Distributed Backbone Structure for Algorithms in the SINR Model of Wireless Networks

  • Tomasz Jurdzinski
  • Dariusz R. Kowalski
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7611)


The Signal-to-Interference-and-Noise-Ratio (SINR) physical model is one of the most popular models of wireless networks. Despite of the vast amount of study done in design and analysis of centralized algorithms supporting wireless communication under the SINR physical model, little is known about distributed algorithms in this model, especially deterministic ones. In this work we construct, in a deterministic distributed way, a backbone structure on the top of a given wireless network, which can be used for efficient transformation of many algorithms designed in a simpler model of ad hoc broadcast networks without interference into the SINR physical model with uniform power of stations. The time cost of the backbone data structure construction is only \(O(\Delta \text{ \!polylog\! } N)\) rounds, where Δ is roughly the network density and {1,…,N} is the range of identifiers (IDs) and thus N is an upper bound on the number of nodes in the whole network. The core of the construction is a novel combinatorial structure called SINR-selector, which is introduced in this paper. We demonstrate the power of the backbone data structure by using it for obtaining efficient \(O(D+\Delta \text{ \!polylog\! } N)\) round and \(O(D+k+\Delta \text{ \!polylog\! } N)\) round deterministic distributed solutions for leader election and multi-broadcast, respectively, where D is the network diameter and k is the number of messages to be disseminated.


Wireless networks SINR Backbone structure Distributed algorithms Leader Election Multi-message broadcast 


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  1. 1.
    Avin, C., Lotker, Z., Pasquale, F., Pignolet, Y.-A.: A Note on Uniform Power Connectivity in the SINR Model. In: Dolev, S. (ed.) ALGOSENSORS 2009. LNCS, vol. 5804, pp. 116–127. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  2. 2.
    Bar-Yehuda, R., Goldreich, O., Itai, A.: On the time-complexity of broadcast in multi-hop radio networks: An exponential gap between determinism and randomization. J. Comput. Syst. Sci. 45(1), 104–126 (1992)MathSciNetzbMATHCrossRefGoogle Scholar
  3. 3.
    Censor-Hillel, K., Gilbert, S., Kuhn, F., Lynch, N.A., Newport, C.C.: Structuring unreliable radio networks. In: PODC, pp. 79–88. ACM (2011)Google Scholar
  4. 4.
    Chung, H.C., Robinson, P., Welch, J.L.: Optimal regional consecutive leader election in mobile ad-hoc networks. In: FOMC, pp. 52–61. ACM (2011)Google Scholar
  5. 5.
    Cidon, I., Kutten, S., Mansour, Y., Peleg, D.: Greedy packet scheduling. SIAM J. Comput. 24(1), 148–157 (1995)MathSciNetzbMATHCrossRefGoogle Scholar
  6. 6.
    Czumaj, A., Rytter, W.: Broadcasting algorithms in radio networks with unknown topology. In: FOCS, pp. 492–501. IEEE Computer Society (2003)Google Scholar
  7. 7.
    DeMarco, G.: Distributed broadcast in unknown radio networks. SIAM J. Comput. 39(6), 2162–2175 (2010)MathSciNetCrossRefGoogle Scholar
  8. 8.
    Dessmark, A., Pelc, A.: Broadcasting in geometric radio networks. J. Discrete Algorithms 5(1), 187–201 (2007)MathSciNetzbMATHCrossRefGoogle Scholar
  9. 9.
    Emek, Y., Gasieniec, L., Kantor, E., Pelc, A., Peleg, D., Su, C.: Broadcasting in udg radio networks with unknown topology. Distributed Computing 21(5), 331–351 (2009)CrossRefGoogle Scholar
  10. 10.
    Fanghänel, A., Kesselheim, T., Räcke, H., Vöcking, B.: Oblivious interference scheduling. In: PODC, pp. 220–229. ACM (2009)Google Scholar
  11. 11.
    Galcík, F., Gasieniec, L., Lingas, A.: Efficient broadcasting in known topology radio networks with long-range interference. In: PODC, pp. 230–239. ACM (2009)Google Scholar
  12. 12.
    Goussevskaia, O., Moscibroda, T., Wattenhofer, R.: Local broadcasting in the physical interference model. In: DIALM-POMC, pp. 35–44. ACM (2008)Google Scholar
  13. 13.
    Goussevskaia, O., Pignolet, Y.A., Wattenhofer, R.: Efficiency of wireless networks: Approximation algorithms for the physical interference model. Foundations and Trends in Networking 4(3), 313–420 (2010)Google Scholar
  14. 14.
    Hobbs, N., Wang, Y., Hua, Q.-S., Yu, D., Lau, F.C.M.: Deterministic Distributed Data Aggregation under the SINR Model. In: Agrawal, M., Cooper, S.B., Li, A. (eds.) TAMC 2012. LNCS, vol. 7287, pp. 385–399. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  15. 15.
    Jurdzinski, T., Kowalski, D.: Distributed backbone structure for deterministic algorithms in the sinr model of wireless networks. CoRR abs/1207.0602v2 (2012)Google Scholar
  16. 16.
    Kesselheim, T.: A constant-factor approximation for wireless capacity maximization with power control in the sinr model. In: SODA, pp. 1549–1559. SIAM (2011)Google Scholar
  17. 17.
    Kesselheim, T., Vöcking, B.: Distributed Contention Resolution in Wireless Networks. In: Lynch, N.A., Shvartsman, A.A. (eds.) DISC 2010. LNCS, vol. 6343, pp. 163–178. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  18. 18.
    Kowalski, D.R., Pelc, A.: Optimal deterministic broadcasting in known topology radio networks. Distributed Computing 19(3), 185–195 (2007)CrossRefGoogle Scholar
  19. 19.
    Kowalski, D.R., Pelc, A.: Leader Election in Ad Hoc Radio Networks: A Keen Ear Helps. In: Albers, S., Marchetti-Spaccamela, A., Matias, Y., Nikoletseas, S., Thomas, W. (eds.) ICALP 2009, Part II. LNCS, vol. 5556, pp. 521–533. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  20. 20.
    Kuhn, F., Lynch, N.A., Newport, C.C.: The abstract mac layer. Distributed Computing 24(3-4), 187–206 (2011)zbMATHCrossRefGoogle Scholar
  21. 21.
    Kushilevitz, E., Mansour, Y.: An omega(d log (n/d)) lower bound for broadcast in radio networks. SIAM J. Comput. 27(3), 702–712 (1998)MathSciNetzbMATHCrossRefGoogle Scholar
  22. 22.
    Richa, A., Scheideler, C., Schmid, S., Zhang, J.: Towards jamming-resistant and competitive medium access in the sinr model. In: S3 2011, pp. 33–36. ACM (2011)Google Scholar
  23. 23.
    Scheideler, C., Richa, A.W., Santi, P.: An o(log n) dominating set protocol for wireless ad-hoc networks under the physical interference model. In: MobiHoc, pp. 91–100. ACM (2008)Google Scholar
  24. 24.
    Yu, D., Hua, Q.-S., Wang, Y., Tan, H., Lau, F.C.M.: Distributed Multiple-Message Broadcast in Wireless Ad-Hoc Networks under the SINR Model. In: Even, G., Halldórsson, M.M. (eds.) SIROCCO 2012. LNCS, vol. 7355, pp. 111–122. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  25. 25.
    Yu, D., Wang, Y., Hua, Q.S., Lau, F.C.M.: Distributed local broadcasting algorithms in the physical interference model. In: DCOSS, pp. 1–8. IEEE (2011)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Tomasz Jurdzinski
    • 1
  • Dariusz R. Kowalski
    • 2
  1. 1.Institute of Computer ScienceUniversity of WrocławPoland
  2. 2.Department of Computer ScienceUniversity of LiverpoolUnited Kingdom

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