Deterministic and Energy-Optimal Wireless Synchronization

  • Leonid Barenboim
  • Shlomi Dolev
  • Rafail Ostrovsky
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6950)


We consider the problem of clock synchronization in a wireless setting where processors must minimize the number of times their radios are used, in order to save energy. Energy efficiency is a central goal in wireless networks, especially if energy resources are severely limited, as occurs in sensor and ad-hoc networks, and in many other settings. The problem of clock synchronization is fundamental and intensively studied in the field of distributed algorithms. In the current setting, the problem is to synchronize clocks of m processors that wake up in arbitrary time points, such that the maximum difference between wake up times is bounded by a positive integer n. (Time intervals are appropriately discretized to allow communication of all processors that are awake in the same discrete time unit.) Currently, the best-known results for synchronization for single-hop networks of m processors is a randomized algorithm due to Bradonjic, Kohler and Ostrovsky [2] of \(O\left(\sqrt{n /m} \cdot \mbox{\em poly-log}(n)\right)\) radio-use times per processor, and a lower bound of \(\Omega\left(\sqrt{n/m}\right)\). The main open question left in their work is to close the poly-log gap between the upper and the lower bound and to de-randomize their probabilistic construction and eliminate error probability. This is exactly what we do in this paper. That is, we show a deterministic algorithm with radio use of \(\Theta\left(\sqrt{n /m}\right)\), which exactly matches the lower bound proven in [2], up to a small multiplicative constant. Therefore, our algorithm is optimal in terms of energy efficiency and completely resolves a long sequence of works in this area [2, 11–14]. Moreover, our algorithm is optimal in terms of running time as well. In order to achieve these results we devise a novel adaptive technique that determines the times when devices power their radios on and off. This technique may be of independent interest.

In addition, we prove several lower bounds on the energy efficiency of algorithms for multi-hop networks. Specifically, we show that any algorithm for multi-hop networks must have radio use of \(\Omega(\sqrt n)\) per processor. Our lower bounds holds even for specific kinds of networks such as networks modeled by unit disk graphs and highly connected graphs.


Sensor Network Deterministic Algorithm Radio Device Clock Synchronization Global Time 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Barenboim, L., Dolev, S., Ostrovsky, R.: Deterministic and Energy-Optimal Wireless Synchronization (2010),
  2. 2.
    Bradonjic, M., Kohler, E., Ostrovsky, R.: Near-Optimal Radio Use For Wireless Network Synchronization. In: Dolev, S. (ed.) ALGOSENSORS 2009. LNCS, vol. 5804, pp. 15–28. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  3. 3.
    Boulis, A., Srivastava, M.: Node-Level Energy Management for Sensor Networks in the Presence of Multiple Applications. Wireless Networks 10(6), 737–746 (2004)CrossRefGoogle Scholar
  4. 4.
    Boulis, A., Ganeriwal, S., Srivastava, M.: Aggregation in sensor networks: an energy-accuracy trade-off. Ad Hoc Networks 1(2-3), 317–331 (2003)CrossRefGoogle Scholar
  5. 5.
    Bush, S.F.: Low-energy sensor network time synchronization as an emergent property. In: Proc. of the 14th International Conference on Communications and Networks, pp. 93–98 (2005)Google Scholar
  6. 6.
    Elson, J., Römer, K.: Wireless sensor networks: a new regime for time synchronization SIGCOMM Comput. Commun. Rev. 33(1), 149–154 (2003)CrossRefGoogle Scholar
  7. 7.
    Fan, R., Chakraborty, I., Lynch, N.: Clock Synchronization for Wireless Networks. In: Higashino, T. (ed.) OPODIS 2004. LNCS, vol. 3544, pp. 400–414. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  8. 8.
    Herman, T., Pemmaraju, S., Pilard, L., Mjelde, M.: Temporal partition in sensor networks. In: Masuzawa, T., Tixeuil, S. (eds.) SSS 2007. LNCS, vol. 4838, pp. 325–339. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  9. 9.
    Honda, N., Nishitani, Y.: The Firing Squad Synchronization Problem for Graphs. Theoretical Computer Sciences 14(1), 39–61 (1981)MathSciNetCrossRefzbMATHGoogle Scholar
  10. 10.
    Mills, D.L.: Internet time synchronization: the network time protocol. IEEE Transactions on Communications 39(10), 1482–1493 (1991)CrossRefGoogle Scholar
  11. 11.
    Moscibroda, T., Von Rickenbach, P., Wattenhofer, R.: Analyzing the Energy-Latency Trade-Off During the Deployment of Sensor Networks. In: Proc. of the 25th IEEE International Conference on Computer Communications, pp. 1–13 (2006)Google Scholar
  12. 12.
    McGlynn, M., Borbash, S.: Birthday protocols for low energy deployment and flexible neighbor discovery in ad hoc wireless networks. In: Proc. of the 2nd ACM International Symposium on Mobile Ad Hoc Networking and Computing, pp. 137–145 (2001)Google Scholar
  13. 13.
    Palchaudhuri, S., Johnson, D.: Birthday paradox for energy conservation in sensor networks. In: Proc. of the 5th Symposium of Operating Systems Design and Implementation (2002)Google Scholar
  14. 14.
    Polastre, J., Hill, J., Culler, D.: Versatile low power media access for wireless sensor networks. In: Proc. of the 2nd International Conference on Embedded Networked Sensor Systems, pp. 95–107 (2004)Google Scholar
  15. 15.
    Schurgers, C., Raghunathan, V., Srivastava, M.: Power management for energy-aware communication systems. ACM Trans. Embedded Comput. Syst. 2(3), 431–447 (2003)CrossRefGoogle Scholar
  16. 16.
    Shnayder, V., Hempstead, M., Chen, B., Allen, G., Welsh, M.: Simulating the power consumption of large-scale sensor network applications. In: Proceedings of the 2nd International Conference on Embedded Networked Sensor Systems, pp. 188–200 (2004)Google Scholar
  17. 17.
    Sichitiu, M.L., Veerarittiphan, C.: Simple, accurate time synchronization for wireless sensor networks. In: IEEE Wireless Communications and Networking, WCNC 2003, vol. 2, pp. 1266–1273 (March 16-20, 2003)Google Scholar
  18. 18.
    Sundararaman, B., Buy, U., Kshemkalyani, A.D.: Clock synchronization for wireless sensor networks: a survey. Ad-hoc Networks 3(3), 281–323 (2005)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Leonid Barenboim
    • 1
  • Shlomi Dolev
    • 1
  • Rafail Ostrovsky
    • 2
  1. 1.Department of Computer ScienceBen-Gurion University of the NegevBeer-ShevaIsrael
  2. 2.Computer Science Department and Department of MathematicsUniversity of CaliforniaLos AngelesUSA

Personalised recommendations