Research Article
Relay-Assisted Task Offloading Optimization for MEC-Enabled Internet of Vehicles
@INPROCEEDINGS{10.1007/978-3-030-94763-7_12, author={Heli Zhang and Haonan Zhang and Xun Shao and Yusheng Ji}, title={Relay-Assisted Task Offloading Optimization for MEC-Enabled Internet of Vehicles}, proceedings={Mobile Networks and Management. 11th EAI International Conference, MONAMI 2021, Virtual Event, October 27-29, 2021, Proceedings}, proceedings_a={MONAMI}, year={2022}, month={1}, keywords={Vehicular network MEC Predictive offloading Multihop relay}, doi={10.1007/978-3-030-94763-7_12} }- Heli Zhang
Haonan Zhang
Xun Shao
Yusheng Ji
Year: 2022
Relay-Assisted Task Offloading Optimization for MEC-Enabled Internet of Vehicles
MONAMI
Springer
DOI: 10.1007/978-3-030-94763-7_12
Abstract
Mobile edge computing (MEC)-enabled Internet of Vehicles (IoV) is a promising way to provide low latency and high computation functions to smart vehicles. Owing to the mobility of vehicles and unpredicted distribution of computation-intensive tasks, computational resources at the edge may be utilized with only low efficiency. To solve this problem, this study investigates a relay-supported task offloading scheme in MEC-enabled IoV. In this scheme, computational tasks produced by vehicles are predictively offloaded to MEC nodes through relays to improve the allocation of computational resources. A combinational problem is used to model relay selection for vehicles connected to the MEC. To solve the corresponding problem, a low-complexity algorithm that combines the Hungarian and the Greedy algorithms is designed. Simulation results show that the proposed scheme achieves better performance than existing schemes in terms of overall efficiency and offloading time.
