Virtual machine migration and management for vehicular clouds

Vehicular Cloud Computing is a growing research field which consolidates the benefit of cloud computing into vehicular ad hoc networks. However, few studies address vehicles as potential Virtual Machine hosts. Due to the rapidly changing environment of a vehicular cloud, a host can easily change or leave coverage. As such, Virtual Machine Management and Migration schemes are necessary to ensure cloud subscribers have a satisfactory level of access to the resources. This paper proposes several Vehicular Virtual Machine Migration (VVMM) schemes: VVMM-U (Uniform), VVMM-LW (Least Workload), VVMM-MA (Mobility Aware) and MDWLAM (Mobility and Destination Workload Aware Migration). Their performance is evaluated with respect to a set of metrics through simulations with varying levels of vehicular traffic congestion, Virtual Machine sizes and levels of load restriction. The most advanced scheme (MDWLAM), takes into account, the workload and mobility of the original host as well as those of the potential destinations. By doing so a valid destination will both have time to receive the workload and migrate the new load when necessary. The behavior of various algorithms is compared and the MDWLAM has been shown to demonstrate best performance, exhibiting migration drop rates that are negligibly small.