Embedded Operating Systems in Wireless Sensor Networks

  • Mohamed Moubarak
  • Mohamed K. Watfa
Part of the Computer Communications and Networks book series (CCN)


Several operating systems (OS) for wireless sensor networks (WSNs) have been designed, implemented and are in the process of enhancement. However, early before implementation, designers face an important decision to make. The designer of an embedded operating system (EOS) has to conform to one of two completely different design philosophies and build his system according to that philosophy. This decision is crucial in the sense that the behavior and performance of each model differs, and those will be reflected on the WSN since the EOS is the core of the system, and any protocol built on top of it will drag with it the characteristics of the design model. Both models are investigated in this chapter by looking at the design and architectures of several EOSs built for WSNs.


Sensor Node Wireless Sensor Network Clock Cycle Execution Model Context Switch 
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.


  1. 1.
    J. Hill, R. Szewczyk, A. Woo, S. Hollar, D. Culler, and K. Pister, “System architecture directions for networked sensors,” Proceedings of the Ninth International Conference on Architectural Support for Programming Languages and Operating Systems, ACM Press, New York, USA, November 2000, pp. 93–104.Google Scholar
  2. 2.
    H. Lauer and R. Needham, “On the duality of operating system structures,” Proceedings of the Second International Symposium on Operating Systems, IR1A, Rocquencourt, France, October 1978; reprinted in Operating Systems Review, April 1979, pp. 3–19.Google Scholar
  3. 3.
    R. Behren, J. Condit, and E. Brewer, “Why events are a bad idea (for high-concurrency servers),” Proceedings of HotOS IX: The Ninth Workshop on Hot Topics in Operating Systems, USENIX Association, Hawaii, USA, May 2003, pp. 19–24.Google Scholar
  4. 4.
    A. Gustafsson, “Threads without the pain,” Queue, ACM Press, New York, USA, November 2005, pp. 34–41.Google Scholar
  5. 5.
    H. Karl and A. Willig, Protocols and Architectures for Wireless Sensor Networks, Wiley, April 2005, pp. 45–50.Google Scholar
  6. 6.
    C. Han, R. Kamur, R. Shea, E. Kohler, and M. Srivastava, “A dynamic operating system for sensor nodes,” Proceedings of the Third International Conference on Mobile Systems, Applications, and Services, ACM Press, New York, USA, June 2005, pp. 163–176.Google Scholar
  7. 7.
    S. Bhatti, J. Carlson, H. Dai, J. Deng, J. Rose, A. Sheth, B. Shucker, C. Gruenwald, A. Torgerson, and R. Han, “MANTIS OS: An embedded multithreaded operating system for wireless micro sensor platforms,” ACMKluwer Mobile Networks and Applications Journal, Special Issue on Wireless Sensor Networks, Kluer Academic, Hingham, USA, August 2005, pp. 563–579.Google Scholar
  8. 8.
    C. Duffy, U. Roedig, G. Herbert, and C. Sreenan, “An experimental comparison of event driven and multi-threaded sensor node operator systems,” Proceedings of the Fifth Annual IEEE International Conference on Pervasive Computing and Communications Workshops, IEEE Computer Society, White Plains, New York, USA, March 2007, pp. 267–271.Google Scholar
  9. 9.
    H. Kim and H. Cha, “Multithreading optimization techniques for sensor network operating systems,” Wireless Sensor Networks, Springer, Heidelberg, April 2007, pp. 293–308.Google Scholar
  10. 10.
    C. Hujumg, C. Sukwon, J. Inuk, K. Hyoseung, S. Hyojeong, Y. Jaehyun, and Y. Chanmin, “RETOS: Resilient, expandable, and threaded operating system for wireless sensor networks,” Proceedings of the Sixth International Conference on Information Processing in Sensor Networks, Massachusetts, USA, April 2007, pp. 148–157.Google Scholar
  11. 11.
    A. Dunkels, B. Gronvall, and T. Voigt, “Contiki – A lightweight and flexible operating system for tiny networked sensors,” Proceedings of the Twenty Ninth Annual IEEE International Conference on Local Computer Networks, November 2004, pp. 455–462.Google Scholar
  12. 12.
    S. Yi, H. Min, J. Heo, B. Boand, and E.F. Roberts, “Performance analysis of task schedulers in operating systems for wireless sensor networks,” Computational Science and Its Applications, Springer, Heidelberg, May 2006, pp. 499–508.Google Scholar
  13. 13.
    C. Duffy, U. Roedig, G. Herbert, and C. Sreenan, “A performance analysis of mantis and tinyos,” University College Cork, Ireland, Technical Report CS-2006-27-11, November 2006.Google Scholar
  14. 14.
    D. Gay, P. Levis, R. von Behren, M. Welsh, E. Brewer, and D. Culler, “The nesC language: A holistic approach to networked embedded systems,” Proceedings of Programming Language Design and Implementation, California, USA, June 2003, pp. 1–11.Google Scholar
  15. 15.
  16. 16.
    Multimodal Networks of In-situ Sensors. .
  17. 17.
    M. Welsh and R. Newton, “Region streams: Functional macroprogramming for sensor networks,” Proceedings of the first workshop on data management for sensor networks, Toronto, Canada, August 2004.Google Scholar

Copyright information

© Springer-Verlag London Limited 2009

Authors and Affiliations

  • Mohamed Moubarak
    • 1
  • Mohamed K. Watfa
  1. 1.Computer Science DepartmentAmerican University of BeirutBeirutLebanon

Personalised recommendations