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An empirical analysis of the IEEE 802.11 MAC layer handoff process

Authors:

Arunesh Mishra,

William ArbaughAuthors Info & Claims

ACM SIGCOMM Computer Communication Review, Volume 33, Issue 2

Pages 93 - 102

https://doi.org/10.1145/956981.956990

Published: 01 April 2003 Publication History

Abstract

IEEE 802.11 based wireless networks have seen rapid growth and deployment in the recent years. Critical to the 802.11 MAC operation, is the handoff function which occurs when a mobile node moves its association from one access point to another. In this paper, we present an empirical study of this handoff process at the link layer, with a detailed breakup of the latency into various components. In particular, we show that a MAC layer function - probe is the primary contributor to the overall handoff latency. In our study, we observe that the latency is significant enough to affect the quality of service for many applications (or network connections). Further we find variations in the latency from one hand-off to another as well as with APs and STAs used from different vendors. Finally, we discuss optimizations on the probe phase which can potentially reduce the probe latency by as much as 98% (and a minimum of 12% in our experiments). Based on the study, we draw some guidelines for future handoff schemes.

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Published In

cover image ACM SIGCOMM Computer Communication Review

ACM SIGCOMM Computer Communication Review Volume 33, Issue 2

April 2003

98 pages

ISSN:0146-4833

DOI:10.1145/956981

Issue’s Table of Contents

Copyright © 2003 Authors.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 April 2003

Published in SIGCOMM-CCR Volume 33, Issue 2

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Cited By

Mohanti SRoy DEisen MCavalcanti DChowdhury K(2024)L-NORM: Learning and Network Orchestration at the Edge for Robot Connectivity and Mobility in Factory Floor EnvironmentsIEEE Transactions on Mobile Computing10.1109/TMC.2023.326664323:4(2898-2914)Online publication date: 1-Apr-2024
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Wang TShen LFeng K(2024)Distributed Multi-Agent Deep Q-Learning for Fast Roaming in IEEE 802.11ax Wi-Fi Systems2024 IEEE 21st Consumer Communications & Networking Conference (CCNC)10.1109/CCNC51664.2024.10454741(433-438)Online publication date: 6-Jan-2024
https://doi.org/10.1109/CCNC51664.2024.10454741
Lv PHe HXu J(2024)ASAPVehicular Communications10.1016/j.vehcom.2024.10082849:COnline publication date: 1-Oct-2024
https://dl.acm.org/doi/10.1016/j.vehcom.2024.100828
Shao SZheng JZhong CLu PGuo SBu X(2023)IEEE 802.11ax Meet Edge Computing: AP Seamless Handover for Multi-Service Communications in Industrial WLANIEEE Transactions on Network and Service Management10.1109/TNSM.2023.323940420:3(3396-3412)Online publication date: 1-Sep-2023
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Pradeepthi KUngati S(2023)Improving Vehicular Handover Time Using Make Before Break Mechanism2023 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)10.1109/ANTS59832.2023.10468749(1-6)Online publication date: 17-Dec-2023
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Cervantes-Bazán JCuevas-Rasgado ARojas-Cárdenas LLazcano-Salas SGarcía-Lamont FSoriano LRubio JPacheco J(2022)Proactive Cross-Layer Framework Based on Classification Techniques for Handover Decision on WLAN EnvironmentsElectronics10.3390/electronics1105071211:5(712)Online publication date: 25-Feb-2022
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Quey LJu HFang XLong YHe RHuang L(2022)Could IEEE 802.11bc Enhance Data Broadcast Performance for Moving Station: A Frame Loss Perspective2022 IEEE 95th Vehicular Technology Conference: (VTC2022-Spring)10.1109/VTC2022-Spring54318.2022.9860960(1-6)Online publication date: Jun-2022
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Balbi HPassos DVieira JCarrano RMagalhães LAlbuquerque C(2022)Towards a fast and stable filter for RSSI-based handoff algorithms in dense indoor WLANsComputer Communications10.1016/j.comcom.2021.10.024183:C(19-32)Online publication date: 1-Feb-2022
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