Optimizing Virtual Machine Migration in Multi-Clouds

Cloud computing is susceptible to failures. Allocating Virtual machine (VM) in a reliable fashion is considered as one of the crucial problems in Cloud computing environment. Most researchers choose the optimal VM allocation based on resource utilization and cost minimization. However, to protect the reputation of cloud providers, service reliability should be addressed appropriately. In this paper, we propose a Markov-based failure prediction model to anticipate the failure of Cloud servers. Our model anticipates a deteriorating server state based on historical data. Server reliability prediction is then integrated into a VM re-allocation approach in a Multi-Cloud setting to optimize fault tolerance by maximizing Cloud reliability while reducing communication delay. The optimization problem is solved optimally and heuristically using the Artificial Bee Colony (ABC) algorithm. The results show that our model enhances reliability and minimizes communication delay between the VMs following service migration.