SAC-based Computation Offloading and Resource Allocation in Vehicular Edge Computing

Yanlang Zheng, Huan Zhou, Rui Chen, Kai Jiang, Yue Cao

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

11 Scopus citations

Abstract

The Vehicular Edge Computing (VEC) provides powerful computing resources for intelligent terminals. However, the diversity of computing resources at edge nodes (i.e., edge servers and idle vehicles) and the mobility of vehicles impose great challenges on computation offloading. In this paper, we investigate the joint optimization problem of computation offloading and resource allocation in a cooperative vehicular network by exploiting idle vehicles and Road Side Units (RSUs) equipped with edge servers. In order to minimize the task completion time under latency constraint, a Soft Actor-Critic (SAC)-based algorithm is proposed to solve the problem. The simulation results show that the proposed SAC-based algorithm can effectively reduce the total latency of the system, and its performance is significantly better than other benchmark methods.

Original languageEnglish
Title of host publicationINFOCOM WKSHPS 2022 - IEEE Conference on Computer Communications Workshops
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665409261
DOIs
StatePublished - 2022
Externally publishedYes
Event2022 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2022 - Virtual, Online, United States
Duration: 2 May 20225 May 2022

Publication series

NameINFOCOM WKSHPS 2022 - IEEE Conference on Computer Communications Workshops

Conference

Conference2022 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2022
Country/TerritoryUnited States
CityVirtual, Online
Period2/05/225/05/22

Keywords

  • Soft Actor-Critic
  • collaborative computation offloading
  • resource allocation
  • vehicle edge computing

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