Deterministic non-adaptive contention resolution on a shared channel

被引:0
|
作者
De Marco, Gianluca [1 ]
Kowalski, Dariusz R. [3 ]
Stachowiak, Grzegorz [2 ]
机构
[1] Univ Salerno, Dipartimento Informat, Fisciano, Italy
[2] Univ Wroclaw, Inst Comp Sci, Wroclaw, Poland
[3] Augusta Univ, Sch Comp & Cyber Sci, Augusta, GA USA
基金
美国国家科学基金会;
关键词
Multiple -access channel; Contention resolution; Deterministic algorithm; Lower bound; DISTRIBUTED BROADCAST; CONFLICT-RESOLUTION; WAKE-UP; MULTIPLE; ALGORITHM;
D O I
10.1016/j.jcss.2022.11.001
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
In a multiple access channel, autonomous stations are able to transmit and listen to a shared device. A fundamental problem, called contention resolution, is to allow any station to successfully deliver its message by resolving the conflicts that arise when several stations transmit simultaneously. Despite a long history on such a problem, most of the results deal with the static setting when all stations start simultaneously, while many fundamental questions remain open in the realistic scenario when stations can join the channel at arbitrary times. In this paper, we explore the impact that three major channel features (asynchrony among stations, knowledge of the number of contenders and possibility of switching off stations after a successful transmission) can have on the time complexity of non-adaptive deterministic algorithms. We establish upper and lower bounds allowing to understand which parameters permit time-efficient contention resolution and which do not.(c) 2022 Elsevier Inc. All rights reserved.
引用
收藏
页码:1 / 22
页数:22
相关论文
共 50 条
  • [1] Deterministic contention resolution on a shared channel
    De Marco, Gianluca
    Kowalski, Dariusz R.
    Stachowiak, Grzegorz
    2019 39TH IEEE INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING SYSTEMS (ICDCS 2019), 2019, : 472 - 482
  • [2] Scalable and Efficient Non-adaptive Deterministic Group Testing
    Kowalski, Dariusz R.
    Pajak, Dominik
    ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 35 (NEURIPS 2022), 2022,
  • [3] Comparison of Monte Carlo and deterministic methods for non-adaptive optimization
    Al-Mharmah, HA
    Calvin, JM
    PROCEEDINGS OF THE 1997 WINTER SIMULATION CONFERENCE, 1997, : 348 - 351
  • [4] ADAPTIVE AND NON-ADAPTIVE MODEL PREDICTIVE CONTROL OF AN IRRIGATION CHANNEL
    Lemos, Joao M.
    Machado, Fernando
    Nogueira, Nuno
    Rato, Luis
    Rijo, Manuel
    NETWORKS AND HETEROGENEOUS MEDIA, 2009, 4 (02) : 303 - 324
  • [5] Resolution Limits for the Noisy Non-Adaptive 20 Questions Problem
    Zhou, Lin
    Hero, Alfred O., III
    IEEE TRANSACTIONS ON INFORMATION THEORY, 2021, 67 (04) : 2055 - 2073
  • [6] Asymptotic Separation Between Adaptive and Non-adaptive Strategies in Quantum Channel Discrimination
    Salek, Farzin
    Hayashi, Masahito
    Winter, Andreas
    2021 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY (ISIT), 2021, : 1194 - 1199
  • [7] NON-ADAPTIVE CHARACTERS
    FORD, EB
    NATURE, 1949, 164 (4177) : 882 - 882
  • [8] Contention resolution in a non-synchronized multiple access channel
    De Marco, Gianluca
    Kowalski, Dariusz R.
    THEORETICAL COMPUTER SCIENCE, 2017, 689 : 1 - 13
  • [9] NON-ADAPTIVE CHARACTERS
    CANNON, HG
    NATURE, 1950, 165 (4197) : 575 - 575
  • [10] Contention Resolution in a Non-Synchronized Multiple Access Channel
    De Marco, Gianluca
    Kowalski, Dariusz R.
    IEEE 27TH INTERNATIONAL PARALLEL AND DISTRIBUTED PROCESSING SYMPOSIUM (IPDPS 2013), 2013, : 525 - 533