research-article

Sparse Backbone and Optimal Distributed SINR Algorithms

Authors:

Magnús M. Halldórsson,

Tigran TonoyanAuthors Info & Claims

ACM Transactions on Algorithms (TALG), Volume 17, Issue 2

Article No.: 17, Pages 1 - 34

https://doi.org/10.1145/3452937

Published: 06 June 2021 Publication History

Abstract

We develop randomized distributed algorithms for many of the most fundamental communication problems in wireless networks under the Signal to Interference and Noise Ratio (SINR) model of communication, including (multi-message) broadcast, local broadcast, coloring, Maximal Independent Set, and aggregation. The complexity of our algorithms is optimal up to polylogarithmic preprocessing time. It shows—contrary to expectation—that the plain vanilla SINR model is just as powerful and fast (modulo the preprocessing) as various extensions studied, including power control, carrier sense, collision detection, free acknowledgements, and geolocation knowledge. Central to these results is an efficient construction of a constant-density backbone structure over the network, which is of independent interest. This is achieved using an indirect sensing technique, where message non-reception is used to deduce information about relative node-distances.

References

[1]

Noga Alon, Amotz Bar-Noy, Nathan Linial, and David Peleg. 1991. A lower bound for radio broadcast. J. Comput. Syst. Sci. 43, 2 (1991), 290–298.

Digital Library

[2]

Leonid Barenboim and David Peleg. 2015. Nearly optimal local broadcasting in the SINR model with feedback. In Proceedings of the 22nd International Colloquium on Structural Information and Communication Complexity (SIROCCO’15), Christian Scheideler (Ed.), Lecture Notes in Computer Science, Vol. 9439. Springer, 164–178.

[3]

Marijke H. L. Bodlaender, Magnús M. Halldórsson, and Pradipta Mitra. 2013. Connectivity and aggregation in multihop wireless networks. In Proceedings of the ACM Symposium on Principles of Distributed Computing (PODC’13), Panagiota Fatourou and Gadi Taubenfeld (Eds.). ACM, 355–364.

Digital Library

[4]

Keren Censor-Hillel, Bernhard Haeupler, D. Ellis Hershkowitz, and Goran Zuzic. 2019. Erasure correction for noisy radio networks. In Proceedings of the 33rd International Symposium on Distributed Computing (DISC’19), Jukka Suomela (Ed.), LIPIcs,Vol. 146. Schloss Dagstuhl, Leibniz-Zentrum für Informatik, 10:1–10:17.

[5]

Imrich Chlamtac and Shay Kutten. 1985. On broadcasting in radio networks-problem analysis and protocol design. IEEE Trans. Commun. 33, 12 (1985), 1240–1246.

[6]

Bogdan S. Chlebus and Shailesh Vaya. 2016. Distributed communication in bare-bones wireless networks. In Proceedings of the 17th International Conference on Distributed Computing and Networking. ACM, 1:1–1:10.

[7]

Sebastian Daum, Seth Gilbert, Fabian Kuhn, and Calvin C. Newport. 2013. Broadcast in the ad hoc SINR model. In Proceedings of the 27th International Symposium on Distributed Computing (DISC’13), Yehuda Afek (Ed.), Lecture Notes in Computer Science,Vol. 8205. Springer, 358–372.

[8]

Bilel Derbel and El-Ghazali Talbi. 2010. Radio network distributed algorithms in the unknown neighborhood model. In Proceedings of the 11th International Conference on Distributed Computing and Networking (ICDCN’10), Krishna Kant, Sriram V. Pemmaraju, Krishna M. Sivalingam, and Jie Wu (Eds.), Lecture Notes in Computer Science, Vol. 5935. Springer, 155–166.

[9]

Benjamin Doerr. 2020. Probabilistic Tools for the Analysis of Randomized Optimization Heuristics. Springer International Publishing, Cham, 1–87.

[10]

Jeremy T. Fineman, Seth Gilbert, Fabian Kuhn, and Calvin Newport. 2019. Contention resolution on a fading channel. Distrib. Comput. 32, 6 (2019), 517–533.

[11]

Fabian Fuchs and Roman Prutkin. 2015. Simple distributed Δ + 1 Coloring in the SINR Model. In Proceedings of the 22nd International Colloquium on Structural Information and Communication Complexity (SIROCCO’15), Christian Scheideler (Ed.), Lecture Notes in Computer Science, Vol. 9439. Springer, 149–163.

[12]

Mohsen Ghaffari, Bernhard Haeupler, and Majid Khabbazian. 2015. Randomized broadcast in radio networks with collision detection. Distrib. Comput. 28, 6 (2015), 407–422.

Digital Library

[13]

Mohsen Ghaffari, Bernhard Haeupler, Nancy A. Lynch, and Calvin C. Newport. 2012. Bounds on contention management in radio networks. In Proceedings of the 26th International Symposium on Distributed Computing (DISC’12), Marcos K. Aguilera (Ed.), Lecture Notes in Computer Science,Vol. 7611. Springer, 223–237.

[14]

Wayne Goddard and Michael A. Henning. 2013. Independent domination in graphs: A survey and recent results. Discr. Math. 313, 7 (2013), 839–854.

[15]

Olga Goussevskaia, Thomas Moscibroda, and Roger Wattenhofer. 2008. Local broadcasting in the physical interference model. In Proceedings of the DIALM-POMC Joint Workshop on Foundations of Mobile Computing, Michael Segal and Alexander Kesselman (Eds.). ACM, 35–44.

Digital Library

[16]

Piyush Gupta and P. R. Kumar. 2000. The capacity of wireless networks. IEEE Trans. Inf. Theory 46, 2 (2000), 388–404.

Digital Library

[17]

Magnús M. Halldórsson, Stephan Holzer, and Nancy A. Lynch. 2015. A local broadcast layer for the SINR network model. In Proceedings of the 2015 ACM Symposium on Principles of Distributed Computing (PODC’15), Chryssis Georgiou and Paul G. Spirakis (Eds.). ACM, 129–138.

[18]

Magnús M. Halldórsson, Fabian Kuhn, Nancy A. Lynch, and Calvin Newport. 2017. An efficient communication abstraction for dense wireless networks. In Proceedings of the 31st International Symposium on Distributed Computing (DISC’17), Andréa W. Richa (Ed.), LIPIcs,Vol. 91. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 25:1–25:16.

[19]

Magnús M. Halldórsson and Pradipta Mitra. 2012. Towards tight bounds for local broadcasting. In Proceedings of the 8th ACM International Workshop on Foundations of Mobile Computing (part of FOMC’12), Fabian Kuhn and Calvin C. Newport (Eds.). ACM, 2.

[20]

Magnús M. Halldórsson and Tigran Tonoyan. 2018. Leveraging indirect signaling for topology inference and fast broadcast. In Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing, (PODC’18), Calvin Newport and Idit Keidar (Eds.). ACM, 85–93.

[21]

Magnús M. Halldórsson and Tigran Tonoyan. 2019. Plain SINR is enough! In Proceedings of the 2019 ACM Symposium on Principles of Distributed Computing (PODC’19), Peter Robinson and Faith Ellen (Eds.). ACM, 127–136.

[22]

Dorit S. Hochbaum and David B. Shmoys. 1986. A unified approach to approximation algorithms for bottleneck problems. J. ACM 33, 3 (1986), 533–550.

Digital Library

[23]

Tomasz Jurdzinski and Dariusz R. Kowalski. 2012. Distributed backbone structure for algorithms in the SINR model of wireless networks. In Proceedings of the 26th International Symposium on Distributed Computing (DISC’12), Marcos K. Aguilera (Ed.), Lecture Notes in Computer Science,Vol. 7611. Springer, 106–120.

[24]

Tomasz Jurdzinski, Dariusz R. Kowalski, Michal Rózanski, and Grzegorz Stachowiak. 2013. Distributed randomized broadcasting in wireless networks under the SINR model. In Proceedings of the 27th International Symposium on Distributed Computing (DISC’13), Yehuda Afek (Ed.), Lecture Notes in Computer Science,Vol. 8205. Springer, 373–387.

Digital Library

[25]

Tomasz Jurdzinski, Dariusz R. Kowalski, Michal Rózanski, and Grzegorz Stachowiak. 2014. On the impact of geometry on ad hoc communication in wireless networks. In Proceedings of the ACM Symposium on Principles of Distributed Computing (PODC’14), Magnús M. Halldórsson and Shlomi Dolev (Eds.). ACM, 357–366.

Digital Library

[26]

Tomasz Jurdzinski, Dariusz R. Kowalski, Michal Rózanski, and Grzegorz Stachowiak. 2018. Deterministic digital clustering of wireless ad hoc networks. In Proceedings of the 2018 ACM Symposium on Principles of Distributed Computing (PODC’18), Calvin Newport and Idit Keidar (Eds.). ACM, 105–114.

Digital Library

[27]

Tomasz Jurdzinski, Dariusz R. Kowalski, Michal Rozanski, and Grzegorz Stachowiak. 2020. Token traversal in ad hoc wireless networks via implicit carrier sensing. Theor. Comput. Sci. 811 (2020), 3–20. issue on Structural Information and Communication Complexit.

[28]

Tomasz Jurdzinski, Dariusz R. Kowalski, and Grzegorz Stachowiak. 2013. Distributed deterministic broadcasting in uniform-power ad hoc wireless networks. In Proceedings of the 19th International Symposium on Fundamentals of Computation Theory (FCT’13), Leszek Gasieniec and Frank Wolter (Eds.), Lecture Notes in Computer Science, Vol. 8070. Springer, 195–209.

Digital Library

[29]

Eyal Kushilevitz and Yishay Mansour. 1998. An omega(D log (N/D)) lower bound for broadcast in radio networks. SIAM J. Comput. 27, 3 (1998), 702–712.

Digital Library

[30]

Thomas Moscibroda and Roger Wattenhofer. 2005. Maximal independent sets in radio networks. In Proceedings of the 24th Annual ACM Symposium on Principles of Distributed Computing (PODC’05), Marcos Kawazoe Aguilera and James Aspnes (Eds.). ACM, 148–157.

Digital Library

[31]

Thomas Moscibroda and Roger Wattenhofer. 2008. Coloring unstructured radio networks. Distrib. Comput. 21, 4 (2008), 271–284.

Digital Library

[32]

Calvin C. Newport. 2014. Radio network lower bounds made easy. In Proceedings of the 28th International Symposium on Distributed Computing (DISC’14), Fabian Kuhn (Ed.), Lecture Notes in Computer Science,Vol. 8784. Springer, 258–272.

[33]

David Peleg. 2000. Distributed Computing: A Locality-sensitive Approach. Society for Industrial and Applied Mathematics, Philadelphia, PA.

[34]

Christian Scheideler, Andréa W. Richa, and Paolo Santi. 2008. An O(log n) dominating set protocol for wireless ad-hoc networks under the physical interference model. In Proceedings of the 9th ACM Interational Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc’08), Xiaohua Jia, Ness B. Shroff, and Peng-Jun Wan (Eds.). ACM, 91–100.

Digital Library

[35]

Dongxiao Yu, Qiang-Sheng Hua, Yuexuan Wang, and Francis C. M. Lau. 2012. An O(log n) distributed approximation algorithm for local broadcasting in unstructured wireless networks. In Proceedings of the IEEE 8th International Conference on Distributed Computing in Sensor Systems (DCOSS’12). IEEE Computer Society, 132–139.

[36]

Dongxiao Yu, Qiang-Sheng Hua, Yuexuan Wang, Haisheng Tan, and Francis C. M. Lau. 2012. Distributed multiple-message broadcast in wireless ad-hoc networks under the SINR model. In Proceedings of the 19th International Colloquium on Structural Information and Communication Complexity (SIROCCO’12), Guy Even and Magnús M. Halldórsson (Eds.), Lecture Notes in Computer Science,Vol. 7355. Springer, 111–122.

[37]

Dongxiao Yu, Qiang-Sheng Hua, Yuexuan Wang, Haisheng Tan, and Francis C. M. Lau. 2016. Distributed multiple-message broadcast in wireless ad hoc networks under the SINR model. Theor. Comput. Sci. 610 (2016), 182–191.

Digital Library

[38]

Dongxiao Yu, Yuexuan Wang, Qiang-Sheng Hua, and Francis C. M. Lau. 2014. Distributed (Δ + 1)-coloring in the physical model. Theor. Comput. Sci. 553 (2014), 37–56.

Digital Library

[39]

Dongxiao Yu, Yuexuan Wang, Tigran Tonoyan, and Magnús M. Halldórsson. 2017. Dynamic adaptation in wireless networks under comprehensive interference via carrier sense. In Proceedings of the 2017 IEEE International Parallel and Distributed Processing Symposium (IPDPS’17). IEEE Computer Society, 337–346.

Cited By

Zhao JLi JFan HLi WZhang JDai X(2022)Optimal Scheduling Model of WDM/OTN Network Transmission Line Based on Machine LearningJournal of Control Science and Engineering10.1155/2022/20069302022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/2006930
Chlebus BKowalski DVaya S(2022)Distributed bare-bones communication in wireless networksDistributed Computing10.1007/s00446-021-00413-735:1(59-80)Online publication date: 1-Feb-2022
https://dl.acm.org/doi/10.1007/s00446-021-00413-7

Index Terms

Sparse Backbone and Optimal Distributed SINR Algorithms
1. Networks
  1. Network algorithms
    1. Control path algorithms
      1. Network control algorithms
  2. Network types
    1. Ad hoc networks
2. Theory of computation
  1. Design and analysis of algorithms
    1. Distributed algorithms

Recommendations

Plain SINR is Enough!
PODC '19: Proceedings of the 2019 ACM Symposium on Principles of Distributed Computing

We develop randomized distributed algorithms for many of the most fundamental communication problems in the wireless SINR model, including (multi-message) broadcast, local broadcast, coloring, MIS, and aggregation. The complexity of the algorithms is ...
Distributed multiple-message broadcast in wireless ad hoc networks under the SINR model

In a multiple-message broadcast, an arbitrary number of messages originate at arbitrary nodes in the network at arbitrary times. The problem is to disseminate all these messages to the whole network. This paper gives the first randomized distributed ...
Distributed wireless link scheduling in the SINR model

We present an approximation algorithm for wireless link scheduling under the physical SINR interference model. In the link scheduling problem, it is given a set of $$n$$n links in a metric space, each of which is a sender---receiver pair, and the ...

Comments

Information & Contributors

Information

Published In

cover image ACM Transactions on Algorithms

ACM Transactions on Algorithms Volume 17, Issue 2

April 2021

235 pages

ISSN:1549-6325

EISSN:1549-6333

DOI:10.1145/3461695

Editor:
Edith Cohen
Google Research, USA and Tel Aviv University, Israel

Issue’s Table of Contents

Copyright © 2021 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]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 June 2021

Accepted: 01 February 2021

Revised: 01 November 2020

Received: 01 December 2019

Published in TALG Volume 17, Issue 2

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article
Research
Refereed

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

2
Total Citations
View Citations
96
Total Downloads

Downloads (Last 12 months)11
Downloads (Last 6 weeks)0

Reflects downloads up to 03 Oct 2024

Other Metrics

View Author Metrics

Citations

Cited By

Zhao JLi JFan HLi WZhang JDai X(2022)Optimal Scheduling Model of WDM/OTN Network Transmission Line Based on Machine LearningJournal of Control Science and Engineering10.1155/2022/20069302022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/2006930
Chlebus BKowalski DVaya S(2022)Distributed bare-bones communication in wireless networksDistributed Computing10.1007/s00446-021-00413-735:1(59-80)Online publication date: 1-Feb-2022
https://dl.acm.org/doi/10.1007/s00446-021-00413-7

View Options

Get Access

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 Article

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

HTML Format

View this article in HTML Format.

Media

Figures

Other

Tables

View Issue’s Table of Contents