Proactive Mitigation of the Revocation Risk for Preemptible Virtualized Resources

The provision of resources at the Cloud follows two generic models. The first model guarantees the provided resources for the requested time while the second involves unreliable resources with lower price compared to the former scheme but with no guarantees concerning an unexpected revocation due to a high demand. In this paper, we focus on the latter model and propose a scheme that monitors the course of execution of tasks placed at unreliable resources and decides when to store their current progress avoid jeopardizing intermediate outcomes in unexpected revocations. We rely on the principles of Optimal Stopping Theory (OST) to manage multiple tasks and decide for which task and when we have to save its current status. The outcome is a novel checkpointing mechanism fully aligned with the needs of the dynamics of an unreliable environment. The proposed model builds upon the heterogeneity of the available services in the Cloud and concludes a proactive mitigation approach of the revocation risk for unreliable virtualized resources. We present the theoretical basis of our mechanism and describe the solution of the identified problem. The pros and cons of our approach are evaluated through extensive simulations and a set of performance metrics.