Sliding-window based propagation-aware temporal verification for monitoring parallel cloud business workflows

On-time completion is one of critical QoS (Quality of Service) measurements for massive time-constrained business processes executing in the cloud environment. However, temporal violations inevitably occur during the execution of business workflows due to the uncertainty and dynamic nature of cloud environment. To realize the goal of the target on-time completion rate, workflow temporal verification is employed for monitoring the execution time of workflow activities and handling time delays before the deadline. While current studies on business cloud workflows temporal verification mainly monitor the execution of workflows with fixed observation time intervals along the system timeline, which can result in huge monitoring cost. To reduce the monitoring cost, this paper presents a sliding-window based dynamic temporal checkpoint selection strategy using propagation-aware throughput temporal consistency model for parallel cloud business workflows. The strategy adjusts the next observation time interval according to the temporal verification result at the previous checkpoint. Experimental results show that our strategy can select fewer temporal checkpoints and violation handling points compared with conventional strategies under the same situations.