Level Based Flooding for Node Search in Wireless Sensor Network

Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 145)

Abstract

In this paper, we pay attention to the problem of node search in Wireless Sensor Networks (WSNs). The main problem of basic flooding is that the cost is too high. In order to solve above problem, we propose a variant of Flooding called Level Based Flooding (LBF). In LBF, the whole network is divided into several layers according to the distance (hops) between the nodes and the sink node. The sink node knows the level information of each node. The search packet is broadcast in the network according to levels of nodes and its TTL is set to the level of the target node. When the target node receives the packet, it sends its data back to the sink node in random walk within level hops.We show by extensive simulations that the energy consumption of LBF is much better than that of basic flooding.

Keywords

Sensor Network Sensor Node Wireless Sensor Network Query Processing Sink Node 
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.

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References

  1. 1.
    Di Francesco, M., Shah, K., Kumar, M., Anastasi, G.: An Adaptive Strategy for Energy-Efficient Data Collection in Sparse Wireless Sensor Networks. In: Silva, J.S., Krishnamachari, B., Boavida, F. (eds.) EWSN 2010. LNCS, vol. 5970, pp. 322–337. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  2. 2.
    Sadagopan, N., Krishnamachari, B., Helmy, A.: The ACQUIRE mechanism for efficient querying in sensor networks. In: Proceedings of the 1st IEEE International Workshop on Sensor Network Protocols and Applications, pp. 149–155 (May 2003)Google Scholar
  3. 3.
    Chang, N.B., Liu, M.: Controlled flooding search in a large network. IEEE/ACM Transactions on Networking 15(2), 436–449 (2007)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Intanagonwiwat, C., Govindan, R., Estrin, D., Heidemann, J., Silva, F.: Directed diffusion for wireless sensor networking. IEEE/ACM Transactions on Networking 11(1), 2–16 (2003)CrossRefGoogle Scholar
  5. 5.
    Gehrke, J., Madden, S.: Query processing in sensor networks. IEEE Pervasive Computing 3(1), 46–55 (2004)CrossRefGoogle Scholar
  6. 6.
    Zuniga, M., Avin, C., Hauswirth, M.: Querying Dynamic Wireless Sensor Networks with Non-Revisiting Random Walks. In: Silva, J.S., Krishnamachari, B., Boavida, F. (eds.) EWSN 2010. LNCS, vol. 5970, pp. 49–64. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  7. 7.
    Nascimento, M.A., Alencar, R.A.E., Brayner, A.: Optimizing Query Processing in Cache-Aware Wireless Sensor Networks. In: Gertz, M., Ludäscher, B. (eds.) SSDBM 2010. LNCS, vol. 6187, pp. 60–77. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  8. 8.
    Huang, H., Hartman, J., Hurst, T.: Data-centric routing in sensor networks using biased walk. In: Proceedings of the 3rd IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks, pp. 1–9 (September 2006)Google Scholar
  9. 9.
    Ahn, J., Kapadia, S., Pattem, S., Sridharan, A., et al.: Empirical evaluation of querying mechanisms for unstructured wireless sensor networks. In: ACM SIGCOMM Computer Communication Review, vol. 38(3), pp. 17–26 (July 2008)Google Scholar
  10. 10.
    Cheng, Z., Heinzelman, W.: Flooding Strategy for Target Discovery in Wireless Networks. Wireless Networks 11(5), 607–618 (2005)MATHCrossRefGoogle Scholar
  11. 11.
    Avin, C., Brito, C.: Efficient and robust query processing in dynamic environments using random walk techniques. In: Proceedings of the 3rd International Symposium on Information Processing in Sensor Networks, pp. 277–286 (April 2004)Google Scholar
  12. 12.
    Braginsky, D., Estrin, D.: “Rumor Routing Algorithm For Sensor Networks. In: Proceedings of the 1st ACM International Workshop on Wireless Sensor Networks and Applications, pp. 22–30 (September 2002)Google Scholar
  13. 13.
    Khan, M., Gabor, A.: An Effective Compiler Design for Efficient Query Processing in Wireless Sensor Networks. In: Internal Conference on Circuit and Signal Processing, pp. 157–159 (November 2010)Google Scholar
  14. 14.
    Chakroaborty, A., Lahiri, K., Mandal, S., Patra, D., et al.: Optimization of Service Discovery in Wireless Sensor Networks. Wired/Wireless Internet Communications, 351–362 (June 2010)Google Scholar

Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  • Yanhong Ding
    • 1
  • Tie Qiu
    • 1
  • Honglian Ma
    • 1
  • Naigao Jin
    • 1
  1. 1.School of SoftwareDalian University of TechnologyDalianChina

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