Vehicle Ad-Hoc Networks VANET enable all components in intelligent transportation systems to be connected so as to improve transport safety, relieve traffic congestion, reduce air pollution, and enhance driving comfort. The vision of all vehicles connected poses a significant challenge to the collection, storage, and analysis of big traffic-related data. Vehicular cloud computing, which incorporates cloud computing into vehicular networks, emerges as a promising solution. Different from conventional cloud computing platform, the vehicle mobility poses new challenges to the allocation and management of cloud resources in roadside cloudlet. In this paper, we study a virtual machine VM migration problem in roadside cloudlet-based vehicular network and unfold that 1 whether a VM shall be migrated or not along with the vehicle moving and 2 where a VM shall be migrated, in order to minimize the overall network cost for both VM migration and normal data traffic. We first treat the problem as a static off-line VM placement problem and formulate it into a mixed-integer quadratic programming problem. A heuristic algorithm with polynomial time is then proposed to tackle the complexity of solving mixed-integer quadratic programming. Extensive simulation results show that it produces near-optimal performance and outperforms other related algorithms significantly. Copyright © 2015 John Wiley & Sons, Ltd.
['Hong Yao', 'Changmin Bai', 'Deze Zeng', 'Qingzhong Liang', 'Yuanyuan Fan']
Migrate or not? Exploring virtual machine migration in roadside cloudlet-based vehicular cloud