Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Detection and Prevention of DDoS Attacks in Wireless Sensor Networks Read chapter Read first chapter

2018 | OriginalPaper | Chapter

EKMT-k-Means Clustering Algorithmic Solution for Low Energy Consumption for Wireless Sensor Networks Based on Minimum Mean Distance from Base Station

Authors : Bindiya Jain, Gursewak Brar, Jyoteesh Malhotra

Published in: Networking Communication and Data Knowledge Engineering

Publisher: Springer Singapore

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

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.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter NS2 Based Structured Network Attack Scrutiny in MANET
next chapter A Review of FIR Filter Designs
Literature
1.
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.
2.
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.
3.
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.
4.
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.
5.
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.
6.
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.
7.
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.
8.
TejalIrkhede and P. Jaini, “Cluster and Traffic Distribution Protocol for Energy consumption in Wireless Sensor Network”, 2013 IEEE.
9.
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.
10.
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.
11.
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,.
12.
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.
13.
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.
14.
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.
15.
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.
16.
J. N. AL-Karaki and A. E. Kamal, “Routing techniques in wireless sensor networks: survey,” IEEE Wireless Communication, 2004, vol. 1, pp. 6–28.
17.
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.
18.
A. Abbasiand, M. Younis: “A survey on clustering algorithms for wireless sensor networks,” Computer Communication 2007, vol. 30, pp. 2826–2841.
19.
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.
20.
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.
21.
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.
22.
A. Paulraj, R. Nabar, and D. Gore, “Introduction to Space-Time Wireless Communications”, Cambridge, U.K., Cambridge Univ. Press, 2003.
Metadata
Title
EKMT-k-Means Clustering Algorithmic Solution for Low Energy Consumption for Wireless Sensor Networks Based on Minimum Mean Distance from Base Station
Authors
Bindiya Jain
Gursewak Brar
Jyoteesh Malhotra
Copyright Year
2018
Publisher
Springer Singapore
Book
Networking Communication and Data Knowledge Engineering

Print ISBN: 978-981-10-4584-4

Electronic ISBN: 978-981-10-4585-1

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-981-10-4585-1_10