Smart and Cooperative Neighbourhood for Spatial Routing in Wireless Sensor Networks

  • Jan Nikodem
  • Zenon Chaczko
  • Maciej Nikodem
  • Ryszard Klempous
Part of the Topics in Intelligent Engineering and Informatics book series (TIEI, volume 2)


The outcome of applying relations and set theories instead of functions when staging the proposed routing algorithm is an appearance of choice in Wireless Sensor Network nodes. This research presents a model that is universal, practical, and mathematically sound. In its essence, the model promotes the emergence of a smart and cooperative neighbourhood. Central, to a rise of emergent properties in WSN, is the deployment of nodes within neighbourhood that are equipped with some form of collective intelligence. While defining the concept of spatial routing, we unfold the rules of smart neighbourhood for relaying data in a dynamic and evolving environment. The most interesting aspect of the proposed concept of neighbourhood smartness is its support for a certain form of stigmergy that allows neighbourhoods behavioural flexibility in WSN. The network routing paths adapt to the level of interference and thus avoiding areas of increased disturbance. By using Link Quality Indicator parameters, it is possible to choose the best consecutive relay. This allows adjusting our choices to the disturbance levels and thus circumventing the area of interference. In the end; this ensures a successful transmission even in the most adverse environmental conditions.


Sensor Network Sensor Node Wireless Sensor Network Receive Signal Strength Indicator Link Quality Indicator 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Burmester, M., Le, T.V., Yasinsac, A.: Adaptive gossip protocols: Managing security and redundancy in dense ad hoc networks. Ad Hoc Networks 5(3), 13–32 (2007)CrossRefGoogle Scholar
  2. 2.
    Cerpa, A., Estrin, D.: ASCENT: Adaptive Self-Configuring Sensor Networks Topologies. IEEE Transactions on Mobile Computing 3(3) (July-September 2004)Google Scholar
  3. 3.
    Cohn, A.G., Bennett, B., Gooday, J.M., Gotts, N.M.: Representing and Reasoning with Qalitative Spatial Relations about Regions. In: Cohn, A.G., Bennett, B., Gooday, J.M., Gotts, N.M. (eds.) Spatial and Temporal Reasoning. Kulwer, Dordrecht, pp. 97–134 (1997)Google Scholar
  4. 4.
    Chaczko, Z., Ahmad, F.: Wireless Sensor Network Based System for Fire Endangered Areas. In: ICITA 2005, Sydney (2005)Google Scholar
  5. 5.
    Chaczko, Z.: Towards Epistemic Autonomy in Adaptive Biomimetic Middleware for Cooperative Sensornets, PhD thesis, UTS, Australia (2009)Google Scholar
  6. 6.
    Feng, C., Yang, L., Rozenblit, J.W., Beudert, P.: Design of a Wireless Sensor Network Based Automatic Light Controller in Theater Arts. In: ECBS 2007, pp. 161–170 (2007)Google Scholar
  7. 7.
    Jaroń, J.: Systemic Prolegomena to Theoretical Cybernetics, Scient. Papers of Inst. of Techn. Cybernetics, vol. (45). Wrocław Techn. Univ., Wrocław (1978)Google Scholar
  8. 8.
    Nikodem, J., Klempous, R., Chaczko, Z.: Modelling of immune functions in a wireless sensors network. In: 20th European Modeling and Simulation Symposium, EMSS 2008. Campora S. Giovanni, Italy (2008)Google Scholar
  9. 9.
    Nikodem, J., Klempous, R., Nikodem, M., Woda, M.: Multihop Communication in Wireless Sensors Network Based on Directed Cooperation. In: 4th International Conference on Broadband Communication, Information Technology and Biomedical Applications, BroadBandCom 2009, Wroclaw, Poland (2009)Google Scholar
  10. 10.
    Nikodem, J.: Designing Communication Space in Wireless Sensor Network Based on Relational Attempt. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds.) EUROCAST 2009. LNCS, vol. 5717, pp. 83–90. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  11. 11.
    Nikodem, J., Nikodem, M., Woda, M., Klempous, R., Chaczko, Z.: Relation-based message routing in wireless sensor networks. In: Chinh, H.D., Tan, Y.K. (eds.) Smart Wireless Sensor Networks, pp. 127–145. InTech (2010)Google Scholar
  12. 12.
    Nikodem, J., Nikodem, M., Klempous, R., Chaczko, Z.: Multi-hop and Directed Routing Based on Neighborhood Cooperation in WSN. In: 15th IEEE International Conference on Intelligent Engineering Systems (INES), Poprad, pp. 221–227 (June 2011) ISBN: 978-1-4244-8954-1, doi:10.1109/INES.2011.5954748Google Scholar
  13. 13.
    Nikodem, J., Chaczko, Z., Nikodem, M., Klempous, R., Wickramasooriya, R.: Combating Security Threats via Immunity and Adaptability in Cognitive Radio Networks. In: Fodor, J., Klempous, R., Suárez Araujo, C.P. (eds.) Recent Advances in Intelligent Engineering Systems. SCI, vol. 378, pp. 221–242. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  14. 14.
    Pichler, F.: Modeling Complex Systems by Multi-Agent Holarchies. In: Kopacek, P., Moreno-Díaz, R., Pichler, F. (eds.) EUROCAST 1999. LNCS, vol. 1798. Springer, Heidelberg (2000)Google Scholar
  15. 15.
    Stojmenović, I. (ed.): Handbook of Sensor Networks Algorithms and Architectures. John Wiley and Sons Inc. (2005)Google Scholar
  16. 16.
    Younis, O., Fahmy, S.: HEED: A Hybrid, Energy-Efficient, Distributed Clustering Approach for Ad Hoc Sensor Networks. IEEE Transactions on Mobile Computing 3(4) (October-December 2004)Google Scholar
  17. 17.
    ZigBee Standards Organisation, ZigBee Specification, Document No 053474r17, Sponsored by ZigBee Alliance, San Ramon, CA, USA (January 2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Jan Nikodem
    • 1
  • Zenon Chaczko
    • 2
  • Maciej Nikodem
    • 1
  • Ryszard Klempous
    • 1
  1. 1.Institute of Computer Engineering, Control and RoboticsWrocław University of TechnologyWroclawPoland
  2. 2.Faculty of Engineering and ITUniversity of Technology Sydney (UTS)UltimoAustralia

Personalised recommendations