Article

The worst-case capacity of wireless sensor networks

Author:

Thomas MoscibrodaAuthors Info & Claims

IPSN '07: Proceedings of the 6th international conference on Information processing in sensor networks

Pages 1 - 10

https://doi.org/10.1145/1236360.1236362

Published: 25 April 2007 Publication History

Abstract

The key application scenario of wireless sensor networks is data gathering sensor nodes transmit data, possibly in a multi-hop fashion, to an information sink. The performance of sensor networks is thus characterized by the rate at which information can be aggregated to the sink. In this paper, we derive the first scaling laws describing the achievable rate in worst-case i.e.arbitrarily deployed,sensor networks. We show that in the physical model of wireless communication and for a large number of practically important functions, a sustainable rate of Ω(1 / log² n) can be achieved in every network even when nodes are positioned in a worst-case manner. In contrast, we show that the best possible rate in the protocol model is Θ(1 /n), which establishes an exponential gap between these two standard models of wireless communication. Furthermore, our worst-case capacity result almost matches the rate of Θ(1 / log n) that can be achieved in randomly deployed networks. The high rate is made possible by employing non-linear power assignment at nodes and by exploiting SINR-effects. Finally,our algorithm also improves the best known bounds on the scheduling complexity in wireless networks.

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Cited By

Halldórsson MKortsarz GMitra PTonoyan T(2021)Network Design under General Wireless InterferenceAlgorithmica10.1007/s00453-021-00866-zOnline publication date: 10-Aug-2021
https://doi.org/10.1007/s00453-021-00866-z
Halldórsson MWattenhofer R(2019)Wireless Network AlgorithmicsComputing and Software Science10.1007/978-3-319-91908-9_9(141-160)Online publication date: 2019
https://doi.org/10.1007/978-3-319-91908-9_9
Avin CLotker ZPignolet Y(2017)On the power of uniform powerWireless Networks10.1007/s11276-016-1282-323:8(2319-2333)Online publication date: 1-Nov-2017
https://dl.acm.org/doi/10.1007/s11276-016-1282-3
Show More Cited By

Index Terms

The worst-case capacity of wireless sensor networks
1. Networks
  1. Network types
    1. Mobile networks
    2. Wireless access networks

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cover image ACM Conferences

IPSN '07: Proceedings of the 6th international conference on Information processing in sensor networks

April 2007

592 pages

ISBN:9781595936387

DOI:10.1145/1236360

General Chair:
Tarek Abdelzaher
University of Illinois at Urbana-Champaign
,
Program Chairs:
Leo Guibas
Stanford University
,
Matt Welsh
Harvard University

Copyright © 2007 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]

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Publication History

Published: 25 April 2007

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IPSN07: The 6th International Conference on Information Processing in Sensor Networks

April 25 - 27, 2007

Massachusetts, Cambridge, USA

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Overall Acceptance Rate 143 of 593 submissions, 24%

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Cited By

Halldórsson MKortsarz GMitra PTonoyan T(2021)Network Design under General Wireless InterferenceAlgorithmica10.1007/s00453-021-00866-zOnline publication date: 10-Aug-2021
https://doi.org/10.1007/s00453-021-00866-z
Halldórsson MWattenhofer R(2019)Wireless Network AlgorithmicsComputing and Software Science10.1007/978-3-319-91908-9_9(141-160)Online publication date: 2019
https://doi.org/10.1007/978-3-319-91908-9_9
Avin CLotker ZPignolet Y(2017)On the power of uniform powerWireless Networks10.1007/s11276-016-1282-323:8(2319-2333)Online publication date: 1-Nov-2017
https://dl.acm.org/doi/10.1007/s11276-016-1282-3
Kantor ELotker ZParter MPeleg D(2015)The Topology of Wireless CommunicationJournal of the ACM10.1145/280769362:5(1-32)Online publication date: 2-Nov-2015
https://dl.acm.org/doi/10.1145/2807693
Parter MPeleg D(2015)On the Relations Between SINR Diagrams and Voronoi DiagramsProceedings of the 14th International Conference on Ad-hoc, Mobile, and Wireless Networks - Volume 914310.1007/978-3-319-19662-6_16(225-237)Online publication date: 29-Jun-2015
https://dl.acm.org/doi/10.1007/978-3-319-19662-6_16
N P(2014)EFFICIENT AND FAST INFORMATION GATHERING IN SENSOR NETWORK ORGANISED AS A TREEInternational Journal of Research -GRANTHAALAYAH10.29121/granthaalayah.v1.i1.2014.30841:1(35-42)Online publication date: 31-Aug-2014
https://doi.org/10.29121/granthaalayah.v1.i1.2014.3084
da Silva MSenne EVijaykumar N(2014)Optimization methods applied to nonlinear signal interference modelsEngineering Optimization 201410.1201/b17488-121(681-686)Online publication date: 7-Oct-2014
https://doi.org/10.1201/b17488-121
Newport CHalldórsson MDolev S(2014)Consensus with an abstract MAC layerProceedings of the 2014 ACM symposium on Principles of distributed computing10.1145/2611462.2611479(66-75)Online publication date: 15-Jul-2014
https://dl.acm.org/doi/10.1145/2611462.2611479
Goussevskaia OHalldórsson MWattenhofer R(2014)Algorithms for wireless capacityIEEE/ACM Transactions on Networking10.1109/TNET.2013.225803622:3(745-755)Online publication date: 1-Jun-2014
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Ji SBeyah RCai Z(2014)Snapshot and Continuous Data Collection in Probabilistic Wireless Sensor NetworksIEEE Transactions on Mobile Computing10.1109/TMC.2013.3013:3(626-637)Online publication date: 1-Mar-2014
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