On Multi-User Binary Computation Offloading in the Finite-Block-Length Regime

被引:0
|
作者
Salmani, Mahsa [1 ]
Davidson, Timothy N. [1 ]
机构
[1] McMaster Univ, Dept Elect & Comp Engn, Hamilton, ON, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
MOBILE; OPTIMIZATION; COMMUNICATION; RADIO;
D O I
10.1109/ieeeconf44664.2019.9048917
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The Mobile Edge Computing framework provides small scale devices with the opportunity to offload their computational tasks to computing infrastructure at a network access point. Effective access to this infrastructure is contingent on the appropriate allocation of the available communication resources among the devices wishing to offload their tasks. In previous work, that allocation has been performed using guidance from classical characterizations of the fundamental limits on the rates at which reliable communication can be achieved, which are contingent on asymptotically long communication block lengths. However, the (latency) constraint on the time by which each device expects the results of its offloaded computational task imposes a natural limit on the block length. In this paper we show how a recent characterization of the rate limits in the finite-block-length regime can be incorporated into the problem of communication resource allocation for a K-device binary computational offloading system that employs the time-division multiple access (TDMA) scheme. We develop an efficient algorithm for that problem that is based on a tailored tree-search algorithm for the binary offloading decisions, a successive convex approximation algorithm for the transmission rates of the users, and closed-form solutions for the transmission powers and durations.
引用
收藏
页码:378 / 382
页数:5
相关论文
共 50 条
  • [21] Optimal Channel Sharing assisted Multi-user Computation Offloading via NOMA
    Wang, Tianshun
    Li, Yang
    Wu, Yuan
    Qian, Liping
    Bin, Lin
    Jia, Weijia
    IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (IEEE INFOCOM WKSHPS 2021), 2021,
  • [22] Optimal Multi-User Computation Offloading Strategy for Wireless Powered Sensor Networks
    Wang, Luhan
    Shao, Hua
    Li, Jingjing
    Wen, Xiangming
    Lu, Zhaoming
    IEEE ACCESS, 2020, 8 : 55150 - 55160
  • [23] Secure Computation Offloading for Multi-user Multi-server MEC-enabled IoT
    Xu, Jun
    Zhu, Pengcheng
    Li, Jiamin
    You, Xiaohu
    IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC 2021), 2021,
  • [24] Multi-user Multi-channel Computation Offloading and Resource Allocation for Mobile Edge Computing
    Nath, Samrat
    Li, Yaze
    Wu, Jingxian
    Fan, Pingzhi
    ICC 2020 - 2020 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC), 2020,
  • [25] Multi-User Multi-Task Computation Offloading in Green Mobile Edge Cloud Computing
    Chen, Weiwei
    Wang, Dong
    Li, Keqin
    IEEE TRANSACTIONS ON SERVICES COMPUTING, 2019, 12 (05) : 726 - 738
  • [26] Finite-block-length analysis in classical and quantum information theory
    Hayashi, Masahito
    PROCEEDINGS OF THE JAPAN ACADEMY SERIES B-PHYSICAL AND BIOLOGICAL SCIENCES, 2017, 93 (03): : 99 - 124
  • [27] Multi-User Computation Offloading with D2D for Mobile Edge Computing
    Hu, Guisheng
    Jia, Yunjian
    Chen, Zhengchuan
    2018 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM), 2018,
  • [28] Game Theoretical Multi-User Computation Offloading for Mobile-Edge Cloud Computing
    Qin, An
    Cai, Chengcheng
    Wang, Qin
    Ni, Yiyang
    Zhu, Hongbo
    2019 2ND IEEE CONFERENCE ON MULTIMEDIA INFORMATION PROCESSING AND RETRIEVAL (MIPR 2019), 2019, : 328 - 332
  • [29] A Multi-user Computation Offloading Optimization Model and Algorithm Based on Deep Reinforcement Learning
    Li Z.
    Yu Z.
    Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology, 2024, 46 (04): : 1321 - 1332
  • [30] A quick-response framework for multi-user computation offloading in mobile cloud computing
    Kuang, Zhikai
    Guo, Songtao
    Liu, Jiadi
    Yang, Yuanyuan
    FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2018, 81 : 166 - 176