QoE-Aware Task Offloading in Edge Computing Environment: Potential Game Approach

SHI Zi-qi; XIE Gang; FAN Wen-hao; LIU Yuan-an

doi:10.12263/DZXB.20241053

您当前的位置：

首页 >

文章列表页 >

QoE-Aware Task Offloading in Edge Computing Environment: Potential Game Approach

PAPERS | 更新时间：2025-10-16

- QoE-Aware Task Offloading in Edge Computing Environment: Potential Game Approach
- ACTA ELECTRONICA SINICA Vol. 53, Issue 6, Pages: 1943-1957(2025)
- 作者机构：
  
  1.北京邮电大学信息与通信工程学院，北京 100876
  2.北京邮电大学电子工程学院，北京 100876
- 作者简介：
- 基金信息：
  
  Beijing Natural Science Foundation Haidian Original Innovation Joint Fund(L242080);National Natural Science Foundation of China(62271086)
- DOI：10.12263/DZXB.20241053
  CLC： TN929.5;TP391.9
- Received：23 November 2024，
  
  Revised：2025-03-11，
  
  Published：25 June 2025
- 稿件说明：
移动端阅览
师子琦, 谢刚, 范文浩, 等. 边缘计算中基于QoE感知的任务卸载：势博弈方法[J]. 电子学报, 2025, 53(06): 1943-1957.

SHI Zi-qi, XIE Gang, FAN Wen-hao, et al. QoE-Aware Task Offloading in Edge Computing Environment: Potential Game Approach[J]. Acta Electronica Sinica, 2025, 53(06): 1943-1957.
师子琦, 谢刚, 范文浩, 等. 边缘计算中基于QoE感知的任务卸载：势博弈方法[J]. 电子学报, 2025, 53(06): 1943-1957. DOI：10.12263/DZXB.20241053

SHI Zi-qi, XIE Gang, FAN Wen-hao, et al. QoE-Aware Task Offloading in Edge Computing Environment: Potential Game Approach[J]. Acta Electronica Sinica, 2025, 53(06): 1943-1957. DOI：10.12263/DZXB.20241053

摘要

随着5G的广泛应用，边缘计算技术被用于任务卸载和处理，基于博弈论的边缘计算策略成为当前研究领域中的热点.本文以最大化用户体验质量（Quality of Experience，QoE）为目标，研究时间约束条件下的多用户任务卸载问题.本文首先从通信模型、计算模型和时间约束三个方面建立系统模型，然后将优化问题转换为博弈问题，给出并证明存在纳什均衡解.本文提出了一种分布式多用户卸载算法（Distributed Multi-User Offloading，DMUO），首次实现了多用户在单时隙内同步更新策略，显著降低了计算开销并提升了收敛速度.理论分析表明，DMUO算法能够收敛至纳什均衡解，并给出了迭代次数的上限.此外，通过分析最坏情况策略与最优解的性能差距，验证了算法的鲁棒性.仿真实验表明，DMUO算法具有优异的收敛性和系统性能，证明了其在大规模边缘计算环境中的可扩展性和实际适用性.

Abstract

With the widespread adoption of 5G technology

the importance of edge computing in task offloading and processing has become increasingly prominent. Consequently

this trend has led to the emergence of game theory-based edge computing strategies as a research hot spot. This paper aims to maximize the quality of experience (QoE) by studying the multi-user task offloading problem under time constraints. A system model is constructed from three aspects: communication model

computation model

and time constraints. The optimization problem is first transformed into a game-theoretic problem

and thereafter

the existence of a Nash equilibrium solution is proven. This paper proposes a distributed multi-user offloading (DMUO) algorithm

which enables multiple users to simultaneously update their policies within a single time slot for the first time

significantly reducing computational overhead and improving convergence speed. Theoretical analysis not only demonstrates that the DMUO algorithm converges to the Nash equilibrium solution

but also provides an upper bound on the number of iterations.Furthermore

the robustness of the algorithm is verified by analyzing the performance gap between the worst-case strategy and the optimal solution. Simulation results show that the DMUO algorithm exhibits excellent convergence and system performance

proving its scalability and practical applicability in large-scale edge computing environments

关键词

Keywords

references

DINH H T , LEE C , NIYATO D , et al . A survey of mobile cloud computing: Architecture, applications, and approaches [J ] . Wireless Communications and Mobile Computing , 2013 , 13 ( 18 ): 1587 - 1611 .

JIN Y , WANG F , ZHAO H W , et al . Survey on trust mechanisms in the environment of cloud computing [J ] . Journal of Chinese Computer Systems , 2016 , 37 ( 1 ): 1 - 11 .

MAO Y Y , YOU C S , ZHANG J , et al . A survey on mobile edge computing: The communication perspective [J ] . IEEE Communications Surveys Tutorials , 2017 , 19 ( 4 ): 2322 - 2358 .

DROLIA U , MARTINS R , TAN J Q , et al . The case for mobile edge-clouds [C ] // 2013 IEEE 10th International Conference on Ubiquitous Intelligence and Computing and 2013 IEEE 10th International Conference on Autonomic and Trusted Computing . Piscataway : IEEE , 2013 : 209 - 215 .

CHIANG M , ZHANG T . Fog and IoT: An overview of research opportunities [J ] . IEEE Internet of Things Journal , 2016 , 3 ( 6 ): 854 - 864 .

WU Y , NI K J , ZHANG C , et al . NOMA-assisted multi-access mobile edge computing: A joint optimization of computation offloading and time allocation [J ] . IEEE Transactions on Vehicular Technology , 2018 , 67 ( 12 ): 12244 - 12258 .

SHAH-MANSOURI H , WONG V W S . Hierarchical fog-cloud computing for IoT systems: A computation offloading game [J ] . IEEE Internet of Things Journal , 2018 , 5 ( 4 ): 3246 - 3257 .

CAI Y , RAN L , ZHANG J , et al . Latency optimization for D2D-enabled parallel mobile edge computing in cellular networks [J ] . EURASIP Journal on Wireless Communications and Networking , 2021 , 2021 ( 1 ). DOI: 10.1186/s13638-021-02008-z http://dx.doi.org/10.1186/s13638-021-02008-z .

PU L J , CHEN X , MAO G Q , et al . Chimera: An energy-efficient and deadline-aware hybrid edge computing framework for vehicular crowdsensing applications [J ] . IEEE Internet of Things Journal , 2019 , 6 ( 1 ): 84 - 99 .

YANG L , CAO J N , TANG S J , et al . A framework for partitioning and execution of data stream applications in mobile cloud computing [C ] // 2012 IEEE Fifth International Conference on Cloud Computing . Piscataway : IEEE , 2012 : 794 - 802 .

WEN Y G , ZHANG W W , LUO H Y . Energy-optimal mobile application execution: Taming resource-poor mobile devices with cloud clones [C ] // 2012 Proceedings IEEE INFOCOM . Piscataway : IEEE , 2012 : 2716 - 2720 .

LI S Y , HU X H , DU Y W . Deep reinforcement learning and game theory for computation offloading in dynamic edge computing markets [J ] . IEEE Access , 2021 , 9 : 121456 - 121466 .

WU L T , SUN P , WANG Z B , et al . Computation offloading in multi-cell networks with collaborative edge-cloud computing: A game theoretic approach [J ] . IEEE Transactions on Mobile Computing , 2023 , 23 ( 3 ): 2093 - 2106 .

TANG Q Q , FEI Z S , LI B , et al . Computation offloading in LEO satellite networks with hybrid cloud and edge computing [J ] . IEEE Internet of Things Journal , 2021 , 8 ( 11 ): 9164 - 9176 .

NGUYEN D C , PATHIRANA P N , DING M , et al . Deep reinforcement learning for collaborative offloading in heterogeneous edge networks [C ] // 2021 IEEE/ACM 21st International Symposium on Cluster , Cloud and Internet Computing . Piscataway : IEEE , 2021 : 297 - 303 .

BISHOYI P K , MISRA S . Enabling green mobile-edge computing for 5G-based healthcare applications [J ] . IEEE Transactions on Green Communications and Networking , 2021 , 5 ( 3 ): 1623 - 1631 .

LIU Y . Exploiting NOMA for cooperative edge computing [J ] . IEEE Wireless Communications , 2019 , 26 ( 5 ): 99 - 103 .

CHEN X , JIAO L , LI W Z , et al . Efficient multi-user computation offloading for mobile-edge cloud computing [J ] . IEEE/ACM Transactions on Networking , 2016 , 24 ( 5 ): 2795 - 2808 .

DING Y , LI K L , LIU C B , et al . A potential game theoretic approach to computation offloading strategy optimization in end-edge-cloud computing [J ] . IEEE Transactions on Parallel and Distributed Systems , 2022 , 33 ( 6 ): 1503 - 1519 .

CHEN Y , ZHAO J , WU Y , et al . QoE-aware decentralized task offloading and resource allocation for end-edge-cloud systems: A game-theoretical approach [J ] . IEEE Transactions on Mobile Computing , 2024 , 23 ( 1 ): 769 - 784 .

HE Q , CUI G M , ZHANG X Y , et al . A game-theoretical approach for user allocation in edge computing environment [J ] . IEEE Transactions on Parallel and Distributed Systems , 2020 , 31 ( 3 ): 515 - 529 .

YANG L C , ZHANG H L , LI X , et al . A distributed computation offloading strategy in small-cell networks integrated with mobile edge computing [J ] . IEEE/ACM Transactions on Networking , 2018 , 26 ( 6 ): 2762 - 2773 .

ZARISKI O . An Introduction to Game Theory [M ] . Shanghai : Shanghai University of Finance and Economics Press , 2005 .

FIEDLER M , HOSSFELD T , TRAN-GIA P . A generic quantitative relationship between quality of experience and quality of service [J ] . IEEE Network , 2010 , 24 ( 2 ): 36 - 41 .

LU H D , HE X M , DU M , et al . Edge QoE: Computation offloading with deep reinforcement learning for Internet of Things [J ] . IEEE Internet of Things Journal , 2020 , 7 ( 10 ): 9255 - 9265 .

LAI P , HE Q , CUI G M , et al . Quality of experience-aware user allocation in edge computing systems: A potential game [C ] // 2020 IEEE 40th International Conference on Distributed Computing Systems . Piscataway : IEEE , 2020 : 223 - 233 .

陈宇博 . 卫星边缘计算场景下的计算卸载研究 [D ] . 重庆 : 重庆邮电大学 , 2022 .

CHEN Y B . Research on Computing Unloading in Satellite Edge Computing Scenarios [D ] . Chongqing : Chongqing University of Posts and Telecommunications , 2022 . (in Chinese)

BI S Z , ZHANG Y J . Computation rate maximization for wireless powered mobile-edge computing with binary computation offloading [J ] . IEEE Transactions on Wireless Communications , 2018 , 17 ( 6 ): 4177 - 4190 .

BARBAROSSA S , SARDELLITTI S , DI LORENZO P . Joint allocation of computation and communication resources in multiuser mobile cloud computing [C ] // 2013 IEEE 14th Workshop on Signal Processing Advances in Wireless Communications . Piscataway : IEEE , 2013 : 26 - 30 .

IOSIFIDIS G , GAO L , HUANG J , et al . An iterative double auction mechanism for mobile data offloading [C ] // 2013 11th International Symposium and Workshops on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt) . Piscataway : IEEE , 2013 : 154 - 161 .

XIAO M B , SHROFF N B , CHONG E K P . A utility-based power-control scheme in wireless cellular systems [J ] . IEEE/ACM Transactions on Networking , 2003 , 11 ( 2 ): 210 - 221 .

KHAN A U R , OTHMAN M , AHMAD MADANI S , et al . A survey of mobile cloud computing application models [J ] . IEEE Communications Surveys Tutorials , 2014 , 16 ( 1 ): 393 - 413 .

MESSOUS M A , SENOUCI S M , SEDJELMACI H , et al . A game theory based efficient computation offloading in an UAV network [J ] . IEEE Transactions on Vehicular Technology , 2019 , 68 ( 5 ): 4964 - 4974 .

CHEN X . Decentralized computation offloading game for mobile cloud computing [J ] . IEEE Transactions on Parallel and Distributed Systems , 2014 , 26 ( 4 ): 974 - 983 .

MONDERER D , SHAPLEY L S . Potential games [J ] . Games and Economic Behavior , 1996 , 14 ( 1 ): 124 - 143 .

VOORNEVELD M . Equilibria and approximate equilibria in infinite potential games [J ] . Economics Letters , 1997 , 56 ( 2 ): 163 - 169 .

BUDHIRAJA I , KUMAR N , TYAGI S . ISHU: Interference reduction scheme for D2D mobile groups using uplink NOMA [J ] . IEEE Transactions on Mobile Computing , 2022 , 21 ( 9 ): 3208 - 3224 .

ZENG H Y , ZHU X , JIANG Y F , et al . A green coordinated multi-cell NOMA system with fuzzy logic based multi-criterion user mode selection and resource allocation [J ] . IEEE Journal of Selected Topics in Signal Processing , 2019 , 13 ( 3 ): 480 - 495 .

LAI P , HE Q , CUI G M , et al . Edge User Aallocation with Dynamic Quality of Service [M ] // Lecture Notes in Computer Science . Cham : Springer International Publishing , 2019 : 86 - 101 .

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Fair Computation Offloading for a Multi-Antenna NOMA Aided Mobile Edge Computing Network

A Multi-User Fine-Grained Task Offloading Scheduling Approach of Mobile Edge Computing

A Survey of Computation Offloading in Vehicular Edge Computing Networks

Related Author

ZENG Sheng

HUANG Xiao-hong

LI Dan-dan

YU Wei-jun

ZHANG De-gan

CUI Yu-ya

ZHU Hao-li

YANG Peng

Related Institution

School of Computer Science（National Pilot Software Engineering School）， Beijing University of Posts and Telecommunications

Office of Party and Government Affairs， Torch Hi-tech Industrial Development Zone

Ministry of Education Key Laboratory of Computer Vision and System， Tianjin University of Technology

School of Sports Economics and Management， Tianjin University of Sport

Tianjin Key Laboratory of Intelligent Computing & Novel Software Technology， Tianjin University of Technology

⁰