An Evolutionary Game Theoretic-Based Approach to Task Offloading in Hybrid Vehicular Cloud-Edge Environment

Jinpeng Li; Yunni Xia; Hui Liu; Jiafeng Feng; Ke Zhang; Zhaoguang Ding; Yumin Dong; Yang Yu; Yu Wang; Qinglan Peng; Xifeng Xu

doi:10.1007/978-3-031-77072-2_1

An Evolutionary Game Theoretic-Based Approach to Task Offloading in Hybrid Vehicular Cloud-Edge Environment

Jinpeng Li, Yunni Xia^*, Hui Liu, Jiafeng Feng, Ke Zhang, Zhaoguang Ding, Yumin Dong, Yang Yu, Yu Wang, Qinglan Peng, Xifeng Xu

^*Corresponding author for this work

School of Computer Science and Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Vehicle Edge Computing (VEC) is a novel computing paradigm that addresses the computational demands of intelligent vehicles by offloading tasks to edge servers. In a VEC environment, edge servers’ limited storage and processing capacity require a sensible task offloading strategy, where only a part of computing requirement can be offloaded directly to the VEC server and the remaining to the remote cloud. A primary challenge in this context is the creation of an effective and responsive task offloading algorithm that improves the utility. This study proposes an evolutionary game theoretic-based approach, utilizing a Dynamical-Resource Evolutionary Game (DREG) algorithm for decentralized task offloading. DREG leverages the Evolutionary Stable Strategy(ESS) and Adaptive Resource Allocation(ARA) method to optimize response delay and energy cost while increasing success rate. Experimental results indicate that DREG outperforms traditional methods across various performance metrics.

Original language	English
Title of host publication	Web Services – ICWS 2024 - 31st International Conference, Held as Part of the Services Conference Federation, SCF 2024, Proceedings
Editors	Yuchao Zhang, Liang-Jie Zhang
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	1-15
Number of pages	15
ISBN (Print)	9783031770715
DOIs	https://doi.org/10.1007/978-3-031-77072-2_1
Publication status	Published - 2025
Event	31st International Conference on Web Services, ICWS 2024, Held as Part of the Services Conference Federation, SCF 2024 - Bangkok, Thailand Duration: 16 Nov 2024 → 19 Nov 2024

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	15428 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	31st International Conference on Web Services, ICWS 2024, Held as Part of the Services Conference Federation, SCF 2024
Country/Territory	Thailand
City	Bangkok
Period	16/11/24 → 19/11/24

Keywords

Evolutionary game theoretic
Fault tolerant
Resource allocation
Task offloading
Vehicle edge computing

Access to Document

10.1007/978-3-031-77072-2_1

Cite this

Li, J., Xia, Y., Liu, H., Feng, J., Zhang, K., Ding, Z., Dong, Y., Yu, Y., Wang, Y., Peng, Q., & Xu, X. (2025). An Evolutionary Game Theoretic-Based Approach to Task Offloading in Hybrid Vehicular Cloud-Edge Environment. In Y. Zhang, & L.-J. Zhang (Eds.), Web Services – ICWS 2024 - 31st International Conference, Held as Part of the Services Conference Federation, SCF 2024, Proceedings (pp. 1-15). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 15428 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-77072-2_1

Li, Jinpeng ; Xia, Yunni ; Liu, Hui et al. / An Evolutionary Game Theoretic-Based Approach to Task Offloading in Hybrid Vehicular Cloud-Edge Environment. Web Services – ICWS 2024 - 31st International Conference, Held as Part of the Services Conference Federation, SCF 2024, Proceedings. editor / Yuchao Zhang ; Liang-Jie Zhang. Springer Science and Business Media Deutschland GmbH, 2025. pp. 1-15 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "An Evolutionary Game Theoretic-Based Approach to Task Offloading in Hybrid Vehicular Cloud-Edge Environment",

abstract = "Vehicle Edge Computing (VEC) is a novel computing paradigm that addresses the computational demands of intelligent vehicles by offloading tasks to edge servers. In a VEC environment, edge servers{\textquoteright} limited storage and processing capacity require a sensible task offloading strategy, where only a part of computing requirement can be offloaded directly to the VEC server and the remaining to the remote cloud. A primary challenge in this context is the creation of an effective and responsive task offloading algorithm that improves the utility. This study proposes an evolutionary game theoretic-based approach, utilizing a Dynamical-Resource Evolutionary Game (DREG) algorithm for decentralized task offloading. DREG leverages the Evolutionary Stable Strategy(ESS) and Adaptive Resource Allocation(ARA) method to optimize response delay and energy cost while increasing success rate. Experimental results indicate that DREG outperforms traditional methods across various performance metrics.",

keywords = "Evolutionary game theoretic, Fault tolerant, Resource allocation, Task offloading, Vehicle edge computing",

author = "Jinpeng Li and Yunni Xia and Hui Liu and Jiafeng Feng and Ke Zhang and Zhaoguang Ding and Yumin Dong and Yang Yu and Yu Wang and Qinglan Peng and Xifeng Xu",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.; 31st International Conference on Web Services, ICWS 2024, Held as Part of the Services Conference Federation, SCF 2024 ; Conference date: 16-11-2024 Through 19-11-2024",

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Li, J, Xia, Y, Liu, H, Feng, J, Zhang, K, Ding, Z, Dong, Y, Yu, Y, Wang, Y, Peng, Q & Xu, X 2025, An Evolutionary Game Theoretic-Based Approach to Task Offloading in Hybrid Vehicular Cloud-Edge Environment. in Y Zhang & L-J Zhang (eds), Web Services – ICWS 2024 - 31st International Conference, Held as Part of the Services Conference Federation, SCF 2024, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 15428 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 1-15, 31st International Conference on Web Services, ICWS 2024, Held as Part of the Services Conference Federation, SCF 2024, Bangkok, Thailand, 16/11/24. https://doi.org/10.1007/978-3-031-77072-2_1

An Evolutionary Game Theoretic-Based Approach to Task Offloading in Hybrid Vehicular Cloud-Edge Environment. / Li, Jinpeng; Xia, Yunni; Liu, Hui et al.
Web Services – ICWS 2024 - 31st International Conference, Held as Part of the Services Conference Federation, SCF 2024, Proceedings. ed. / Yuchao Zhang; Liang-Jie Zhang. Springer Science and Business Media Deutschland GmbH, 2025. p. 1-15 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 15428 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Feng, Jiafeng

AU - Zhang, Ke

AU - Ding, Zhaoguang

AU - Dong, Yumin

AU - Yu, Yang

AU - Wang, Yu

AU - Peng, Qinglan

AU - Xu, Xifeng

N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

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Y1 - 2025

N2 - Vehicle Edge Computing (VEC) is a novel computing paradigm that addresses the computational demands of intelligent vehicles by offloading tasks to edge servers. In a VEC environment, edge servers’ limited storage and processing capacity require a sensible task offloading strategy, where only a part of computing requirement can be offloaded directly to the VEC server and the remaining to the remote cloud. A primary challenge in this context is the creation of an effective and responsive task offloading algorithm that improves the utility. This study proposes an evolutionary game theoretic-based approach, utilizing a Dynamical-Resource Evolutionary Game (DREG) algorithm for decentralized task offloading. DREG leverages the Evolutionary Stable Strategy(ESS) and Adaptive Resource Allocation(ARA) method to optimize response delay and energy cost while increasing success rate. Experimental results indicate that DREG outperforms traditional methods across various performance metrics.

AB - Vehicle Edge Computing (VEC) is a novel computing paradigm that addresses the computational demands of intelligent vehicles by offloading tasks to edge servers. In a VEC environment, edge servers’ limited storage and processing capacity require a sensible task offloading strategy, where only a part of computing requirement can be offloaded directly to the VEC server and the remaining to the remote cloud. A primary challenge in this context is the creation of an effective and responsive task offloading algorithm that improves the utility. This study proposes an evolutionary game theoretic-based approach, utilizing a Dynamical-Resource Evolutionary Game (DREG) algorithm for decentralized task offloading. DREG leverages the Evolutionary Stable Strategy(ESS) and Adaptive Resource Allocation(ARA) method to optimize response delay and energy cost while increasing success rate. Experimental results indicate that DREG outperforms traditional methods across various performance metrics.

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Li J, Xia Y, Liu H, Feng J, Zhang K, Ding Z et al. An Evolutionary Game Theoretic-Based Approach to Task Offloading in Hybrid Vehicular Cloud-Edge Environment. In Zhang Y, Zhang LJ, editors, Web Services – ICWS 2024 - 31st International Conference, Held as Part of the Services Conference Federation, SCF 2024, Proceedings. Springer Science and Business Media Deutschland GmbH. 2025. p. 1-15. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-77072-2_1