Impulsive Interference Avoidance in Dense Wireless Sensor Networks

  • Nicholas M. Boers
  • Ioanis Nikolaidis
  • Pawel Gburzynski
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7363)


Wireless sensor networks (WSNs) are subject to interference from other users of the radio-frequency (RF) medium. If the WSN nodes can recognize the interference pattern, they can benefit from steering their transmissions around it. This possibility has stirred some interest among researchers involved in cognitive radios, where special hardware has been postulated to circumvent non-random interference. Our goal is to explore ways of enhancing medium access control (MAC) schemes operating within the framework of traditional off-the-shelf RF modules applicable in low-cost WSN motes, such that they can detect interference patterns in the neighbourhood and creatively respond to them, mitigating their negative impact on the packet reception rate. In this paper, and based on previous work on the post-deployment characterization of a channel aimed at identifying “spiky” interference patterns, we describe (a) a way to incorporate interference models into an existing WSN emulator and (b) the subsequent evaluation of a proof-of-concept MAC technique for circumventing the interference. We found that an interference-aware MAC can improve the packet delivery rates in these environments at the cost of increased, but acceptable, latency.


classification interference sampling wireless sensor networks channel modelling medium access control 


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  1. 1.
    Do, J., Akos, D., Enge, P.: L and S bands spectrum survey in the San Francisco Bay area. In: PLANS 2004: Position Location and Navigation Symposium, pp. 566–572 (2004)Google Scholar
  2. 2.
    Boers, N.M., Chodos, D., Huang, J., Stroulia, E., Gburzynski, P., Nikolaidis, I.: The Smart Condo: Visualizing independent living environments in a virtual world. In: PervasiveHealth 2009: Proceedings from the 3rd International Conference on Pervasive Computing Technologies for Healthcare, London, UK (April 2009)Google Scholar
  3. 3.
    Stroulia, E., Chodos, D., Boers, N.M., Huang, J., Gburzynski, P., Nikolaidis, I.: Software engineering for health education and care delivery systems: The Smart Condo project. In: SEHC 2009: Proceedings from the 31st International Conference on Software Engineering, Vancouver, Canada (2009)Google Scholar
  4. 4.
    Boers, N.M., Nikolaidis, I., Gburzynski, P.: Patterns in the RSSI traces from an indoor urban environment. In: CAMAD 2010: IEEE 14th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks, Coconut Creek, FL, December 3-4 (2010)Google Scholar
  5. 5.
    Vieira, M., Coelho Jr., C.N., da Silva Junior, D.C., da Mata, J.: Survey on wireless sensor network devices. In: ETFA 2003: Proceedings of the IEEE Conference on Emerging Technologies and Factory Automation, vol. 1, pp. 537–544 (September 2003)Google Scholar
  6. 6.
    Oetting, J.: A comparison of modulation techniques for digital radio. IEEE Transactions on Communications 27(12), 1752–1762 (1979)zbMATHCrossRefGoogle Scholar
  7. 7.
    Boers, N.M., Nikolaidis, I., Gburzynski, P.: Sampling and classifying interference patterns in a wireless sensor network. ACM Transactions on Sensor Networks (to appear)Google Scholar
  8. 8.
    Srinivasan, K., Dutta, P., Tavakoli, A., Levis, P.: An empirical study of low-power wireless. ACM Transactions on Sensor Networks 6(2), 1–49 (2010)CrossRefGoogle Scholar
  9. 9.
    Chandra, A.: Measurements of radio impulsive noise from various sources in an indoor environment at 900 MHz and 1800 MHz. In: 13th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, vol. 2, pp. 639–643 (September 2002)Google Scholar
  10. 10.
    Srinivasan, K., Dutta, P., Tavakoli, A., Levis, P.: Understanding the causes of packet delivery success and failure in dense wireless sensor networks. In: SenSys 2006: Proceedings of the 4th International Conference on Embedded Networked Sensor Systems, pp. 419–420. ACM, New York (2006)CrossRefGoogle Scholar
  11. 11.
    Lee, H., Cerpa, A., Levis, P.: Improving wireless simulation through noise modeling. In: IPSN 2007: Proceedings of the 6th International Conference on Information Processing in Sensor Networks, pp. 21–30. ACM, New York (2007)CrossRefGoogle Scholar
  12. 12.
    Rusak, T., Levis, P.: Physically-based models of low-power wireless links using signal power simulation. Computer Networks 54(4), 658–673 (2010)CrossRefGoogle Scholar
  13. 13.
    Akhmetshina, E., Gburzynski, P., Vizeacoumar, F.: PicOS: A tiny operating system for extremely small embedded platforms. In: Arabnia, H.R., Yang, L.T. (eds.) Embedded Systems and Applications, pp. 116–122. CSREA Press (2003)Google Scholar
  14. 14.
    Gburzynski, P., Nikolaidis, I.: Wireless network simulation extensions in SMURPH/SIDE. In: WSC 2006: Proceedings of the 2006 Winter Simulation Conference, Monterey, California (December 2006)Google Scholar
  15. 15.
    Boers, N.M., Gburzynski, P., Nikolaidis, I., Olesinski, W.: Developing wireless sensor network applications in a virtual environment. Telecommunication Systems 45(2), 165–176 (2010)CrossRefGoogle Scholar
  16. 16.
    Srinivasan, K., Jain, M., Choi, J.I., Azim, T., Kim, E.S., Levis, P., Krishnamachari, B.: The κ-factor: Inferring protocol performance using inter-link reception correlation. In: MobiCom 2010: Proceedings of the 16th Annual International Conference on Mobile Computing and Networking, pp. 317–328. ACM, USA (2010)Google Scholar
  17. 17.
    Zhou, G., He, T., Krishnamurthy, S., Stankovic, J.A.: Impact of radio irregularity on wireless sensor networks. In: MobiSys 2004: Proceedings of the 2nd International Conference on Mobile Systems, Applications, and Services, pp. 125–138. ACM, USA (2004)CrossRefGoogle Scholar
  18. 18.
    Olesinski, W., Rahman, A., Gburzynski, P.: TARP: A tiny ad-hoc routing protocol for wireless networks. In: ATNAC 2003: Proceedings of Australian Telecommunications Networks and Applications Conference, Melbourne, Australia, December 8-10 (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Nicholas M. Boers
    • 1
  • Ioanis Nikolaidis
    • 2
  • Pawel Gburzynski
    • 3
  1. 1.Department of Computer ScienceGrant MacEwan UniversityEdmontonCanada
  2. 2.Department of Computing ScienceUniversity of AlbertaEdmontonCanada
  3. 3.Olsonet Communications CorporationOttawaCanada

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