On Boosting Cloud Service Dependability through Optimized Checkpointing

Abstract

Virtual machines (VMs) are used in cloud computing systems to handle user requests for service. Failure of VMs cause that the user's request not being completed. Replication mechanisms can be used to mitigate the impact of VM failures. In this paper, we are primarily interested in characterizing the failure-recovery behavior of a VM in cloud with different replication schemes. We use a service-oriented dependability metric called Defects Per Million (DPM) defined as the number of user requests dropped out of a million, due to VM failures. We present an analytical modeling approach for computing the DPM metric in different replication schemes on the basis of structure-state process and checkpointing method. The effectiveness of replication schemes are demonstrated through experimental results. To verify the validity of the proposed analytical models, we extend the widely used cloud simulator CloudSim and compare the simulation results with analytical solutions.