Efficient and Robust Data Dissemination Using Limited Extra Network Knowledge

  • Ioannis Chatzigiannakis
  • Athanasios Kinalis
  • Sotiris Nikoletseas
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4026)


We propose a new data dissemination protocol for wireless sensor networks, that basically pulls some additional knowledge about the network in order to subsequently improve data forwarding towards the sink. This extra information is still local, limited and obtained in a distributed manner. This extra knowledge is acquired by only a small fraction of sensors thus the extra energy cost only marginally affects the overall protocol efficiency. The new protocol has low latency and manages to propagate data successfully even in the case of low densities. Furthermore, we study in detail the effect of failures and show that our protocol is very robust. In particular, we implement and evaluate the protocol using large scale simulation, showing that it significantly outperforms well known relevant solutions in the state of the art.


Sensor Network Wireless Sensor Network Cluster Head Transmission Range Sensor Device 
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.
    Alvarez, C., Diaz, J., Petit, J., Rolim, J., Serna, M.: Efficient and reliable high level communication in randomly deployed wireless sensor networks. In: 3rd International Mobility and Wireless Access Workshop (MOBIWAC 2004) (2004)Google Scholar
  2. 2.
    Antoniou, T., Boukerche, A., Chatzigiannakis, I., Mylonas, G., Nikoletseas, S.: A new energy efficient and fault-tolerant protocol for data propagation in smart dust networks using varying transmission range. In: 37th Annual Simulation Symposium (ANSS 2004), pp. 43–52. IEEE Press, Los Alamitos (2004)CrossRefGoogle Scholar
  3. 3.
    Aspnes, J., Goldenberg, D., Yang, Y.R.: On the computational complexity of sensor network localization. In: Nikoletseas, S.E., Rolim, J.D.P. (eds.) ALGOSENSORS 2004. LNCS, vol. 3121, pp. 32–44. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  4. 4.
    Boukerche, A., Nikoletseas, S.: Protocols for Data Propagation in Wireless Sensor Networks: A Survey. In: Wireless Communications Systems and Networks, pp. 23–51. Kluwer Academic Publishers, Dordrecht (2004)CrossRefGoogle Scholar
  5. 5.
    Boukerche, A., Pazzi, R., Araujo, R.: A supporting protocol to periodic, event-driven and query-based application scenarios for critical conditions surveillance. In: Nikoletseas, S.E., Rolim, J.D.P. (eds.) ALGOSENSORS 2004. LNCS, vol. 3121, pp. 137–146. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  6. 6.
    Bonabeau, E., Dorigo, M., Theraulaz, G.: Swarm Intelligence: From Natural to Artificial Systems. In: A Volume in the Santa Fe Institute Studies in the Sciences of Complexity. Oxford University Press, Oxford (1999)Google Scholar
  7. 7.
    Bulusu, N., Estrin, D., Girod, L., Heidemann, J.: Scalable coordination for wireless sensor networks: self-configuring localization systems. In: International Symposium on Communication Theory and Applications (ISCTA 2001) (2001)Google Scholar
  8. 8.
    Busch, C., Magdon-Ismail, M., Sivrikaya, F., Yener, B.: Contention-free MAC protocols for wireless sensor networks. In: Guerraoui, R. (ed.) DISC 2004. LNCS, vol. 3274, pp. 245–259. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  9. 9.
    Chatzigiannakis, I., Dimitriou, T., Nikoletseas, S., Spirakis, P.: A probabilistic forwarding protocol for efficient data propagation in sensor networks. In: 5th European Wireless Conference on Mobile and Wireless Systems beyond 3G (EW 2004), pp. 344–350 (2004) (Also, in the Journal of Ad-Hoc Networks, 2005) Google Scholar
  10. 10.
    Chatzigiannakis, I., Kinalis, A., Nikoletseas, S.: Wireless sensor networks protocols for efficient collision avoidance in multi-path data propagation. In: ACM Workshop on Performance Evaluation of Wireless Ad Hoc, Sensor, and Ubiquitous Networks (PE-WASUN 2004), pp. 8–16 (2004) (Also, in Performance Evaluation Journal: Special issue on PE-WASUN04) (to appear) Google Scholar
  11. 11.
    Chatzigiannakis, I., Kinalis, A., Nikoletseas, S.: An adaptive power conservation scheme for heterogeneous wireless sensor networks with node redeployment. In: 17th Annual Symposium on Parallel Algorithms and Architectures (SPAA 2005), pp. 96–105 (2005) (Also, in the Theory of Computing Systems Journal (TOCS): Special Issue on SPAA 2005) (to appear) Google Scholar
  12. 12.
    Chatzigiannakis, I., Nikoletseas, S.: A forward planning situated protocol for data propagation in wireless sensor networks based on swarm intelligence techniques. In: 17th Annual Symposium on Parallel Algorithms and Architectures (SPAA 2005), p. 214 (2005)Google Scholar
  13. 13.
    Chatzigiannakis, I., Nikoletseas, S., Spirakis, P.: Efficient and robust protocols for local detection and propagation in smart dust networks. Journal of Mobile Networks and Applications 10(1), 133–149 (2005) (Special Issue on Algorithmic Solutions for Wireless, Mobile, Ad Hoc and Sensor Networks)CrossRefGoogle Scholar
  14. 14.
    Crossbow technology inc., MICA motes,
  15. 15.
    Diaz, J., Petit, J., Serna, M.: Evaluation of basic protocols for optical smart dust networks. IEEE Transactions Mobile Networks 2(3), 186–196 (2003)CrossRefGoogle Scholar
  16. 16.
    Dolev, S., Herman, T., Lahiani, L.: Polygonal broadcast, secret maturity and the firing sensors. In: 3rd International Conference on Fun with Algorithms, pp. 41–52 (2004)Google Scholar
  17. 17.
    Heinzelman, W.R., Chandrakasan, A., Balakrishnan, H.: Energy-efficient communication protocol for wireless microsensor networks. In: 33rd IEEE Hawaii International Conference on System Sciences (HICSS 2000) (2000)Google Scholar
  18. 18.
    Hollar, S.: COTS Dust. Msc thesis, Engineering-Mechanical Engineering. University of California, Berkeley, USA (2000)Google Scholar
  19. 19.
    Intanagonwiwat, C., Govindan, R., Estrin, D.: Directed diffusion: A scalable and robust communication paradigm for sensor networks. In: 6th ACM/IEEE Annual International Conference on Mobile Computing (MOBICOM 2000), pp. 56–67 (2000)Google Scholar
  20. 20.
    Nikoletseas, S., Chatzigiannakis, I., Euthimiou, H., Kinalis, A., Antoniou, T., Mylonas, G.: Energy efficient protocols for sensing multiple events in smart dust networks. In: 37th Annual Simulation Symposium (ANSS 2004), pp. 15–24. IEEE Press, Los Alamitos (2004)CrossRefGoogle Scholar
  21. 21.
    Rao, A., Ratnasamy, S., Papadimitriou, C., Shenker, S., Stoica, I.: Geographic routing without location information. In: 9th ACM/IEEE Annual International Conference on Mobile Computing (MOBICOM 2003), San Diego, CA, pp. 96–108 (2003)Google Scholar
  22. 22.
    Wattenhofer, M., Wattenhofer, R., Widmayer, P.: Geometric routing without geometry. In: Pelc, A., Raynal, M. (eds.) SIROCCO 2005. LNCS, vol. 3499, pp. 307–322. Springer, Heidelberg (2005)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Ioannis Chatzigiannakis
    • 1
  • Athanasios Kinalis
    • 1
    • 2
  • Sotiris Nikoletseas
    • 1
    • 2
  1. 1.Computer Technology InstitutePatrasGreece
  2. 2.Department of Computer Engineering and InformaticsUniversity of PatrasPatrasGreece

Personalised recommendations