Game-Theoretic Dependent Task Offloading and Resource Pricing in Vehicular Edge Computing

Liang Zhao, Shuai Huang, Huan Zhou, Zilong Bai, Victor C.M. Leung

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

Abstract

This paper proposes a Stacklberg game-based Dependent task Offloading and resource Pricing framework (SDOP), where vehicles partially offload their dependent substaks to the SDN controller and pays corresponding fees. Firstly, we model the interaction between the SDN controller and vehicles as a Stackelberg game, where both parties wish to maximize their utility. Then, we employ the backward induction approach to analyze the investigated problem, and prove the existence and uniqueness of Nash and Stackelberg equilibrium. Next, we propose a Gradient Ascent Plus Genetic algorithm (GAPG) to solve the considered problem. Finally, extensive simulation results show that the proposed GAPG outperforms other baseline schemes under various scenarios.

Original languageEnglish
Title of host publication2024 IEEE/ACM 32nd International Symposium on Quality of Service, IWQoS 2024
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350350128
DOIs
StatePublished - 2024
Event32nd IEEE/ACM International Symposium on Quality of Service, IWQoS 2024 - Guangzhou, China
Duration: 19 Jun 202421 Jun 2024

Publication series

NameIEEE International Workshop on Quality of Service, IWQoS
ISSN (Print)1548-615X

Conference

Conference32nd IEEE/ACM International Symposium on Quality of Service, IWQoS 2024
Country/TerritoryChina
CityGuangzhou
Period19/06/2421/06/24

Keywords

  • Dependent Task Offloading
  • Resource Pricing
  • Stackelberg Game
  • Vehicular Edge Computing

Fingerprint

Dive into the research topics of 'Game-Theoretic Dependent Task Offloading and Resource Pricing in Vehicular Edge Computing'. Together they form a unique fingerprint.

Cite this