Mobile Edge Computing for the Internet of Vehicles: Offloading Framework and Job Scheduling

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.

[1]  Giovanni Pau,et al.  Pics-on-wheels: Photo surveillance in the vehicular cloud , 2013, 2013 International Conference on Computing, Networking and Communications (ICNC).

[2]  Thomas Engel,et al.  Luxembourg SUMO Traffic (LuST) Scenario: 24 hours of mobility for vehicular networking research , 2015, 2015 IEEE Vehicular Networking Conference (VNC).

[3]  Yusheng Ji,et al.  Resource Allocation for SVC Streaming Over Cooperative Vehicular Networks , 2018, IEEE Transactions on Vehicular Technology.

[4]  Yu Huang,et al.  User-driven cloud transportation system for smart driving , 2012, 4th IEEE International Conference on Cloud Computing Technology and Science Proceedings.

[5]  Aiqing Zhang,et al.  Security, Privacy, and Fairness in Fog-Based Vehicular Crowdsensing , 2017, IEEE Communications Magazine.

[6]  Yusheng Ji,et al.  Power Control in D2D-Based Vehicular Communication Networks , 2015, IEEE Transactions on Vehicular Technology.

[7]  Yusheng Ji,et al.  AVE: Autonomous Vehicular Edge Computing Framework with ACO-Based Scheduling , 2017, IEEE Transactions on Vehicular Technology.

[8]  Yusheng Ji,et al.  Cooperative Content Delivery in Vehicular Networks with Integration of Sub-6 GHz and mmWave , 2017, 2017 IEEE Globecom Workshops (GC Wkshps).

[9]  Xuemin Shen,et al.  Connected Vehicles: Solutions and Challenges , 2014, IEEE Internet of Things Journal.

[10]  Tarik Taleb,et al.  Mobile Edge Computing Potential in Making Cities Smarter , 2017, IEEE Communications Magazine.

[11]  Yusheng Ji,et al.  2016 Energy-Efficient Resource Allocation for Multi-User Mobile Edge Computing , 2016 .

[12]  Luca Maria Gambardella,et al.  Ant colony system: a cooperative learning approach to the traveling salesman problem , 1997, IEEE Trans. Evol. Comput..

[13]  Rong Yu,et al.  Distributed Reputation Management for Secure and Efficient Vehicular Edge Computing and Networks , 2017, IEEE Access.

[14]  Hiroshi Harada,et al.  A radio-on-fiber based millimeter-wave road-vehicle communication system by a code division multiplexing radio transmission scheme , 2001, IEEE Trans. Intell. Transp. Syst..

[15]  Yusheng Ji,et al.  HVC: A Hybrid Cloud Computing Framework in Vehicular Environments , 2017, 2017 5th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud).