Abstract
EKMT-k-means clustering algorithmic solution is one of the well known methods among all the partition based algorithms to partition a data set into group of patterns. This paper presents an energy efficient k-means clustering algorithm named EKMT which is based on concept of finding the cluster head minimizing the sum of squared distances between the closest cluster centers and member nodes and also considers the minimum distance between cluster heads and base station. In the proposed protocol the effort was made to improve the energy efficiency of the protocol by re-selecting the cluster head among the most possible cluster heads on the basis of the least distance between new selected cluster head and the base station thus improves throughput and delay.
References
W. Heinzelman, A. Chandrakasan, and H. Balakrishnan, “Energy-Efficient Communication Protocols for Wireless Micro sensor Networks (LEACH)” in HICSS, vol. 8, Maui, Hawaii, January 2003, pp. 1–10.
V. Pal, G. Singh and R. P. Yadav, “SCHS: Smart Cluster Head Selection Scheme for Clustering Algorithms in wireless Sensor Networks” Wireless Sensor Network, 4, 2012, pp. 273–280.
Y. Zhu, W W-d, J. Pan and T y-P, “An energy efficient data gathering algorithm to prolong lifetime of wireless sensor networks,” Comput. Commun. 33, 2010 pp. 639–647.
S. Gao, H. Zhang and S. Dass, “Efficient data collection in wireless sensor networks with path – constrained mobile sinks,” IEEE TRANS. Mob. comput. 10, 2011, pp. 592–608.
P. Bawa, B. Singh and V. Shokeen “Enhancement in Leach Protocol for Wireless Sensor Networks.” International Journal of Computer Applications (0975 – 8887), July 2013, Volume 74– No. 21.
J. Hu, Y. Jin, and L. Dou, “A Time-based Cluster-Head Selection Algorithm for LEACH,” IEEE Symposium on Computers and Communications, 2008, pp. 1172–1176.
H. Yang and B. Sikdar, “Optimal Cluster Head Selection in the LEACH Architecture”, IEEE International Conference on performance, Computing, and Communications, 2007, pp 93–100.
TejalIrkhede and P. Jaini, “Cluster and Traffic Distribution Protocol for Energy consumption in Wireless Sensor Network”, 2013 IEEE.
H. Yang and B. Sikdar, “Optimal Cluster Head Selection in the LEACH Architecture”, IEEE International Conference on Performance, Computing, and Communications, pp 93–100, 2007.
M. Usha and N. Sankarram, “A Survey on Energy Efficient Hierarchical (Leach) Clustering Algorithms in Wireless Sensor Network”, International Journal of Innovative Research in Computer and Communication Engineering ISO 3297: 2007.
O. Younis, S. Fahmy, “HEED: A hybrid, energy-efficient, distributed clustering approach for adhoc sensor networks.” IEEE Trans. Mobile Comput., Vol. 3, 2004, pp 366–379,.
P. A. Forero, A. Cano, and G. B. Giannakis, “Distributed Clustering using Wireless sensor networks”, IEEE Journal of selected topics in signal processing, August 2011, Vol 5, No. 4.
G. Y. Park, H. Kim, H. W. Jeong, and H. Y Youn, “A Novel Cluster Head Selection Method based on K-Means Algorithm for Energy Efficient Wireless Sensor Network”, 27th International Conference on Advanced Information Networking and Applications Workshops, 2013.
Y. Gong, G. Chen and L. Tan. “A Balanced serial K-means based clustering protocol for wireless sensor networks”, Oct. 2008, IEEE. pp 1–6.
S. Rani, J. Malhotra, R. Talwar, “Energy Efficient Chain based co-operative routing protocol for wireless sensor networks” Elsevier, Journal Applied Soft computing, Oct. 2015, pp. 1568–4946.
J. N. AL-Karaki and A. E. Kamal, “Routing techniques in wireless sensor networks: survey,” IEEE Wireless Communication, 2004, vol. 1, pp. 6–28.
W. B. Heinzelman, A. P. Chandrakasan, and H. Balakrishnan, “An application- specific protocol architecture for wireless microsensor networks,” IEEE Transactions on Wireless Networking, vol. 1, 2002, pp. 660–670.
A. Abbasiand, M. Younis: “A survey on clustering algorithms for wireless sensor networks,” Computer Communication 2007, vol. 30, pp. 2826–2841.
S. Rani, J. Malhotra, R. Talwar, “On the Development of Realistic Cross Layer Communication Protocol for Wireless Sensor Networks,” Sensor Network, 2014, 6, 57–66.
W. Yang, W. Shuan, X. Gfeng, W. Fan, G. Chen “Minimizing mobile sensor movements to form a line K-coverage,” Peer-to-Peer Netw. Appl., published online 2015, doi:10.1007/s12083-016-0469-9.
G Nidhi, S Sanjeev, V Renu, “Energy-efficient mobile cluster-head data collection model for wireless sensor networks.” Turk J Elec Eng & Comp Sci 2016 24: 3448–3458 doi:10.3906/elk-1406-155.
A. Paulraj, R. Nabar, and D. Gore, “Introduction to Space-Time Wireless Communications”, Cambridge, U.K., Cambridge Univ. Press, 2003.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Jain, B., Brar, G., Malhotra, J. (2018). EKMT-k-Means Clustering Algorithmic Solution for Low Energy Consumption for Wireless Sensor Networks Based on Minimum Mean Distance from Base Station. In: Perez, G., Mishra, K., Tiwari, S., Trivedi, M. (eds) Networking Communication and Data Knowledge Engineering. Lecture Notes on Data Engineering and Communications Technologies, vol 3. Springer, Singapore. https://doi.org/10.1007/978-981-10-4585-1_10
Download citation
DOI: https://doi.org/10.1007/978-981-10-4585-1_10
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-10-4584-4
Online ISBN: 978-981-10-4585-1
eBook Packages: EngineeringEngineering (R0)