Article

Free access

Link-level measurements from an 802.11b mesh network

Authors:

Robert MorrisAuthors Info & Claims

SIGCOMM '04: Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications

Pages 121 - 132

https://doi.org/10.1145/1015467.1015482

Published: 30 August 2004 Publication History

Abstract

This paper analyzes the causes of packet loss in a 38-node urban multi-hop 802.11b network. The patterns and causes of loss are important in the design of routing and error-correction protocols, as well as in network planning.The paper makes the following observations. The distribution of inter-node loss rates is relatively uniform over the whole range of loss rates; there is no clear threshold separating "in range" and "out of range." Most links have relatively stable loss rates from one second to the next, though a small minority have very bursty losses at that time scale. Signal-to-noise ratio and distance have little predictive value for loss rate. The large number of links with intermediate loss rates is probably due to multi-path fading rather than attenuation or interference.The phenomena discussed here are all well-known. The contributions of this paper are an understanding of their relative importance, of how they interact, and of the implications for MAC and routing protocol design.

References

[1]

ISL3873: Wireless LAN Integrated Medium Access Controller with Baseband Processor Inersil Corporation, 2000. Application Note FN4868.

[2]

D. W. Allan. Time and frequency (ime domain) characterization, estimation and prediction of precision clocks and oscillators. In IEEE Trans. UFFC, vol. 34, no. 6 November 1987.

[3]

H. Balakrishnan and R. Katz. Explicit loss notification and wireless web performance. In IEEE Globecom Internet Mini-Conference October 1998.

[4]

M. V. Clark, K. K. Leung, B. McNair, and Z. Kosic. Outdoor IEEE 802.11 cellular networks: Radio link performance. In Proc. of IEEE ICC 2002 April 2002.

[5]

D. C. Cox. Delay Doppler characteristics of multipath propagation a 910 MHz in a suburban mobile radio environment. In IEEE Transactions on Antennas and Propagation, AP-20 (5): 625--635 September 1972.

[6]

D. De Couto, D. Aguayo, J. Bicket, and R. Morris. A high-throughput path metric for multi-hop wireless routing. In Proceedings of ACM MobiCom Conference September 2003.

Digital Library

[7]

D. Eckhardt and P. Steenkiste. Measurement and analysis of the error characteristics of an in-building wireless network. In Computer Communication Review 26:4, pp. 243--254, SIGCOMM '96 October 1996.

Digital Library

[8]

G. Judd and P. Steenkiste. Repeatable and realistic wireless experimentation through physical emulation. In HotNets-II Cambridge, MA, November 2003. ACM.

[9]

A. Konrad, B. Y. Zhao, A. D. Joseph, and R. Ludwig. A Markov-based channel model algorithm for wireless networks. In Proceedings of Fourth ACM International Workshop on Modeling, Analysis and Simulation of Wireless and Mobile Systems 2001.

Digital Library

[10]

D. Kotz, C. Newport, and C. Elliot . The mistaken axioms of wireless-network research. Technical report TR2003-647, Dartmouth CS Department, July 2003.

[11]

H. Lundgren, E. Nordstrom, and C. Tschudin. Coping with communication gray zones in IEEE 802.11b based ad hoc networks. In ACM WoWMoM Workshop September 2002.

Digital Library

[12]

G. Nguyen, R. H. Katz, B. Noble, and M. Satyanarayanan. A race-based approach for modeling wireless channel behavior. In Proc. Winter Simulation Conf., December 1996.

Digital Library

[13]

E. S. Sousa, V. M. Jovanovic, and C. Daigneaul . Delay spread measurements for the digital cellular channel in Toronto. In IEEE Trans. on Veh. Tech., vol. 43, no. 4, pp. 1--11 November 1994.

[14]

A. Willig, M. Kubisch, C. Hoene, and A. Wolisz. Measurements of a wireless link in an industrial environment using an IEEE 802.11-compliant physical layer. In IEEE Transactions on Industrial Electronics, vol. 43, no. 6, pp. 1265--1282 December 2002.

[15]

M. Yarvis, W. Conner, L. Krishnamurthy, J. Chhabra, B. Elliott, and A. Mainwaring. Real-world experiences with an interactive ad hoc sensor network. In Proceedings of the International Workshop on Ad Hoc Networking Augus 2002.

Cited By

Silva ATavares DBachega S(2024)PROVA DE CONCEITO SOBRE A APLICAÇÃO DE OLSR EM SMARTPHONES ANDROIDREVISTA FOCO10.54751/revistafoco.v17n3-14817:3(e4749)Online publication date: 28-Mar-2024
https://doi.org/10.54751/revistafoco.v17n3-148
Zhu RZhu XZhang AZhang XSun JQian FQiu HMao ZLee MShu YLiu JTan RHe YChen J(2024)Boosting Collaborative Vehicular Perception on the Edge with Vehicle-to-Vehicle CommunicationProceedings of the 22nd ACM Conference on Embedded Networked Sensor Systems10.1145/3666025.3699328(141-154)Online publication date: 4-Nov-2024
https://dl.acm.org/doi/10.1145/3666025.3699328
Yang KLiu MDu W(2024)RALoRa: Rateless-Enabled Link Adaptation for LoRa NetworkingIEEE/ACM Transactions on Networking10.1109/TNET.2024.339234232:4(3392-3407)Online publication date: Aug-2024
https://doi.org/10.1109/TNET.2024.3392342
Show More Cited By

Index Terms

Link-level measurements from an 802.11b mesh network
1. Networks
  1. Network types
    1. Mobile networks
    2. Wireless access networks

Recommendations

Link-level measurements from an 802.11b mesh network

This paper analyzes the causes of packet loss in a 38-node urban multi-hop 802.11b network. The patterns and causes of loss are important in the design of routing and error-correction protocols, as well as in network planning.The paper makes the ...
Evaluation of a LoRa mesh wireless networking system supporting time-critical transmission and data lost recovery: poster abstract
IPSN '19: Proceedings of the 18th International Conference on Information Processing in Sensor Networks

This paper evaluates a LoRa mesh networking system for large-area monitoring of sensor applications. A prior study [1] proposed a LoRa-based wireless mesh network that supported periodic data collection. In this study, we further evaluated how data ...
A link performance model for multi-user wireless fading channels
QShine '06: Proceedings of the 3rd international conference on Quality of service in heterogeneous wired/wireless networks

The two-state Markov chain has been widely used to model fading channels in the performance study of upper-layer communication protocols in wireless networks. It can be used to model transmission success/failure based on the physical characteristics of ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

SIGCOMM '04: Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications

August 2004

402 pages

ISBN:1581138628

DOI:10.1145/1015467

General Chair:
Raj Yavatkar
Intel Corporation
,
Program Chairs:
Ellen Zegura
Georgia Institute of Technology
,
Jennifer Rexford
AT&T Labs -- Research

ACM SIGCOMM Computer Communication Review Volume 34, Issue 4
October 2004
385 pages
ISSN:0146-4833
DOI:10.1145/1030194
Issue’s Table of Contents

Copyright © 2004 ACM.

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]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 30 August 2004

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Article

Conference

SIGCOMM04

Sponsor:

SIGCOMM04: ACM SIGCOMM 2004 Conference

August 30 - September 3, 2004

Oregon, Portland, USA

Acceptance Rates

Overall Acceptance Rate 462 of 3,389 submissions, 14%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

818
Total Citations
View Citations
3,913
Total Downloads

Downloads (Last 12 months)155
Downloads (Last 6 weeks)15

Reflects downloads up to 23 Dec 2024

Other Metrics

View Author Metrics

Citations

Cited By

Silva ATavares DBachega S(2024)PROVA DE CONCEITO SOBRE A APLICAÇÃO DE OLSR EM SMARTPHONES ANDROIDREVISTA FOCO10.54751/revistafoco.v17n3-14817:3(e4749)Online publication date: 28-Mar-2024
https://doi.org/10.54751/revistafoco.v17n3-148
Zhu RZhu XZhang AZhang XSun JQian FQiu HMao ZLee MShu YLiu JTan RHe YChen J(2024)Boosting Collaborative Vehicular Perception on the Edge with Vehicle-to-Vehicle CommunicationProceedings of the 22nd ACM Conference on Embedded Networked Sensor Systems10.1145/3666025.3699328(141-154)Online publication date: 4-Nov-2024
https://dl.acm.org/doi/10.1145/3666025.3699328
Yang KLiu MDu W(2024)RALoRa: Rateless-Enabled Link Adaptation for LoRa NetworkingIEEE/ACM Transactions on Networking10.1109/TNET.2024.339234232:4(3392-3407)Online publication date: Aug-2024
https://doi.org/10.1109/TNET.2024.3392342
Zhang XChiu CHe T(2024)Energy-Efficient Decentralized Learning Via Graph SparsificationICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)10.1109/ICASSP48485.2024.10445868(13026-13030)Online publication date: 14-Apr-2024
https://doi.org/10.1109/ICASSP48485.2024.10445868
Chiu CZhang XHe TWang SSwami A(2023)Laplacian Matrix Sampling for Communication- Efficient Decentralized LearningIEEE Journal on Selected Areas in Communications10.1109/JSAC.2023.324273541:4(887-901)Online publication date: Apr-2023
https://doi.org/10.1109/JSAC.2023.3242735
Zhang LLiew S(2023)Reliable Wireless Networking via Soft-Source Information CombiningIEEE Internet of Things Journal10.1109/JIOT.2022.321998010:6(4970-4984)Online publication date: 15-Mar-2023
https://doi.org/10.1109/JIOT.2022.3219980
Arrabal TStojanova MGuérin Lassous IPicot J(2023)Experiment-driven platform for link quality estimation in IEEE 802.11 WLANs2023 IEEE 24th International Conference on High Performance Switching and Routing (HPSR)10.1109/HPSR57248.2023.10148011(134-139)Online publication date: 5-Jun-2023
https://doi.org/10.1109/HPSR57248.2023.10148011
Lei X(2022)Online Bayesian Learning for Rate Adaptation in Non-stationary Wireless Channels2022 19th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON)10.1109/SECON55815.2022.9918166(55-63)Online publication date: 20-Sep-2022
https://dl.acm.org/doi/10.1109/SECON55815.2022.9918166
Horita KYang BCarette TJimbo MNakao A(2022)Optimal Network Selection Method Using Federated Learning to Achieve Large-Scale Learning While Preserving Privacy2022 IEEE 11th International Conference on Cloud Networking (CloudNet)10.1109/CloudNet55617.2022.9978891(220-228)Online publication date: 7-Nov-2022
https://doi.org/10.1109/CloudNet55617.2022.9978891
Grohmann AGabriel FZimmermann SFitzek F(2020)SourceShift: Resilient Routing in Highly Dynamic Wireless Mesh Networks2020 IEEE Wireless Communications and Networking Conference (WCNC)10.1109/WCNC45663.2020.9120818(1-8)Online publication date: May-2020
https://doi.org/10.1109/WCNC45663.2020.9120818
Show More Cited By

View Options

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

Media

Figures

Other

Tables

View Table of Contents