A novel dynamic checkpoint selection strategy for time-constrained massive cloud business workflows

Rongbin Xu, Yeguo Wang, Ying Xie, Li Li, Dong Yuan

Abstract: The utilization of cloud computing resources contributes to a fast growth of e-business and e-government where businesses and government agencies often require processing a large volume of service requests in a constrained period of time. In order to achieve on-time completion of a large volume of time-constrained parallel processes, this paper proposes a novel dynamic checkpoint selection strategy (CSS DM ) for monitoring cloud business workflows. CSS DM monitors the execution time points rather than activities along the business workflows. The paper also provides some parameters that can track the execution process of each virtual machine. This mechanism significantly increases the efficiency in monitoring large volume processes so as to improve the quality of service in both e-business and e-government sectors. Simulation results show that CSS DM has excellent performance in different scenarios even when certain amounts of noises are added.