), L Qing (ed.), BC Ooi (ed.), E Damiani (ed.), DC Schmidt (ed.), J White (ed.), M Hauswirth (ed.), P Hitzler (ed.), M Mohania (ed.)
ON THE MOVE TO MEANINGFUL INTERNET SYSTEMS: OTM 2011, PT I | SPRINGER-VERLAG BERLIN | Published : 2011
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 resu..
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Awarded by National Science andTechnology
Awarded by National Basic Research Program
Awarded by National High-Tech Development Program
Awarded by NSF
Funding Acknowledgements
Thework is supported by the National Science andTechnology Major Project (HGJ) of China (No.2010ZX01042-002-002-01), the National Basic Research Program (973 Plan) of China (No. 2009CB320700), the National High-Tech Development Program (863 Plan) of China (No. 2008AA042301) and an NSF Project of China (No. 61003099)