A Self-Adaptive Recovery Net (SARN) is an extended Petri net model for specifying exceptional behavior in workow systems. SARN caters for high-level recovery policies that are incorporated either with a single task or a set of tasks, called a recovery region. A recovery region delimits the part of the workow from which the associated recovery policies take place. In this paper, we assume that SARN is initially partitioned into recovery regions by workow designers who have a priori expectations for how exceptions will be handled. We propose a pattern-based approach to dynamically restructure SARN partition. The objective is to continuously restructure recovery regions within SARN partition to reect the dynamic changes in handling exceptions. The restructuring of SARN partition is based on the observation of prede_ned recovery patterns.
|Cite as: Hamadi, R. and Benatallah, B. (2005). Dynamic Restructuring of Recovery Nets. In Proc. Sixteenth Australasian Database Conference (ADC2005), Newcastle, Australia. CRPIT, 39. Williams, H. E. and Dobbie, G., Eds. ACS. 37-46. |
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