Variable Density Deployment and Topology Control for the Solution of the Sink-Hole Problem

  • Novella Bartolini
  • Tiziana Calamoneri
  • Annalisa Massini
  • Simone Silvestri
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 22)


The use of mobile sensors is of great relevance to monitor critical areas where sensors cannot be deployed manually. The presence of data collector sinks causes increased energy depletion in their proximity, due to the higher relay load under multi-hop communication schemes (sink-hole phenomenon). We propose a new approach towards the solution of this problem by means of an autonomous deployment algorithm that guarantees the adaptation of the sensor density to the sink proximity and enables their selective activation.

The proposed algorithm also permits a fault tolerant and self-healing deployment, and allows the realization of an integrated solution for deployment, dynamic relocation and selective sensor activation.

Performance comparisons between our proposal and previous approaches show how the former can efficiently reach a deployment at the desired variable density with moderate energy consumption under a wide range of operative settings.


Mobile Sensor Topology Control Sensor Deployment Density Requirement Coverage Hole 
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.
    Wu, X., chen, G., Das, S.K.: On the energy hole problem of nonuniform node distribution in wireless sensor networks. IEEE Transactions on Parallel and Distributed System 19, 710–720 (2008)CrossRefGoogle Scholar
  2. 2.
    Li, J., Mohapatra, P.: Analytical modeling and mitigation techniques for the energy hole problem in sensor networks. In: Pervasive and Mobile Computing, pp. 233–254 (2007)Google Scholar
  3. 3.
    Olariu, S., Stojmenovic, I.: Design guidelines for maximizing lifetime and avoiding energy holes in sensor networks with uniform distribution and uniform reporting. In: Proceedings of INFOCOM (2006)Google Scholar
  4. 4.
    Bartolini, N., Calamoneri, T., Fusco, E., Massini, A., Silvestri, S.: Push & pull: autonomous deployment of mobile sensors for a complete coverage. ACM/Springer Wireless Networks (2009)Google Scholar
  5. 5.
    Zou, Y., Chakrabarty, K.: Sensor deployment and target localization based on virtual forces. In: Proc. IEEE INFOCOM (2003)Google Scholar
  6. 6.
    Heo, N., Varshney, P.: Energy-efficient deployment of intelligent mobile sensor networks. IEEE Transactions on Systems, Man and Cybernetics 35 (2005)Google Scholar
  7. 7.
    Chen, J., Li, S., Sun, Y.: Novel deployment schemes for mobile sensor networks. Sensors 7 (2007)Google Scholar
  8. 8.
    Poduri, S., Sukhatme, G.S.: Constrained coverage for mobile sensor networks. In: Proc. of IEEE ICRA (2004)Google Scholar
  9. 9.
    Pac, M.R., Erkmen, A.M., Erkmen, I.: Scalable self-deployment of mobile sensor networks; a fluid dynamics approach. In: Proc. of IEEE IROS (2006)Google Scholar
  10. 10.
    Kerr, W., Spears, D., Spears, W., Thayer, D.: Two formal fluid models for multi-agent sweeping and obstacle avoidance. In: Proc. of the Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS (2004)Google Scholar
  11. 11.
    Wang, G., Cao, G., Porta, T.L.: Movement-assisted sensor deployment. IEEE Transaction on Mobile Computing 6 (2006)Google Scholar
  12. 12.
    Ma, M., Yang, Y.: Adaptive triangular deployment algorithm for unattended mobile sensor networks. IEEE Transactions on Computers 56 (2007)Google Scholar
  13. 13.
    Garetto, M., Gribaudo, M., Chiasserini, C.F., Leonardi, E.: A distributed sensor relocation scheme for environmental control. In: The ACM/IEEE Proc. of MASS (2007)Google Scholar
  14. 14.
    Wu, X., Chen, G., Das, S.K.: On the energy hole problem of nonuniform node distribution in wireless sensor networks. In: Proc. of IEEE MASS, pp. 180–187 (2006)Google Scholar
  15. 15.
    Cardei, M., Yang, Y., Wu, J.: Non-uniform sensor deployment in mobile wireless sensor networks. In: Proc. of WoWMoM, pp. 1–8 (2008)Google Scholar
  16. 16.
    Wu, C., Verma, D.: A sensor placement algorithm for redundant covering based on riesz energy minimization. In: Proc. ISCAS (2007)Google Scholar
  17. 17.
    Wang, Y.C., Tseng, Y.C.: Distributed deployment schemes for mobile wireless sensor networks to ensure multilevel coverage. IEEE Transactions on Parallel and Distributed System 19 (2008)Google Scholar
  18. 18.
    Johnson, M., Sarioz, D., Bar-Noy, A., Brown, T., Verma, D., Wu, C.: More is more: the benefits of denser sensor deployment. In: Proc. INFOCOM (2009)Google Scholar
  19. 19.
    Wang, G., Cao, G., Porta, T.L., Zhang, W.: Sensor relocation in mobile sensor networks. In: Proc. of IEEE INFOCOM (2005)Google Scholar
  20. 20.
    Pattem, S., Poduri, S., Krishnamachari, B.: Energy-quality tradeoffs for target tracking in wireless sensor networks. In: Zhao, F., Guibas, L.J. (eds.) IPSN 2003. LNCS, vol. 2634, pp. 32–46. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  21. 21.
    Ma, K., Zhang, Y., Trappe, W.: Managing the mobility of a mobile sensor network using network dynamics. IEEE Transaction on Parallel and Distributed Systems 19, 106–120 (2008)CrossRefGoogle Scholar
  22. 22.
    Anastasi, G., Conti, M., Falchi, A., Gregori, E., Passarella, A.: Performance mea- surements of mote sensor networks. In: Proc. of ACM MSWiM 2004 (2004)Google Scholar

Copyright information

© ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering 2009

Authors and Affiliations

  • Novella Bartolini
    • 1
  • Tiziana Calamoneri
    • 1
  • Annalisa Massini
    • 1
  • Simone Silvestri
    • 1
  1. 1.Department of Computer Science“Sapienza” University of RomeItaly

Personalised recommendations