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
  • [41] Delay-Minimization Nonorthogonal Multiple Access Enabled Multi-User Mobile Edge Computation Offloading
    Wu, Yuan
    Qian, Li Ping
    Ni, Kejie
    Zhang, Cheng
    Shen, Xuemin
    IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, 2019, 13 (03) : 392 - 407
  • [42] Multi-User Computation Offloading as Multiple Knapsack Problem for 5G Mobile Edge Computing
    Ketyko, Istvan
    Kecskes, Laszlo
    Nemes, Csaba
    Farkas, Lorant
    2016 EUROPEAN CONFERENCE ON NETWORKS AND COMMUNICATIONS (EUCNC), 2016, : 225 - 229
  • [43] Learning-based Sustainable Multi-User Computation Offloading for Mobile Edge-Quantum Computing
    Xu, Minrui
    Niyato, Dusit
    Kang, Jiawen
    Xiong, Zehui
    Chen, Mingzhe
    ICC 2023-IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS, 2023, : 4045 - 4050
  • [44] Code Caching-Assisted Computation Offloading and Resource Allocation for Multi-User Mobile Edge Computing
    Chen, Zhixiong
    Zhou, Zhaokun
    Chen, Chen
    IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT, 2021, 18 (04): : 4517 - 4530
  • [45] Dependency-Aware and Latency-Optimal Computation Offloading for Multi-User Edge Computing Networks
    Shu, Chang
    Zhao, Zhiwei
    Han, Yunpeng
    Min, Geyong
    2019 16TH ANNUAL IEEE INTERNATIONAL CONFERENCE ON SENSING, COMMUNICATION, AND NETWORKING (SECON), 2019,
  • [46] Partial Computation Offloading for Double-RIS Assisted Multi-User Mobile Edge Computing Networks
    Li Bin
    Liu Wenshuai
    Xie Wancheng
    Ye Yinghui
    JOURNAL OF ELECTRONICS & INFORMATION TECHNOLOGY, 2022, 44 (07) : 2309 - 2316
  • [47] The partial computation offloading strategy based on game theory for multi-user in mobile edge computing environment
    Zhou, Shuchen
    Jadoon, Waqas
    COMPUTER NETWORKS, 2020, 178
  • [48] Computation offloading strategy for balanced-resource allocation in the multi-user mobile edge Computing environment
    Lu, Min
    Song, Yijie
    Yang, Xiaohui
    Yang, Zhongming
    Huang, Chunlan
    Yue, Guangxue
    Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS, 2024, 30 (11): : 4009 - 4020
  • [49] Poster Abstract: A Multi-User Computation Offloading Algorithm based on Game Theory in Mobile Cloud Computing
    Liu, Yujiong
    Wang, Shangguang
    Yang, Fangchun
    2016 FIRST IEEE/ACM SYMPOSIUM ON EDGE COMPUTING (SEC 2016), 2016, : 93 - 94
  • [50] Min-Max Worst-Case Design for Computation Offloading in Multi-user MEC System
    Zhang, Liping
    Chai, Rong
    Yang, Tiantian
    Chen, Qianbin
    IEEE INFOCOM 2020 - IEEE CONFERENCE ON COMPUTER COMMUNICATIONS WORKSHOPS (INFOCOM WKSHPS), 2020, : 1075 - 1080