@inproceedings{5b82a92eb91944bc9d1a833b46ca7b0e,
title = "A Collaborative Task Offloading Scheme in Vehicular Edge Computing",
abstract = "The increase of mobile applications in the internet of vehicles (IoVs), necessitates the demand for higher computation capabilities. Vehicles can transfer related applications to another nodes for processing. In this paper, an efficient task offloading scheme for cellular vehicle to everything (C-V2X) is proposed to improve offloading reliability and latency. Vehicles are grouped into clusters, where vehicles in need of assistance can transfer their task to other vehicles for processing through the vehicle to vehicle (V2V) link, or transfer their task to the mobile edge computing (MEC) server via the vehicle to network (V2N) link. Matching theory is exploited for the task assignments. Simulation results reveals that the proposed scheme performs better than the existing schemes.",
keywords = "clustering, matching, Vehicle to vehicle (V2X), vehicular edge computing (VEC)",
author = "Bute, {Muhammad Saleh} and Pingzhi Fan and Gang Liu and Fakhar Abbas and Zhiguo Ding",
note = "Funding Information: ACKNOWLEDGMENT This work was supported by the NSFC Project No.61731017, No.62020106001, and the 111 project No.111-2-14. The work of Gang Liu was supported by NSFC Project No.61971359. Publisher Copyright: {\textcopyright} 2021 IEEE.; 93rd IEEE Vehicular Technology Conference, VTC 2021-Spring ; Conference date: 25-04-2021 Through 28-04-2021",
year = "2021",
month = apr,
doi = "10.1109/VTC2021-Spring51267.2021.9448975",
language = "British English",
series = "IEEE Vehicular Technology Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2021 IEEE 93rd Vehicular Technology Conference, VTC 2021-Spring - Proceedings",
address = "United States",
}