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Link Quality-Based Channel Selection for Resource Constrained WSNs

  • Markku Hänninen
  • Jukka Suhonen
  • Timo D. Hämäläinen
  • Marko Hännikäinen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6646)

Abstract

Wireless Sensor Networks (WSN) consist of autonomous and intelligent nodes that combine sensing, actuation, and distributed computing with small size and low energy. One of the major issues is overcoming the non-ideality of unreliable real-world wireless links and avoiding interferences. This paper presents a link quality-based lightweight channel selection mechanism that discovers low interference and lightly loaded channels, thus improving latency, reliability, and throughput. The mechanism grades a channel from link reliability and changes the channel on interference. The proposed selection is suitable for resource and energy constrained WSNs as it does not require any extra communication or channel sensing. The channel selection is implemented with a low energy 2.4 GHz multihop mesh WSN using 1 mW transmission power. In practical measurements in a typical office environment with 100 mW WLAN interference, the selection had 96% average link reliability compared to the 84% of randomized channel selection.

Keywords

Wireless sensor networks Channel Selection Interference Avoidance 

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References

  1. 1.
    Ansari, J., Mähönen, P.: Channel selection in spectrum agile and cognitive mac protocols for wireless sensor networks. In: Proceedings of the 8th ACM International Workshop on Mobility Management and Wireless Access, MobiWac 2010, pp. 83–90. ACM, New York (2010)Google Scholar
  2. 2.
    Gnawali, O., Yarvis, M., Heidemann, J., Govindan, R.: Interaction of retransmission, blacklisting, and routing metrics for reliability in sensor network routing. In: First Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks (SECON), pp. 34–43 (October 2004)Google Scholar
  3. 3.
    ISA: Wireless systems for industrial automation: Process control and related applications (2009), ISA-100.11a-2009Google Scholar
  4. 4.
    ISO/IEC 8802-11, IEEE Std 802.11 Second Edition: Information technology - telecommunications and information exchange between systems - local and metropolitan area networks - specific requirements part 11: Wireless LAN medium access control (MAC) and physical layer (PHY) specifications (August 2005)Google Scholar
  5. 5.
    Jin, F., Choi, H.A., Subramaniam, S.: Hardware-aware communication protocols in low energy wireless sensor networks. In: IEEE Military Communications Conference (MILCOM), vol. 1, pp. 676–681 (October 2003)Google Scholar
  6. 6.
    Kohvakka, M., Suhonen, J., Hännikäinen, M., Hämäläinen, T.D.: Transmission power based path loss metering for wireless sensor networks. In: 17th Int’l Symposium on Personal, Indoor and Mobile Radio Communications, pp. 1–5 (September 2006)Google Scholar
  7. 7.
    Kohvakka, M., Suhonen, J., Hämäläinen, T.D., Hännikäinen, M.: Energy-efficient reservation-based medium access control protocol for wireless sensor networks. EURASIP Journal on Wireless Communications and Networking, 20 pages (2010)Google Scholar
  8. 8.
    Liu, T., Kamthe, A., Jiang, L., Cerpa, A.: Performance evaluation of link quality estimation metrics for static multihop wireless sensor networks. In: 6th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON), pp. 1–9 (June 2009)Google Scholar
  9. 9.
    Nelakuditi, S., Lee, S., Yu, Y., Wang, J., Zhong, Z., Lu, G.H., Zhang, Z.L.: Blacklist-aided forwarding in static multihop wireless networks. In: 2nd Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks, pp. 252–262 (September 2005)Google Scholar
  10. 10.
    Ortiz, J., Culler, D.: Multichannel reliability assessment in real world wsns. In: Proceedings of the 9th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN), pp. 162–173. ACM, New York (2010)CrossRefGoogle Scholar
  11. 11.
    Son, D., Krishnamachari, B., Heidemann, J.: Experimental study of the effects of transmission power control and blacklisting in wireless sensor networks. In: First Annual IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks (SECON), pp. 289–298 (October 2004)Google Scholar
  12. 12.
    Song, J., et al.: WirelessHART: Applying wireless technology in real-time industrial process control. In: Real-Time and Embedded Techology and Applications Symposium (RTAS), pp. 377–386 (2008)Google Scholar
  13. 13.
    Srinivasan, K., Levis, P.: Rssi is under appreciated. In: The Third Workshop on Embedded Networked Sensors (EmNets) (May 2006)Google Scholar
  14. 14.
    Suhonen, J., Kuorilehto, M., Hännikäinen, M., Hämäläinen, T.D.: Cost-aware dynamic routing protocol for wireless sensor networks - design and prototype experiments. In: 17th International Symposium on Personal, Indoor and Mobile Radio Communications, pp. 1–5 (September 2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Markku Hänninen
    • 1
  • Jukka Suhonen
    • 1
  • Timo D. Hämäläinen
    • 1
  • Marko Hännikäinen
    • 1
  1. 1.Department of Computer SystemsTampere University of TechnologyTampereFinland

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