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A Data Aggregation Based Efficient Clustering Scheme in Underwater Wireless Sensor Networks

Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 280)

Abstract

The restricted underwater wireless sensor networks (UWSNs) such as large propagation delay, low bandwidth capacity, high bit error rates, mobility, limited memory as well as battery and so on pose many challenges for scientists doing UWSN construction. In this paper, we take into account of proposing a promised clustering scheme that can overcome the UWSN’s confined. Our proposed data aggregation based clustering scheme involves 4 phases: initial phase, cluster head election phase, clustering phase, and data aggregation phase. The main goals of our proposed include reducing the energy consumed of the overall network, increasing the throughput, and minimizing data redundancy while still guarantying data accuracy.

Keywords

Cluster Data Aggregation with Similarity Function Underwater Wireless Sensor Networks 

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References

  1. 1.
    Akyildiz, I.F., Pompili, D., Melodia, T.: Underwater acoustic sensor networks: research challenges. Ad Hoc Networks (Elsevier) 3, 257–279 (2005)CrossRefGoogle Scholar
  2. 2.
    Akyildiz, I.F., Pompili, D., Melodia, T.: State-of-the-art in protocol research for underwater acoustic sensor networks. In: Proceedings of the 1st ACM International Workshop on Underwater Networks (WUWNet 2006). ACM, New York (2006)Google Scholar
  3. 3.
    Akyildiz, I.F., Pompili, D., Melodia, T.: Challenges for Efficient Communication in Underwater Acoustic Sensor Networks. ACM Sigbed Review 1(2) (July 2004)Google Scholar
  4. 4.
    Domingo, M.C., Prior, R.: A Distributed Clustering Scheme for Underwater Wireless Sensor Networks. In: IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC 2007), pp. 1–5 (September 2007)Google Scholar
  5. 5.
    Manvi, S.S., Manjula, B.: Issues in underwater acoustic sensor networks. International Journal on Computer and Electrical Engineering 3(1), 101–111 (2011)Google Scholar
  6. 6.
    Yu, J.Y., Chong, P.H.J.: A survey of clustering schemes for mobile ad hoc networks. IEEE Communications Surveys & Tutorials 7(1), 32–48 (First Qtr. 2005)Google Scholar
  7. 7.
    Pu, W., Cheng, L., Jun, Z., Mouftah, H.T.: A Dependable Clustering Protocol for Survivable Underwater Sensor Networks. In: IEEE International Conference on Communications, pp. 3263–3268 (May 2008)Google Scholar
  8. 8.
    Manjula, R.B., Manvi, S.S.: Cluster based data aggregation in underwater acoustic sensor networks. 2012 Annual IEEE India Conference (INDICON), 104–109 (December 2012)Google Scholar
  9. 9.
    Salva-Garau, F., Stojanovic, M.: Multi-cluster protocol for ad hoc mobile underwater acoustic networks. In: Proceedings of the OCEANS 2003, vol. 1, pp. 91–98 (2003)Google Scholar
  10. 10.
    Yang, G., Xiao, M., Cheng, E., Zhang, J.: A Cluster-Head Selection Scheme for Underwater Acoustic Sensor Networks. In: International Conference on Communications and Mobile Computing (CMC), vol. 3, pp. 188–191 (April 2010)Google Scholar
  11. 11.
    Tran, K.T.-M., Oh, S.-H., Byun, J.-Y.: Well-Suited Similarity Functions for Data Aggregation in Cluster-Based Underwater Wireless Sensor Networks. International Journal of Distributed Sensor Networks 2013, Article ID 645243, 7 pages (2013)Google Scholar
  12. 12.
    Virmani, D., Sharma, T., Sharma, R.: Adaptive Energy Aware Data Aggregation Tree for Wireless Sensor Networks. International Journal of Hybrid Information Technology (IJHIT) 6(1), 25–36 (2013)Google Scholar
  13. 13.
    Maraiya, K., Kant, K., Gupta, N.: Wireless sensor network: A review on data aggregation. International Journal of Scientific and Engineering Research 2(4), 269–274 (2011)Google Scholar
  14. 14.
  15. 15.
    Tran, K.T.M., Oh, S.H.: A cooperative MAC scheduling scheme for underwater sensor networks. Applied Mechanics and Materials 295-298, 903–908 (2013)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  1. 1.Department of Computer ScienceDongguk UniversitySeoulSouth Korea

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