Next Article in Journal
A Survey of Sound Source Localization and Detection Methods and Their Applications
Next Article in Special Issue
Resource Cluster-Based Resource Search and Allocation Scheme for Vehicular Clouds in Vehicular Ad Hoc Networks
Previous Article in Journal
Vision Measurement Method Based on Plate Glass Window Refraction Model in Tunnel Construction
Previous Article in Special Issue
Ultra-Reliable Deep-Reinforcement-Learning-Based Intelligent Downlink Scheduling for 5G New Radio-Vehicle to Infrastructure Scenarios
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Sensors
Volume 24
Issue 1
10.3390/s24010069
sensors-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

A Game-Based Computing Resource Allocation Scheme of Edge Server in Vehicular Edge Computing Networks Considering Diverse Task Offloading Modes

by
Xiangyan Liu
1,*,
Jianhong Zheng
1,
Meng Zhang
2,
Yang Li
3,
Rui Wang
1,4 and
Yun He
1
1
School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
2
State Key Laboratory of Block Chain and Data Security, Zhejiang University, Hangzhou 310058, China
3
Cyberspace Security Key Laboratory of Sichuan Province, Chengdu 610043, China
4
Department of Electronic Communication Engineering, Yuxi Normal University, Yuxi 653100, China
*
Author to whom correspondence should be addressed.
Sensors 2024, 24(1), 69; https://doi.org/10.3390/s24010069
Submission received: 19 October 2023 / Revised: 20 December 2023 / Accepted: 20 December 2023 / Published: 22 December 2023
(This article belongs to the Special Issue Vehicle-to-Everything (V2X) Communication for Intelligent Transportation)
Browse Figures
Versions Notes

Abstract

Introducing partial task offloading into vehicle edge computing networks (VECNs) can ease the burden placed on the Internet of Vehicles (IoV) by emerging vehicle applications and services. In this circumstance, the task offloading ratio and the resource allocation of edge servers (ES) need to be addressed urgently. Based on this, we propose a best response-based centralized multi-TaV computation resource allocation algorithm (BR-CMCRA) by jointly considering service vehicle (SeV) selection, offloading strategy making, and computing resource allocation in a multiple task vehicle (TaV) system, and the utility function is related to the processing delay of all tasks, which ensures the TaVs’s quality of services (QoS). In the scheme, SeV is first selected from three candidate SeVs (CSVs) near the corresponding TaV based on the channel gain. Then, an exact potential game (EPG) is conducted to allocate computation resources, where the computing resources can be allocated step by step to achieve the maximum benefit. After the resource allocation, the task offloading ratio can be acquired accordingly. Simulation results show that the proposed algorithm has better performance than other basic algorithms.
Keywords: vehicular edge computing networks; computing resource allocation; offloading strategy; exact potential game vehicular edge computing networks; computing resource allocation; offloading strategy; exact potential game

Share and Cite

MDPI and ACS Style

Liu, X.; Zheng, J.; Zhang, M.; Li, Y.; Wang, R.; He, Y. A Game-Based Computing Resource Allocation Scheme of Edge Server in Vehicular Edge Computing Networks Considering Diverse Task Offloading Modes. Sensors 2024, 24, 69. https://doi.org/10.3390/s24010069

AMA Style

Liu X, Zheng J, Zhang M, Li Y, Wang R, He Y. A Game-Based Computing Resource Allocation Scheme of Edge Server in Vehicular Edge Computing Networks Considering Diverse Task Offloading Modes. Sensors. 2024; 24(1):69. https://doi.org/10.3390/s24010069

Chicago/Turabian Style

Liu, Xiangyan, Jianhong Zheng, Meng Zhang, Yang Li, Rui Wang, and Yun He. 2024. "A Game-Based Computing Resource Allocation Scheme of Edge Server in Vehicular Edge Computing Networks Considering Diverse Task Offloading Modes" Sensors 24, no. 1: 69. https://doi.org/10.3390/s24010069

APA Style

Liu, X., Zheng, J., Zhang, M., Li, Y., Wang, R., & He, Y. (2024). A Game-Based Computing Resource Allocation Scheme of Edge Server in Vehicular Edge Computing Networks Considering Diverse Task Offloading Modes. Sensors, 24(1), 69. https://doi.org/10.3390/s24010069

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop