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Contract-theoretic Approach for Delay Constrained Offloading in Vehicular Edge Computing Networks

Authors:

Sabita Maharjan,

Yan ZhangAuthors Info & Claims

Mobile Networks and Applications, Volume 24, Issue 3

Pages 1003 - 1014

https://doi.org/10.1007/s11036-018-1032-0

Published: 01 June 2019 Publication History

Abstract

Mobile Edge Computing (MEC) is a promising solution to improve vehicular services through offloading computation to cloud servers in close proximity to mobile vehicles. However, the self-interested nature together with the high mobility characteristic of the vehicles make the design of the computation offloading scheme a significant challenge. In this paper, we propose a new Vehicular Edge Computing (VEC) framework to model the computation offloading process of the mobile vehicles running on a bidirectional road. Based on this framework, we adopt a contract theoretic approach to design optimal offloading strategies for the VEC service provider, which maximize the revenue of the provider while enhancing the utilities of the vehicles. To further improve the utilization of the computing resources of the VEC servers, we incorporate task priority distinction as well as additional resource providing into the design of the offloading scheme, and propose an efficient VEC server selection and computing resource allocation algorithm. Numerical results indicate that our proposed schemes greatly enhance the revenue of the VEC provider, and concurrently improve the utilization of cloud computing resources.

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Cited By

Jiang SLi JSang GWu HZhou Y(2024)Vehicular Edge Computing Meets Cache: An Access Control Scheme With Fair Incentives for Privacy-Aware Content DeliveryIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2024.335752225:8(8404-8418)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1109/TITS.2024.3357522
Cao DHuang SGu NSharma PMa XJi B(2024)An Incentive Approach for Sustainable Vehicle Resource Utilization in Delay-Energy Sensitive Vehicular Edge ComputingIEEE Transactions on Consumer Electronics10.1109/TCE.2024.341631870:3(5177-5187)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1109/TCE.2024.3416318
Zheng YZou LZhang WYang JYang LLin Z(2023)Contract-based Cooperative Computation and Communication Resources Sharing in Mobile Edge ComputingJournal of Grid Computing10.1007/s10723-023-09649-y21:1Online publication date: 27-Feb-2023
https://dl.acm.org/doi/10.1007/s10723-023-09649-y
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Published In

cover image Mobile Networks and Applications

Mobile Networks and Applications Volume 24, Issue 3

Jun 2019

414 pages

ISSN:1383-469X

Issue’s Table of Contents

Copyright © Copyright © 2019 Springer Science+Business Media, LLC, part of Springer Nature.

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 June 2019

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Jiang SLi JSang GWu HZhou Y(2024)Vehicular Edge Computing Meets Cache: An Access Control Scheme With Fair Incentives for Privacy-Aware Content DeliveryIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2024.335752225:8(8404-8418)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1109/TITS.2024.3357522
Cao DHuang SGu NSharma PMa XJi B(2024)An Incentive Approach for Sustainable Vehicle Resource Utilization in Delay-Energy Sensitive Vehicular Edge ComputingIEEE Transactions on Consumer Electronics10.1109/TCE.2024.341631870:3(5177-5187)Online publication date: 1-Aug-2024
https://dl.acm.org/doi/10.1109/TCE.2024.3416318
Zheng YZou LZhang WYang JYang LLin Z(2023)Contract-based Cooperative Computation and Communication Resources Sharing in Mobile Edge ComputingJournal of Grid Computing10.1007/s10723-023-09649-y21:1Online publication date: 27-Feb-2023
https://dl.acm.org/doi/10.1007/s10723-023-09649-y
Li X(2022)5G Converged Network Resource Allocation Strategy Based on Reinforcement Learning in Edge Cloud Computing EnvironmentComputational Intelligence and Neuroscience10.1155/2022/61747082022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/6174708
Kazmi SDang TYaqoob IManzoor AHussain RKhan AHong CSalah K(2022)A Novel Contract Theory-Based Incentive Mechanism for Cooperative Task-Offloading in Electrical Vehicular NetworksIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2021.307891323:7(8380-8395)Online publication date: 1-Jul-2022
https://dl.acm.org/doi/10.1109/TITS.2021.3078913
Meneguette RDe Grande RUeyama JFilho GMadeira E(2021)Vehicular Edge Computing: Architecture, Resource Management, Security, and ChallengesACM Computing Surveys10.1145/348512955:1(1-46)Online publication date: 23-Nov-2021
https://dl.acm.org/doi/10.1145/3485129
Kazmi SOtoum SHussain RMouftah H(2021)A Novel Deep Reinforcement Learning-based Approach for Task-offloading in Vehicular Networks2021 IEEE Global Communications Conference (GLOBECOM)10.1109/GLOBECOM46510.2021.9685073(1-6)Online publication date: 7-Dec-2021
https://dl.acm.org/doi/10.1109/GLOBECOM46510.2021.9685073
Dziyauddin RNiyato DLuong NMohd Atan AMohd Izhar MAzmi MMohd Daud S(2021)Computation offloading and content caching and delivery in Vehicular Edge NetworkComputer Networks: The International Journal of Computer and Telecommunications Networking10.1016/j.comnet.2021.108228197:COnline publication date: 9-Oct-2021
https://dl.acm.org/doi/10.1016/j.comnet.2021.108228
Wu QXu XZhao QDai F(2021)Tasks Offloading for Connected Autonomous Vehicles in Edge ComputingMobile Networks and Applications10.1007/s11036-021-01794-627:6(2295-2304)Online publication date: 3-Aug-2021
https://dl.acm.org/doi/10.1007/s11036-021-01794-6
Liu WYu ZYan MWang GLiu X(2021)A Novel Task-Allocation Framework Based on Decision-Tree Classification Algorithm in MECNetwork and Parallel Computing10.1007/978-3-030-93571-9_8(93-104)Online publication date: 3-Nov-2021
https://dl.acm.org/doi/10.1007/978-3-030-93571-9_8
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