Research article of American Journal of Computer Engineering
Enhancing Networks Lifetime Using Two-Step Uniform Clustering Algorithm (TSUC)
Vrince Vimal and Madhav J Nigam
Department of Electronics and Communication Engineering, Indian Institute of Technology, Roorkee, Uttarakhand, India
Wireless sensor networks have enticed lot of spotlight from researchers all around globe, owing to its wide applications in industrial, military and agricultural ﬁelds. Energy conservation and node deployment strategies play a paramount role for effective execution of Wireless Sensor Networks. Clustering of nodes in the wireless sensor networks is an approach commenced to achieve energy efﬁciency in the network. Clustering algorithm, if not executed properly can reduce life of the network. In this paper, a Two -Step Uniform Clustering (TSUC) algorithm has been proposed with the aim to provide connectivity to the nodes in every part of the network. This algorithm increases networks lifetime and throughput by re-clustering isolated nodes rather than providing them connectivity by already connected node. Results obtained after simulation showed that proposed TSUC algorithm performed better than the other existing clustering algorithm.
Keywords: WSN, Clustering Algorithm, TSUC, Networks lifetime
How to cite this article:
Vrince Vimal and Madhav J Nigam. Enhancing Networks Lifetime Using Two-Step Uniform Clustering Algorithm (TSUC). American Journal of Computer Engineering, 2018; 1:3. (This article has been withdrawn from American Journal of Computer Engineering)
1. Shih FY, Wu YT, undeﬁned J L Chen. A Smart Sensor Network for Object Detection, Classiﬁcation and Recognition Frank,. JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 23, 1955-1969 (2007). 2005;23:1955–1969.
2. Krysander M, Frisk E. Sensor Placement for Fault Diagnosis,. IEEE Trans Systems, Man Cybernetics Part A Systems and Hu-mans. 2008;38(6):1398–1410.
3. Rawat HCP, Bonnin JM. Wireless Sensor Networks: A Survey on Recent Develop-ments and Potential Synergies,. The Journal of Supercomputing. 2014;68(1):1–48.
4. Gola´nski M, Schoeneich RO, Zgid D, Fran-ciszkiewicz M, Kucharski M. RBCP-WSN: The Reliable Biderectional Control Proto-col for Wireless Sensor Networks,. Int Journal Electronics of Telecommunications. 2017;63(2):201–207.
5. He YGYP. A Comprehensive Survey on the Reliability of Mobile Wireless Sensor Net-works: Taxonomy, Challenges, and Future Directions,. Information Fusion. 2018;.
6. Newman MHR. Adaptive routing in wireless sensor networks: QoS optimisation for en-hanced application performance,. Inf Fusion. 2015;22:3–15.
7. Xu CCZ, Guan X. Joint Clustering and Rout-ing Design for Reliable and Efﬁcient Data Collection in Large-Scale Wireless Sensor Networks,. IEEE Internet of Things Journal. 2016;3(4):520–532.
8. Vimal V, Nigam MJ. Ensuring Uni-form Energy Consumption in Non- Deter-ministic Wireless Sensor Network to Pro-tract Networks Lifetime,. Int Journal of Electronics and Communication Engineering. 2017;11(9):966–970.
9. Lin CH, Tsai MJ. A Comment on ‘HEED: A Hybrid, Energy-Efﬁcient, Distributed clus-tering approach for ad hoc sensor net-works,’. IEEE Trans Mobile Computing. 2006;5(10):1471–1472.
10. Barboni L, Valle M. “Wireless Sensor Net-works Power-Aware Deployment,”. In: 2008 Second International Conference on Sensor Technologies and Applications (SENSOR-COMM 2008); 2008. p. 252–257.
11. Aznoli F, Navimipour NJ. Deployment Strategies in the Wireless Sensor Networks: Systematic Literature Review, Classiﬁcation, and Current Trends,. Wireless Personal Com-munications. 2017;95(2):819–846.
12. A Wireless Sensor Networks’ Analytics Sys-tem for Predicting Performance in On-Demand Deployments,. IEEE Systems Jour-nal. 2015;9(4):1344–1353.
13. Cherepanov A, Tyshchenko I, Popova M, Vakhnin D. Building Energy Efﬁcient Wire-less Sensor Networks,. International Jour-nal of Electronics and Telecommunications. 2017;63(1):45–49.
14. Luo RC, Chen O. Mobile Sensor Node Deployment and Asynchronous Power Man-agement for Wireless Sensor Networks,. IEEE Transactions on Industrial Electronics. 2012;59(5):2377–2385.
15. Abo-Zahhad M, Sabor N, Sasaki S, Ahmed SM. A Centralized Immune-Voronoi Deploy-ment Algorithm for Coverage Maximization and Energy Conservation in Mobile Wire-less Sensor Networks,. Information Fusion. 2016;30:36–51.
16. Xu CCZ, Guan X. Joint Clustering and Rout-ing Design for Reliable and Efﬁcient Data Collection in Large-Scale Wireless Sensor Networks,. IEEE Internet of Things Journal. 2016;3(4):520–532.
17. Sanz D. Wireless Sensor Networks for Plan-etary Exploration: Experimental Assessment of Communication and Deployment,. Ad-vances in Space Research. 2013;52(6):1029– 1046.
18. Sweidan HI, Havens TC. Coverage Optimiza-tion in a Terrain-Aware Wireless Sensor Net-work,. In: 2016 IEEE Congress on Evolution-ary Computation (CEC); 2016. p. 3687–3694
19. Putra EH, Hidayat R, undeﬁned Widyawan, undeﬁned I W Mustika. Energy-Efﬁcient Routing Based on Dynamic Programming for Wireless Multimedia Sensor Networks (WM-SNs),. International Journal of Electronics and Telecommunications. 2017;63(3):279– 283.
20. Sivathasan S, O′Brien D. Hybrid Radio and Optical Communications for Energy-efﬁcient Wireless Sensor Networks,. IETE Journal of Research. 2011;57(5):399.
21. Du T, Qu S, Liu F, undeﬁned Q Wang. An en-ergy efﬁciency semi-static routing algorithm for WSNs based on HAC clustering method,. Information Fusion. 2015;21(1):18–29.
22. Energy-Effective Relay Selection by Utilizing Spacial Diversity For Random Wireless Sen-sor Networks,. IEEE Communication Letters. 2013;17(10):1972–1975.
23. Javaid N. An energy-efﬁcient distributed clus-tering algorithm for heterogeneous WSNs,. Eurasip Journal of Wireless Commutation and Network. 2015;2015(1).
24. Kaur SP, Sharma M. Radially Optimized Zone-Divided Energy-Aware Wireless Sensor Networks (WSN) Protocol Using BA (Bat Algorithm),. IETE Journal of Research. 2015;61(2):170–179.
25. Heinzelman ACWR, Balakrishnan H. Energy-Efﬁcient Communication Protocol for Wireless Microsensor Networks,. In: Proceedings of the 33rd Hawaii International Conference on System Sciences – 2000. vol. 0; 2000. p. 3005–3014.
26. Qing QZL, Wang M. Design of a Distributed Energy-Efﬁcient Clustering Al-gorithm for Heterogeneous Wireless Sen-sor Networks,. Computer Communication. 2006;29(12):2230–2237.
27. Zhao L, Liang Q. Medium-Contention Based Energy-Efﬁcient Distributed Cluster-ing (MEDIC) for Wireless Sensor Networks,. International Journal of Distributed Sensor Networks, 3: 347–369, 2007. 2007;3(4):347– 369.
28. Leu MCYJS, Su KW. Energy Efﬁcient Clustering Scheme for Prolonging the life-time of Wireless Sensor Network with Iso-lated Nodes,. IEEE Communication Letters. 2015;19(2):259–262.
29. An Efﬁcient Centroid-Based Routing Proto-col for Energy Management in WSN-Assisted IoT,. IEEE Access. 2017;5:18469–18479.
30. Zhang XFJ, Liu Z. A Grid-based Clus-tering Algorithm via Load Analysis for In-dustrial Internet of Things,. IEEE Access. 2018;6:13117–13128.
31. Energy Aware Hierarchical Cluster-Based Routing Protocol for WSNs,. J China