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Monitoring Churn in Wireless Networks

  • Stephan Holzer
  • Yvonne Anne Pignolet
  • Jasmin Smula
  • Roger Wattenhofer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6451)

Abstract

Wireless networks often experience a significant amount of churn, the arrival and departure of nodes. In this paper we propose a distributed algorithm for single-hop networks that detects churn and is resilient to a worst-case adversary. The nodes of the network are notified about changes quickly, in asymptotically optimal time up to an additive logarithmic overhead. We establish a trade-off between saving energy and minimizing the delay until notification for single- and multi-channel networks.

Keywords

Time Slot Collision Detection Leader Election Communication Graph Replacement Node 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Bakshi, A., Prasanna, V.K.: Energy-Efficient Communication in Multi-Channel Single-Hop Sensor Networks. In: Conference on Parallel and Distributed Systems, p. 403. IEEE, Los Alamitos (2004)Google Scholar
  2. 2.
    Bar-Yehuda, R., Goldreich, O., Itai, A.: Efficient Emulation of Single-Hop Radio Network with Collision Detection on Multi-Hop Radio Network with No Collision Detection. Distributed Computing 5(2), 67–71 (1991)CrossRefzbMATHGoogle Scholar
  3. 3.
    Caragiannis, I., Galdi, C., Kaklamanis, C.: Basic computations in wireless networks. In: Deng, X., Du, D.-Z. (eds.) ISAAC 2005. LNCS, vol. 3827, pp. 533–542. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  4. 4.
    Chlebus, B.S., Kowalski, D.R., Lingas, A.: Performing work in broadcast networks. Distributed Computing 18(6), 435–451 (2006)CrossRefzbMATHGoogle Scholar
  5. 5.
    Chlebus, B.S., Kowalski, D.R., Rokicki, M.A.: Maximum throughput of multiple access channels in adversarial environments. Distributed Computing 22(2), 93–116 (2009)CrossRefzbMATHGoogle Scholar
  6. 6.
    Chockler, G.V., Keidar, I., Vitenberg, R.: Group communication specifications: a comprehensive study. ACM Computing Surveys (CSUR) 33(4), 427–469 (2001)CrossRefGoogle Scholar
  7. 7.
    Kowalski, D.R., Georgiou, C., Gilbert, S.: Meeting the deadline: On the complexity of fault-tolerant continuous gossip. In: PODC (2010)Google Scholar
  8. 8.
    Holzer, S., Pignolet, Y.A., Smula, J., Wattenhofer, R.: Monitoring Churn in Wireless Networks. Technical report, Computer Engineering and Networks Laboratory (TIK), ETH Zurich, Switzerland (2010), ftp://ftp.tik.ee.ethz.ch/pub/publications/TIK-Report-328.pdf
  9. 9.
    Kabarowski, J., Kutylowski, M., Rutkowski, W.: Adversary immune size approximation of single-hop radio networks. In: Cai, J.-Y., Cooper, S.B., Li, A. (eds.) TAMC 2006. LNCS, vol. 3959, p. 148. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  10. 10.
    Kik, M.: Merging and Merge-Sort in a Single Hop Radio Network. In: Wiedermann, J., Tel, G., Pokorný, J., Bieliková, M., Štuller, J. (eds.) SOFSEM 2006. LNCS, vol. 3831, p. 341. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  11. 11.
    Klonowski, M., Kutyłowski, M., Zatopianski, J.: Energy Efficient Alert in Single-Hop Networks of Extremely Weak Devices. In: Dolev, S. (ed.) ALGOSENSORS 2009. LNCS, vol. 5804, pp. 139–150. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  12. 12.
    Kowalski, D.R., Pelc, A.: Leader Election in Ad Hoc Radio Networks: A Keen Ear Helps. In: 36th International Colloquium on Automata, Languages and Programming, p. 533 (2009)Google Scholar
  13. 13.
    Kutyłowski, M., Letkiewicz, D.: Computing Average Value in Ad Hoc Networks. In: Rovan, B., Vojtáš, P. (eds.) MFCS 2003. LNCS, vol. 2747, pp. 511–520. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  14. 14.
    Kutyłowski, M., Rutkowski, W.: Adversary Immune Leader Election in Ad Hoc Radio Networks. In: Di Battista, G., Zwick, U. (eds.) ESA 2003. LNCS, vol. 2832, pp. 397–408. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  15. 15.
    Lavault, C., Marckert, J.F., Ravelomanana, V.: Quasi-optimal energy-efficient leader election algorithms in radio networks. Information and Computation 205(5), 679–693 (2007)MathSciNetCrossRefzbMATHGoogle Scholar
  16. 16.
    Singh, M., Prasanna, V.K.: Optimal energy-balanced algorithm for selection in a single hop sensor network. In: IEEE Workshop on Sensor Network Protocols and Applications (SNPA) (2003)Google Scholar
  17. 17.
    Singh, M., Prasanna, V.K.: Energy-optimal and energy-balanced sorting in a single-hop wireless sensor network. In: Pervasive Computing and Communications (PERCOM) (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Stephan Holzer
    • 1
  • Yvonne Anne Pignolet
    • 2
  • Jasmin Smula
    • 1
  • Roger Wattenhofer
    • 1
  1. 1.Computer Engineering and Networks Laboratory (TIK)ETHZurichSwitzerland
  2. 2.Zurich Research LaboratoryIBM ResearchZurichSwitzerland

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