Dynamic Admission Control and Resource Allocation for Mobile Edge Computing Enabled Small Cell Network

被引:57
|
作者
Huang, Jiwei [1 ]
Lv, Bofeng [1 ]
Wu, Yuan [2 ,3 ]
Chen, Ying [4 ]
Shen, Xuemin [5 ]
机构
[1] China Univ Petr, Beijing Key Lab Petr Data Min, Beijing 102249, Peoples R China
[2] Univ Macau, State Key Lab Internet Things Smart City, Macau 999078, Peoples R China
[3] Univ Macau, Dept Comp & Informat Sci, Macau 999078, Peoples R China
[4] Beijing Informat Sci & Technol Univ, Comp Sch, Beijing 100101, Peoples R China
[5] Univ Waterloo, Dept Elect & Comp Engn, Waterloo, ON N2L 3G1, Canada
基金
北京市自然科学基金; 中国国家自然科学基金;
关键词
Task analysis; Servers; Admission control; Resource management; Throughput; Vehicle dynamics; Stochastic processes; MEC; small cell networks; admission control; resource allocation; OPTIMIZATION; MANAGEMENT; RADIO;
D O I
10.1109/TVT.2021.3133696
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Mobile edge computing (MEC) has recently risen as a promising paradigm to meet the increasing resource requirements of the terminal devices. Meanwhile, small cell network (SCN) with MEC has been emerging to handle the exponentially increasing data traffic and improve the network coverage, and is recognized as one key component of the next generation wireless networks. However, with the growing number of terminal devices requiring computation offloading to the edge servers, the network would be heavily congested and thus the performance would be degraded and unbalanced among multiple devices. In this paper, we propose the joint admission control and computation resource allocation in the MEC enabled SCN, and formulate it as a stochastic optimization problem. The goal is to maximize the system utility combining the throughput and fairness while bounding the queue. We decouple the original problem into three independent subproblems, which can be solved in a distributed manner without requiring the system statistical information. An admission control and computation resource allocation (ACCRA) algorithm is designed to obtain the optimal solutions of the subproblems. Theoretical analysis proves that the ACCRA algorithm can achieve the close-to-optimal system utility and reach the arbitrary tradeoff between the utility and the queue length. Experiments are conducted to validate the derived analytical results and evaluate the performance of the ACCRA algorithm.
引用
收藏
页码:1964 / 1973
页数:10
相关论文
共 50 条
  • [41] Multiple Energy Harvesting Devices Enabled Joint Computation Offloading and Dynamic Resource Allocation for Mobile-Edge Computing Systems
    Du, Wei
    Lei, Qiwang
    He, Qiang
    Liu, Wei
    Chen, Feifei
    Pan, Lei
    Lei, Tao
    Zhao, Hailiang
    2019 IEEE INTERNATIONAL CONFERENCE ON WEB SERVICES (IEEE ICWS 2019), 2019, : 154 - 158
  • [42] A Robust Optimization Approach for Resource Allocation in Edge Computing-enabled NetworksA Robust Optimization Approach for Resource Allocation in Edge Computing-enabled Networks
    Cheng, Yuxia
    Liang, Chengchao
    Chen, Qianbin
    Yu, F. Richard
    2024 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE, WCNC 2024, 2024,
  • [43] Multi-Agent Reinforcement Learning for Distributed Resource Allocation in Cell-Free Massive MIMO-Enabled Mobile Edge Computing Network
    Tilahun, Fitsum Debebe
    Abebe, Ameha Tsegaye
    Kang, Chung G.
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2023, 72 (12) : 16454 - 16468
  • [44] Collaborative computation offloading and resource allocation based on dynamic pricing in mobile edge computing
    Xue, Jianbin
    Guan, Xiangrui
    COMPUTER COMMUNICATIONS, 2023, 198 : 52 - 62
  • [45] UAV-Assisted Mobile Edge Computing: Dynamic Trajectory Design and Resource Allocation
    Wang, Zhuwei
    Zhao, Wenjing
    Hu, Pengyu
    Zhang, Xige
    Liu, Lihan
    Fang, Chao
    Sun, Yanhua
    SENSORS, 2024, 24 (12)
  • [46] Dynamic Computation Offloading and Resource Allocation for Multi-user Mobile Edge Computing
    Nath, Samrat
    Wu, Jingxian
    2020 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), 2020,
  • [47] Optimal Resource Allocation for Wireless Powered Mobile Edge Computing with Dynamic Task Arrivals
    Wang, Feng
    Xing, Hong
    Xu, Jie
    ICC 2019 - 2019 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC), 2019,
  • [48] Dynamic Resource Allocation for URLLC in UAV-Enabled Multi-access Edge Computing
    Falcao, Marcos
    Souza, Caio
    Balieiro, Andson
    Dias, Kelvin
    2023 JOINT EUROPEAN CONFERENCE ON NETWORKS AND COMMUNICATIONS & 6G SUMMIT, EUCNC/6G SUMMIT, 2023, : 293 - 298
  • [49] Resource allocation and trust computing for blockchain-enabled edge computing system
    Zhang, Lejun
    Zou, Yanfei
    Wang, Weizheng
    Jin, Zilong
    Su, Yansen
    Chen, Huiling
    COMPUTERS & SECURITY, 2021, 105
  • [50] Joint Load Management and Resource Allocation in the Energy Harvesting Powered Small Cell Networks with Mobile Edge Computing
    Guo, Fengxian
    Ma, Liangde
    Zhang, Heli
    Ji, Hong
    Li, Xi
    IEEE INFOCOM 2018 - IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (INFOCOM WKSHPS), 2018, : 299 - 304