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Estimating the Transmission Probability in Wireless Networks with Configuration Models

Published: 21 April 2016 Publication History

Abstract

We propose a new methodology to estimate the probability of successful transmissions for random access scheduling in wireless networks, in particular those using Carrier Sense Multiple Access (CSMA). Instead of focusing on spatial configurations of users, we model the interference between users as a random graph. Using configuration models for random graphs, we show how the properties of the medium access mechanism are captured by some deterministic differential equations when the size of the graph gets large. Performance indicators such as the probability of connection of a given node can then be efficiently computed from these equations. We also perform simulations to illustrate the results on different types of random graphs. Even on spatial structures, these estimates get very accurate as soon as the variance of the interference is not negligible.

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Cited By

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  • (2022)Markovian Online Matching Algorithms on Large Bipartite Random GraphsMethodology and Computing in Applied Probability10.1007/s11009-022-09973-y24:4(3195-3225)Online publication date: 1-Dec-2022
  • (2020)QoS Provision in a Dynamic Channel Allocation Based on Admission Control DecisionsACM Transactions on Modeling and Performance Evaluation of Computing Systems10.1145/33727865:1(1-29)Online publication date: 4-Feb-2020
  • (2019)Control de Acceso al Medio basado en Entropía para S-ALOHA en Redes Inalámbricas Ad-HocRevista Iberoamericana de Automática e Informática industrial10.4995/riai.2018.1039816:2(178)Online publication date: 20-Mar-2019
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Published In

cover image ACM Transactions on Modeling and Performance Evaluation of Computing Systems
ACM Transactions on Modeling and Performance Evaluation of Computing Systems  Volume 1, Issue 2
June 2016
112 pages
ISSN:2376-3639
EISSN:2376-3647
DOI:10.1145/2928293
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 April 2016
Accepted: 01 December 2015
Revised: 01 October 2015
Received: 01 November 2014
Published in TOMPECS Volume 1, Issue 2

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Author Tags

  1. Wireless networks
  2. medium access probability
  3. parking process
  4. random graphs

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Cited By

View all
  • (2022)Markovian Online Matching Algorithms on Large Bipartite Random GraphsMethodology and Computing in Applied Probability10.1007/s11009-022-09973-y24:4(3195-3225)Online publication date: 1-Dec-2022
  • (2020)QoS Provision in a Dynamic Channel Allocation Based on Admission Control DecisionsACM Transactions on Modeling and Performance Evaluation of Computing Systems10.1145/33727865:1(1-29)Online publication date: 4-Feb-2020
  • (2019)Control de Acceso al Medio basado en Entropía para S-ALOHA en Redes Inalámbricas Ad-HocRevista Iberoamericana de Automática e Informática industrial10.4995/riai.2018.1039816:2(178)Online publication date: 20-Mar-2019
  • (2017)Estimating the medium access probability in large cognitive radio networksAd Hoc Networks10.1016/j.adhoc.2017.05.00363(1-13)Online publication date: Aug-2017
  • (2017)Scaling Limits and Generic Bounds for Exploration ProcessesJournal of Statistical Physics10.1007/s10955-017-1902-z169:5(989-1018)Online publication date: 27-Oct-2017

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