Nowadays, most business processes are running in a parallel, distributed and time-constrained manner. How to guarantee their on-time completion is a challenging issue. In the past few years, temporal checkpoint selection which selects a subset of workflow activities for verification of temporal consistency has been proved to be very successful in monitoring single, complex and large size scientific workflows. An intuitive approach is to apply those strategies to individual business processes. However, in such a case, the total number of checkpoints will be enormous, namely the cost for system monitoring and exception handling could be excessive. To address such an issue, we propose a brand new idea which selects time points along the workflow execution time line as checkpoints to monitor a batch of parallel business processes simultaneously instead of individually. Based on such an idea, a set of new definitions as well as a time-point based checkpoint selection strategy are presented in this paper. Our preliminary results demonstrate that it can achieve an order of magnitude reduction in the number of checkpoints while maintaining satisfactory on-time completion rates compared with the state-of-the-art activity-point based checkpoint selection strategy.
Funding
Management of Large-Scale Models
Directorate for Computer & Information Science & Engineering