Adaptive Cooperative Task Offloading for Energy-Efficient Small Cell MEC Networks

被引:5
|
作者
Jing, Zewei [1 ]
Yang, Qinghai [1 ]
Wu, Yan [1 ]
Qin, Meng [2 ]
Kwak, Kyung Sup [3 ]
Wang, Xianbin [4 ]
机构
[1] Xidian Univ, Sch Telecommun Engn, Xian, Peoples R China
[2] Shenzhen Pengcheng Lab, Shenzhen, Peoples R China
[3] Inha Univ, Grad Sch Informat Technol & Telecommun, Incheon, South Korea
[4] Western Univ, Dept Elect & Comp Engn, London, ON, Canada
关键词
Mobile edge computing; small cell; energy efficiency; cooperative task offloading;
D O I
10.1109/WCNC51071.2022.9771874
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Cooperative task offloading has emerged as a compelling computing paradigm for balancing spatially uneven task workloads and computational resources in distributed mobile edge computing (MEC) systems. However, enabling cooperation among multiple MEC nodes inevitably requires extra communication and computational energy overheads which might counteract the cooperation gain without energy-efficient offloading mechanisms. This paper presents an adaptive cooperative task offloading algorithm aiming at maximizing the time-averaged energy efficiency for small cell MEC networks enabled by millimeter-wave backhauls. With the considered network dynamics, the proposed algorithm makes a good tradeoff between the harvested cooperation utility and the total energy consumption in the long term. In addition, our algorithm ensures the network stability and fulfills the task admission rate requirement of each individual user equipment, by making slot-based decisions over time without requiring a-priori knowledge of the network dynamics. Simulation results verify the outstanding performance of the proposed algorithm by comparing with the static cooperative and adaptive non-cooperative schemes.
引用
收藏
页码:292 / 297
页数:6
相关论文
共 50 条
  • [1] Energy-Efficient Task Offloading in Wireless-Powered MEC: A Dynamic and Cooperative Approach
    He, Huaiwen
    Zhou, Chenghao
    Huang, Feng
    Shen, Hong
    Li, Shuangjuan
    MATHEMATICS, 2024, 12 (15)
  • [2] Deep Reinforcement Learning for Energy-Efficient Task Offloading in Cooperative Vehicular Edge Networks
    Agbaje, Paul
    Nwafor, Ebelechukwu
    Olufowobi, Habeeb
    2023 IEEE 21ST INTERNATIONAL CONFERENCE ON INDUSTRIAL INFORMATICS, INDIN, 2023,
  • [3] An Energy-efficient Task Offloading Solution for MEC-based IoT in Ultra-dense Networks
    El Haber, Elie
    Tri Minh Nguyen
    Assi, Chadi
    Ajib, Wessam
    2019 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC), 2019,
  • [4] Energy-Efficient and Reliable MEC Offloading for Heterogeneous Industrial IoT Networks
    Hsu, Che-Wei
    Hsu, Yung-Lin
    Wei, Hung-Yu
    2019 EUROPEAN CONFERENCE ON NETWORKS AND COMMUNICATIONS (EUCNC), 2019, : 384 - 388
  • [5] Energy-Efficient Task Offloading for Semantic-Aware Networks
    Ji, Zelin
    Qin, Zhijin
    ICC 2023-IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS, 2023, : 3584 - 3589
  • [6] Distributed energy-efficient and secure offloading in air-to-ground MEC networks
    Liu, Wanning
    Xu, Yitao
    Wu, Ducheng
    Wang, Haichao
    Zheng, Xueqiang
    Chen, Xueqiang
    EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING, 2021, 2021 (01)
  • [7] Distributed energy-efficient and secure offloading in air-to-ground MEC networks
    Wanning Liu
    Yitao Xu
    Ducheng Wu
    Haichao Wang
    Xueqiang Zheng
    Xueqiang Chen
    EURASIP Journal on Advances in Signal Processing, 2021
  • [8] Energy-Efficient Task Offloading and Trajectory Design for UAV-based MEC Systems
    El-Emary, Mohamed
    Ranjha, Ali
    Naboulsi, Diala
    Stanica, Razvan
    2023 19TH INTERNATIONAL CONFERENCE ON WIRELESS AND MOBILE COMPUTING, NETWORKING AND COMMUNICATIONS, WIMOB, 2023, : 274 - 279
  • [9] Energy Efficient Computation Offloading for Multi-access MEC enabled Small Cell Networks
    Guo, Fengxian
    Zhang, Heli
    Ji, Hong
    Li, Xi
    Leung, Victor C. M.
    2018 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS WORKSHOPS (ICC WORKSHOPS), 2018,
  • [10] Cooperative partial task-offloading for heterogeneous industrial robotic MEC system using spectral and energy-efficient federated learning
    Pourghasemian, Mohsen
    Gacanin, Haris
    Perenda, Erma
    IEEE CONFERENCE ON GLOBAL COMMUNICATIONS, GLOBECOM, 2023, : 219 - 224