EWSN 2006: Wireless Sensor Networks pp 115-131 | Cite as

On the Scalability of Routing Integrated Time Synchronization

  • János Sallai
  • Branislav Kusý
  • Ákos Lédeczi
  • Prabal Dutta
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3868)

Abstract

Reactive time synchronization is becoming increasingly popular in the realm of wireless sensor networks. Unlike proactive protocols, traditionally implemented as a standalone middleware service that provides a virtual global time to the application layer, reactive techniques establish a common reference time base post facto, i.e. after an event of interest has occurred. In this paper, we present the formal error analysis of a representative reactive technique, the Routing Integrated Time Synchronization protocol (RITS). We show that in the general case, the presence of clock skews cause RITS to scale poorly with the size of the network. Then we identify a special class of sensor network applications that are resilient to this scalability limit. For applications outside this class, we propose an in-network skew compensation strategy that makes RITS scale well with both network size and node density. We provide experimental results using a 45-node network of Berkeley MICA2 motes.

Keywords

Sensor Node Wireless Sensor Network Sink Node Time Synchronization Clock Rate 
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.
This is a preview of subscription content, log in to check access.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Xu, N., Rangwala, S., Chintalapudi, K.K., Ganesan, D., Broad, A., Govindan, R., Estrin, D.: A wireless sensor network for structural monitoring. In: SenSys 2004: Proceedings of the 2nd international conference on Embedded networked sensor systems, pp. 13–24 (2004)Google Scholar
  2. 2.
    West, B.W., Flikkema, P.G., Sisk, T., Koch, G.W.: Wireless sensor networks for dense spatio-temporal monitoring of the environment: A case for integrated circuit, system, and network design. In: 2001 IEEE CAS Workshop on Wireless Communications and Networking (2001)Google Scholar
  3. 3.
    Wang, H., Elson, J., Girod, L., Estrin, D., Yao, K.: Target classification and localization in a habitat monitoring application. In: Proc. of IEEE ICASSP (2003)Google Scholar
  4. 4.
    Simon, G., Maróti, M., Lédeczi, A., Balogh, G., Kusý, B., Nádas, A., Pap, G., Sallai, J., Frampton, K.: Sensor network-based countersniper system. In: SenSys 2004: Proceedings of the 2nd international conference on Embedded networked sensor systems, pp. 1–12 (2004)Google Scholar
  5. 5.
    Lédeczi, A., Nádas, A., Völgyesi, P., Balogh, G., Kusý, B., Sallai, J., Pap, G., Dóra, S., Molnár, K., Maróti, M., Simon, G.: Countersniper system for urban warfare. ACM Transactions on Sensor Networks 1, 153–177 (2005)CrossRefGoogle Scholar
  6. 6.
    Maróti, M., Kusý, B., Simon, G., Lédeczi, A.: The flooding time synchronization protocol. In: SenSys 2004: Proceedings of the 2nd international conference on Embedded networked sensor systems, pp. 39–49 (2004)Google Scholar
  7. 7.
    Elson, J., Girod, L., Estrin, D.: Fine-grained network time synchronization using reference broadcasts. SIGOPS Oper. Syst. Rev. 36, 147–163 (2002)CrossRefGoogle Scholar
  8. 8.
    Kusy, B., Dutta, P., Levis, P., Maroti, M., Ledeczi, A., Culler, D.: Elapsed time on arrival: A simple and versatile primitive for canonical time synchronization services. International Journal of Ad Hoc and Ubiquitous Computing 2 (2006)Google Scholar
  9. 9.
    Römer, K.: Time synchronization in ad hoc networks. In: Proceedings of MobiHoc 2001 (2001)Google Scholar
  10. 10.
    Elson, J., Estrin, D.: Time synchronization for wireless sensor networks. In: Proceedings of the 15th International Parallel and Distributed Processing Symposium, IPDPS 2001 (2001)Google Scholar
  11. 11.
    Elson, J.: Time synchronization in wireless sensor networks. Ph.D. Thesis (2003)Google Scholar
  12. 12.
    Maróti, M.: Directed flood-routing framework for wireless sensor networks. In: Jacobsen, H.-A. (ed.) Middleware 2004. LNCS, vol. 3231, pp. 99–114. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  13. 13.
    Hill, J., Culler, D.: Mica: A wireless platform for deeply embedded networks. IEEE Micro 22, 12–24 (2002)CrossRefGoogle Scholar
  14. 14.
    Polastre, J., Szewczyk, R., Culler, D.: Telos: Enabling ultra-low power wireless research. In: Proceedings of the 4th Int. Conf. on Information Processing in Sensor Networks: Special track on Platform Tools and Design Methods for Network Embedded Sensors, IPSN/SPOTS (2005)Google Scholar
  15. 15.
    Ganeriwal, S., Ganesan, D., Hansen, M., Srivastava, M.B., Estrin, D.: Rate-adaptive time synchronization for long lived sensor networks. In: Proceedings of the ACM international conference on Measurement and modeling of computer systems (SIGMETRICS 2005), Short Paper (2005)Google Scholar
  16. 16.
    Ganeriwal, S., Ganesan, D., Sim, H., Tsiatsis, V., Srivastava, M.B.: Estimating clock uncertainty for efficient duty cycling in sensor networks. In: SenSys 2005: Third ACM Conference on Embedded Networked Sensor Systems (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • János Sallai
    • 1
  • Branislav Kusý
    • 1
  • Ákos Lédeczi
    • 1
  • Prabal Dutta
    • 2
  1. 1.Institute for Software Integrated SystemsVanderbilt UniversityNashvilleUSA
  2. 2.Computer Science DivisionUniversity of CaliforniaBerkeleyUSA

Personalised recommendations