A New Approach for VM Failure Prediction using Stochastic Model in Cloud
Ajay Rawat, Rama Sushil, Amit Agarwal, Afzal Sikander · IETE Journal of Research · 2018
In the present study, a new approach is suggested for the prediction of virtual machine (VM) failure based on the time series stochastic model. Motivated by various proactive fault tolerance techniques in the cloud, prediction of VM failure is highly anticipated. However, precise prediction of VM failure is extremely challenging and having a substantial impact on the proactive fault tolerance system. In proactive fault management techniques, it is essential to forecast the VM failure in the cloud and to characterize the system behavior. To predict the VM failure, we need to monitor the execution of VMs in the clouds dynamic environment and gather their health-related information. Therefore, in this paper, VM failure prediction is presented through a failure predictor module which is designed using time series based autoregressive integrated moving average. The suggested approach is tested on non-stationary failure trace of VM. It is observed that the proposed approach provides the failure prediction accurately.