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Reseach Article

Energy Efficient K-Means Clustering Technique for Underwater Wireless Sensor Network

by Sunpreet Kaur, Vinay Bhardwaj
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 145 - Number 4
Year of Publication: 2016
Authors: Sunpreet Kaur, Vinay Bhardwaj
10.5120/ijca2016910606

Sunpreet Kaur, Vinay Bhardwaj . Energy Efficient K-Means Clustering Technique for Underwater Wireless Sensor Network. International Journal of Computer Applications. 145, 4 ( Jul 2016), 43-47. DOI=10.5120/ijca2016910606

@article{ 10.5120/ijca2016910606,
author = { Sunpreet Kaur, Vinay Bhardwaj },
title = { Energy Efficient K-Means Clustering Technique for Underwater Wireless Sensor Network },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2016 },
volume = { 145 },
number = { 4 },
month = { Jul },
year = { 2016 },
issn = { 0975-8887 },
pages = { 43-47 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume145/number4/25270-2016910606/ },
doi = { 10.5120/ijca2016910606 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:47:55.815731+05:30
%A Sunpreet Kaur
%A Vinay Bhardwaj
%T Energy Efficient K-Means Clustering Technique for Underwater Wireless Sensor Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 145
%N 4
%P 43-47
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The communication range of underwater wireless sensor networks (UWSN) is limited by the underwater environment. Acoustic networks with huge number of sensors may have long communication range with appropriate protocols in literature. On the other hand, especially, the networks including small number of nodes have communication problems for long ranges. In energy constrained 3D underwater system environment it is essential to discover approaches to enhance the lifetime of the sensor nodes. Underwater sensors cannot utilize sunlight-based vitality to recharge the batteries. To challenge this problem, Multihop communication in underwater acoustic networks is a promising solution. In this study, a novel approach, Multihop Energy Efficient K-Means Clustering algorithm (MH-EKMC) is introduced and developed. The goal of this paper is to produce simulation results that would show the exhibitions of the proposed protocol for a given metric such as Network lifetime, No of dead nodes per round and total energy consumption. From the results, proposed protocol shows better performance for an energy-constrained network.

References
  1. Elhamifar E, Vidal R. Sparse subspace clustering: Algorithm, theory, and applications. Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 35, no.11, pp. 2765-2781, 2013.
  2. Hai Yan, Zhijie Jerry Shi, and Jun-Hong Cui “Depth-Based Routing for Underwater Sensor Networks” Department of Computer Science and Engineering University of Connecticut, Storrs, CT 06269-2155.
  3. Ibrahim D M, Eltobely T E, Fahmy M M, et al. Enhancing the Vector-Based Forwarding Routing Protocol for Underwater Wireless Sensor Networks: A Clustering Approach. ICWMC 2014, The Tenth International Conference on Wireless and Mobile Communications. pp. 98-104, 2014.
  4. Lalita Yadav et al, “Low Energy Adaptive Clustering Hierarchy in Wireless Sensor Network (LEACH)” (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 5 , 4661-4664, 2014.
  5. Mander Chitre, Shiraz Shahabudeen, “ Recent advances in underwater acoustic communication & networking” , International journal of soft computing , 2000.
  6. Manijeh Keshtgary, Reza Mohammadi ”Energy Consumption Estimation in Cluster based Underwater Wireless Sensor Networks Using M/M/1 Queuing Model ” International Journal of Computer Applications (0975 – 8887) Vol-43, No.24, April 2012.
  7. Mari Carmen Domingo,1 Rui Prior. “A Distributed clustering scheme for underwater wireless sensor networks”, The 18th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC'07) .
  8. Ms. Kalpana .S, Mr. Arutchelvan G “An Accoustic Sensor for Transmission in Underwater Environment ” International Research Journal of Engineering and Technology (IRJET) ,Vol-2,Aug-2015
  9. Sihem Souiki1, Mourad Hadjila1 and Mohammed Feham1”Fuzzzy Based Clustering And Energy Efficient Routing For Underwater Wireless Sensor Networks” International Journal of Computer Networks & Communications (IJCNC) Vol.7, No.2, March 2015.
  10. Syed Abdul Basit , Manoj Kumar “A Review of Routing Protocols for Underwater Wireless Sensor Networks” IJARCCE, Vol. 4, Issue 12, December 2015.
  11. Wang W, Yang J, Muntz R. STING: A statistical information grid approach to spatial data mining. VLDB. vol. 97, pp. 186-195, 1997.
  12. Xiaobing Wu , Guihai Chen “ A reliable and energy balanced routing algorithm for UWSNs” State Key Laboratory for Novel Software Technology Nanjing University ,Nov 2008.
  13. Xie P., Zhou Z., Peng Z., Cui J.-H., and Shi Z , “Void Avoidance in Three-dimensional Mobile Underwater Sensor Networks”, Proc. of the 4th international conference of wireless algorithms, system, and applications (WASA ), USA, 2009.
  14. Peng Jiang , Jun Liu, Feng Wu , Jianzhong Wang and Anke Xue “Node Deployment Algorithm for Underwater Sensor Networks Based on Connected Dominating Set”, Vol- 16, 2010.
Index Terms

Computer Science
Information Sciences

Keywords

Underwater Sensor Networks K-Means Clustering Energy Efficiency Network Lifetime Acoustic Communication