Citation

Feng J, Liu Z, Wu C, Ji Y. IEEE Veh. Tech. Mag. 2019; 14(1): 28-36.

Copyright

(Copyright © 2019, Institute of Electrical and Electronics Engineers, Inc.)

DOI

10.1109/MVT.2018.2879647

PMID

unavailable

Abstract

As an enabling technology for the Internet of Vehicles (IoV), mobile edge computing (MEC) provides potential solutions for sharing the computation capabilities among vehicles, in addition to other accessible resources. In this article, we first introduce a distributed vehicular edge computing solution named the autonomous vehicular edge (AVE), which makes it possible to share neighboring vehicles' available resources via vehicle-tovehicle (V2V) communications. We then extend this concept to a more general online solution called the hybrid vehicular edge cloud (HVC), which enables the efficient sharing of all accessible computing resources, including roadside units (RSUs) and the cloud, by using multiaccess networks. We also demonstrate the impact of these two decentralized edge computing solutions on the task execution performance. Finally, we discuss several open problems and future research directions.

Language: en

Keywords

autonomous vehicular edge; Cellular networks; cloud computing; Cloud computing; distributed vehicular edge computing solution; Edge computing; hybrid vehicular edge cloud; intelligent transportation systems; Internet of Vehicles; job scheduling; mobile computing; mobile edge computing; multiaccess networks; offloading framework; Process control; Processor scheduling; resource allocation; resources sharing; roadside units; scheduling; Scheduling; vehicle-to-vehicle communications; Vehicular and wireless technologies