A Collaborative Task Offloading Scheme in Vehicular Edge Computing

Muhammad Saleh Bute, Pingzhi Fan, Gang Liu, Fakhar Abbas, Zhiguo Ding

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

19 Scopus citations

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.

Original languageBritish English
Title of host publication2021 IEEE 93rd Vehicular Technology Conference, VTC 2021-Spring - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728189642
DOIs
StatePublished - Apr 2021
Event93rd IEEE Vehicular Technology Conference, VTC 2021-Spring - Virtual, Online
Duration: 25 Apr 202128 Apr 2021

Publication series

NameIEEE Vehicular Technology Conference
Volume2021-April
ISSN (Print)1550-2252

Conference

Conference93rd IEEE Vehicular Technology Conference, VTC 2021-Spring
CityVirtual, Online
Period25/04/2128/04/21

Keywords

  • clustering
  • matching
  • Vehicle to vehicle (V2X)
  • vehicular edge computing (VEC)

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