Data Filtering and Aggregation in a Localisation WSN Testbed

  • Ivo F. R. Noppen
  • Desislava C. Dimitrova
  • Torsten Braun
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 44)


The main challenge in wireless networks is to optimally use the confined radio resources to support data transfer. This holds for large-scale deployments as well as for small-scale test environments such as test-beds. We investigate two approaches to reduce the radio traffic in a test-bed, namely, filtering of unnecessary data and aggregation of redundant data. Both strategies exploit the fact that, depending on the tested application’s objective, not all data may be of interest. The proposed design solutions indicate that traffic reduction as high as 97% can be achieved in the specific case of test-bed for indoor localisation.


WSN filtering aggregation WiFi bluetooth 


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  1. 1.
    Greenorbs test-bed, (accessed: January 27, 2012)
  2. 2.
    Gumstix overo, (accessed: January 27, 2012)
  3. 3.
    Honk kong university, internet and mobile computing laboratory test-bed, (accessed: January 27, 2012)
  4. 4.
    IEEE 802.11-2007, Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications (2007),
  5. 5.
    Chen, Z., Shin, K.G.: Opag: Opportunistic data aggregation in wireless sensor networks. In: Real-Time Systems Symposium 2008, pp. 345–354 (2008)Google Scholar
  6. 6.
    Dimitrova, D.C., Alyafawi, I., Braun, T.: Experimental Comparison of Bluetooth and WiFi Signal Propagation for Indoor Localisation. In: Koucheryavy, Y., Mamatas, L., Matta, I., Tsaoussidis, V. (eds.) WWIC 2012. LNCS, vol. 7277, pp. 126–137. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  7. 7.
    Dolfus, K., Braun, T.: An evaluation of compression schemes for wireless networks. In: International Congress on Ultra Modern Telecommunications and Control Systems, pp. 1–6 (2010)Google Scholar
  8. 8.
    Krishnamachari, L., Estrin, D., Wicker, S.: The impact of data aggregation in wireless sensor networks. In: Proc. of Distributed Computing Systems Workshops, pp. 575–578 (2002)Google Scholar
  9. 9.
    Kumar, V., McCarville-Schueths, J., Madria, S.: A test-bed for secure hierarchical data aggregation in wireless sensor networks. In: 2010 IEEE 7th International Conference on Mobile Adhoc and Sensor Systems (MASS), pp. 762–764 (November 2010)Google Scholar
  10. 10.
    Murty, R.N., Mainland, G., Rose, I., Chowdhury, A.R., Gosain, A., Bers, J., Welsh, M.: Citysense: An urban-scale wireless sensor network and testbed. In: Proc. of IEEE Technologies for Homeland Security, pp. 583–588 (2008)Google Scholar
  11. 11.
    Staub, T., Morgenthaler, S., Balsiger, D., Goode, P.K., Braun, T.: Adam: Administration and deployment of adhoc mesh networks. In: 3rd IEEE Workshop on Hot Topics in Mesh Networking (IEEE HotMESH 2011) (2011)Google Scholar
  12. 12.
    Taghikhaki, Z., Meratnia, N., Havinga, P.J.M.: Energy-efficient trust-based aggregation in wireless sensor networks. In: IEEE INFOCOM: Workshops, pp. 584–589 (2011)Google Scholar

Copyright information

© ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering 2012

Authors and Affiliations

  • Ivo F. R. Noppen
    • 2
  • Desislava C. Dimitrova
    • 1
  • Torsten Braun
    • 1
  1. 1.Universität BernBernSwitzerland
  2. 2.Universiteit TwenteEnschedeThe Netherlands

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