Advertisement

Does Clock Precision Influence ZigBee’s Energy Consumptions?

  • Christian Groß
  • Holger Hermanns
  • Reza Pulungan
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4878)

Abstract

Wireless embedded sensor networks are predicted to provide attractive application possibilities in industry as well as at home. IEEE 802.15.4 and ZigBee are proposed as standards for such networks with a particular focus on pairing reliability with energy efficiency, while sacrificing high data rates.

IEEE 802.15.4 is configurable in many aspects, including the synchronicity of the communication, and the periodicity in which battery-powered sensors need to wake up to communicate. This paper develops a formal behavioral model for the energy implications of these options. The model is modularly specified using the language modest, which has an operational semantics mapping on stochastic timed automata. The latter are simulated using a variant of discrete-event simulation implemented in the tool Möbius. We obtain estimated energy consumptions of a number of possible communication scenarios in accordance with the standards, and derive conclusions about the energy-optimal configuration of such networks. As a specific fine point, we investigate the effects of drifting clocks on the energy behavior of various application scenarios.

Keywords

Sensor networks formal modelling distributed coordination power-aware design clock drift 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    CC2420 Product Information. Chipcon AS (2005), http://www.chipcon.com/index.cfm?kat_id=2&subkat_id=12&dok_id=115
  2. 2.
    IEEE 802.15.4: Wireless Medium Access Control (MAC) and Physical Layer (PHY) Specifications for Low-Rate Wireless Personal Area Networks (2003)Google Scholar
  3. 3.
    ZigBee Specification Version 1.0. ZigBee Alliance (2004), http://www.zigbee.org/en/spec_download/download_request.asp
  4. 4.
    MoDeST Tutorial: development of a complex model in MoDeST. Dependable Systems and Software, Saarland University, Germany (2006), http://depend.cs.uni-sb.de/modesttutorial/index.html
  5. 5.
    The network simulator – ns-2 website (2007), http://www.isi.edu/nsnam/ns/
  6. 6.
    Andel, T.R., Yasinac, A.: On the credibility of Manet simulations. IEEE Computer 39(7), 48–54 (2006)Google Scholar
  7. 7.
    Bengtsson, J., Larsen, K.G., Larsson, F., Pettersson, P., Yi, W.: Uppaal – a tool suite for automatic verification of real-time systems. In: Hybrid Systems III, pp. 232–243. Springer, Heidelberg (1995)Google Scholar
  8. 8.
    Bohnenkamp, H.C., D’Argenio, P.R., Hermanns, H., Katoen, J.-P.: MoDeST: A compositional modeling formalism for hard and softly timed systems. IEEE Trans. Soft. Eng. 32(10), 812–830 (2006)CrossRefGoogle Scholar
  9. 9.
    Bohnenkamp, H.C., Gorter, J., Guidi, J., Katoen, J.-P.: Are you still there? - A lightweight algorithm to monitor node presence in self-configuring networks. In: DSN 2005, pp. 704–709. IEEE CS Press, Los Alamitos (2005)Google Scholar
  10. 10.
    Bohnenkamp, H.C., Hermanns, H., Klaren, R., Mader, A., Usenko, Y.S.: Synthesis and stochastic assessment of schedules for lacquer production. In: QEST 2004, pp. 28–37. IEEE CS Press, Los Alamitos (2004)CrossRefGoogle Scholar
  11. 11.
    Bougard, B., Catthoor, F., Daly, D.C., Chandrakasan, A., Dehaene, W.: Energy efficiency of the IEEE 802.15.4 standard in dense wireless microsensor networks: Modeling and improvement perspectives. In: DATE 2005, pp. 196–201. IEEE CS Press, Los Alamitos (2005)Google Scholar
  12. 12.
    Cadilhac, M., Hérault, T., Lassaigne, R., Peyronnet, S., Tixeuil, S.: Evaluating complex MAC protocols for sensor networks with APMC. Elect. Notes Theor. Comput. Sci. 185, 33–46 (2007)CrossRefGoogle Scholar
  13. 13.
    Cavin, D., Sasson, Y., Schiper, A.: On the accuracy of MANET simulators. In: POMC 2002, pp. 38–43. ACM Press, New York (2002)CrossRefGoogle Scholar
  14. 14.
    Daly, D., Deavours, D.D., Doyle, J.M., Webster, P.G., Sanders, W.H.: Möbius: An extensible tool for performance and dependability modeling. In: Haverkort, B., Bohnenkamp, H.C., Smith, C.U. (eds.) TOOLS 2000. LNCS, vol. 1786, pp. 332–336. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  15. 15.
    Deavours, D.D., Sanders, W.H.: An efficient well-specified check. In: PNPM 1999, pp. 124–133. IEEE CS Press, Los Alamitos (1999)Google Scholar
  16. 16.
    Fruth, M.: Probabilistic model checking of contention resolution in the IEEE 802.15.4 low-rate wireless Personal Area Network protocol. In: ISoLA 2006 (2006)Google Scholar
  17. 17.
    Garavel, H., Lang, F., Mateescu, R.: An overview of CADP 2001. EASST Newsletter 4, 13–24 (2001)Google Scholar
  18. 18.
    Hermanns, H., Jansen, D.N., Usenko, Y.S.: From StoCharts to MoDeST: a comparative reliability analysis of train radio communications. In: WOSP 2005, pp. 13–23. ACM Press, New York (2005)CrossRefGoogle Scholar
  19. 19.
    Kwiatkowska, M.Z., Norman, G., Parker, D.: PRISM: Probabilistic symbolic model checker. In: Field, T., Harrison, P.G., Bradley, J., Harder, U. (eds.) TOOLS 2002. LNCS, vol. 2324, pp. 200–204. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  20. 20.
    Landsiedel, O., Wehrle, K., Götz, S.: Accurate prediction of power consumption in sensor networks. In: EmNetS-II, pp. 37–44 (2005)Google Scholar
  21. 21.
    Pongor, G.: OMNeT: Objective modular network testbed. In: MASCOTS 1993, pp. 323–326 (1993)Google Scholar
  22. 22.
    Titzer, B.L., Lee, D.K., Palsberg, J.: Avrora: Scalable sensor network simulation with precise timing. In: IPSN 2005, pp. 477–482 (2005)Google Scholar
  23. 23.
    Zeng, X., Bagrodia, R., Gerla, M.: GloMoSim: A library for parallel simulation of large-scale wireless networks. In: WPDS 1998, pp. 154–161 (1998)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Christian Groß
    • 1
  • Holger Hermanns
    • 2
  • Reza Pulungan
    • 2
  1. 1.comlet Verteilte Systeme GmbHZweibrückenGermany
  2. 2.Department of Computer ScienceSaarland UniversitySaarbrückenGermany

Personalised recommendations