Top

Arabian Journal for Science and Engineering

Published in:

09-08-2021 | Research Article-Computer Engineering and Computer Science

FEECS: Fuzzy-Based Energy-Efficient Cluster Head Selection Algorithm for Lifetime Enhancement of Wireless Sensor Networks

Authors: Ganesh Jayaraman, V. R. Sarma Dhulipala

Published in: Arabian Journal for Science and Engineering | Issue 2/2022

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

search-config

AI-assisted search

Off

Abstract

The wireless sensor network (WSN) infrastructure is deployed with sensor nodes that are used to collect the sensed information and transmit to the central station, namely base station. The power limitations of sensors are commonly known in WSN. Due to limitation in power supply, energy utilization becomes a challenge in the networks. Various categories of protocols have been developed and addressed the energy issues, but the longevity of network lifetime is a crucial factor. In this paper, fuzzy-based energy-efficient cluster head selection algorithm is introduced to prolong the network lifetime. While the formation of the cluster, k-means algorithm is used to form a cluster in an efficient way and cluster head is selected based on fuzzy logic system. Simulation results show the proposed algorithm outperforms the existing algorithms.

previous article Convalescing the Process of Ranking Metabolites for Diseases using Subcellular Localization

next article A Simple, Precise, and High-Speed Die Edge Detection Framework Based on Improved K-Mean and Landscape Analysis for the Semiconductor Industry

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

Yi, D.; Yang, H.: HEER—A delay-aware and energy-efficient routing protocol for wireless sensor networks. Comput. Netw. 104, 155–173 (2016). https://doi.org/10.1016/j.comnet.2016.04.022CrossRef

Pour, S.E.; Javidan, R.: A new energy aware cluster head selection for LEACH in wireless sensor networks. IET Wirel. Sensor Syst. (2021). https://doi.org/10.1049/wss2.12007

Agrawal, D.; Pandey, S.: FUCA: Fuzzy-based unequal clustering algorithm to prolong the lifetime of wireless sensor networks. Int. J. Commun. Syst. 31, 1–18 (2018). https://doi.org/10.1002/dac.3448CrossRef

Ar-Reyouchi, E.M.; Chatei, Y.; Ghoumid, K.; Hammouti, M.; Hajji, B.: Efficient coding techniques algorithm for cluster-heads communication in wireless sensor networks. AEU Int. J. Electron. Commun. 82, 294–304 (2017). https://doi.org/10.1016/j.aeue.2017.08.047CrossRef

Alia, O.M.D: Dynamic relocation of mobile base station in wireless sensor networks using a cluster-based harmony search algorithm. Inf. Sci. (NY). 385–386, 76–95 (2017). https://doi.org/10.1016/j.ins.2016.12.046

Muthukumaran, K.; Chitra, K.; Selvakumar, C.: An energy efficient clustering scheme using multilevel routing for wireless sensor network. Comput. Electr. Eng. 69, 642–652 (2018). https://doi.org/10.1016/j.compeleceng.2017.10.007CrossRef

Sirdeshpande, N.; Udupi, V.: Fractional lion optimization for cluster head-based routing protocol in wireless sensor network. J. Frankl. Inst. 354, 4457–4480 (2017). https://doi.org/10.1016/j.jfranklin.2017.04.005MathSciNetCrossRefMATH

Xiao, X.; Tang, B.; Deng, L.: High accuracy synchronous acquisition algorithm of multi-hop sensor networks for machine vibration monitoring. Meas. J. Int. Meas. Confed. 102, 10–19 (2017). https://doi.org/10.1016/j.measurement.2017.01.036CrossRef

Sabor, N.; Abo-zahhad, M.; Sasaki, S.; Ahmed, S.M.: An unequal multi-hop balanced immune clustering protocol. Appl. Soft Comput. J. (2016). https://doi.org/10.1016/j.asoc.2016.02.016

10.

Baradaran, A.A.; Navi, K.: HQCA-WSN: High-quality clustering algorithm and optimal cluster head selection using fuzzy logic in wireless sensor networks. Fuzzy Sets Syst. 389, 114–144 (2020). https://doi.org/10.1016/j.fss.2019.11.015MathSciNetCrossRef

11.

Forero, P.A.; Cano, A.; Giannakis, G.B.: Distributed clustering using wireless sensor networks. IEEE J. Sel. Top. Signal Process. 5, 707–724 (2011)CrossRef

12.

Alam, S.; Dobbie, G.; Koh, Y.S.; Riddle, P.; Ur Rehman, S.: Research on particle swarm optimization based clustering: A systematic review of literature and techniques. Swarm Evol. Comput. 17, 1–13 (2014). https://doi.org/10.1016/j.swevo.2014.02.001CrossRef

13.

Neamatollahi, P.; Naghibzadeh, M.: Distributed unequal clustering algorithm in large-scale wireless sensor networks using fuzzy logic. J. Supercomput. 74, 2329–2352 (2018). https://doi.org/10.1007/s11227-018-2261-5CrossRef

14.

Logambigai, R.; Ganapathy, S.; Kannan, A.: Energy-effi cient grid-based routing algorithm using intelligent fuzzy rules for wireless sensor networks. Comput. Electr. Eng. 68, 62–75 (2018). https://doi.org/10.1016/j.compeleceng.2018.03.036CrossRef

15.

Abbasi, A.A.: A survey on clustering algorithms for wireless sensor networks. Comput. Commun. 30, 2826–2841 (2007). https://doi.org/10.1016/j.comcom.2007.05.024CrossRef

16.

Liu, X.: Atypical Hierarchical routing protocols for wireless sensor networks: a review. IEEE Sens. J. 15, 5372–5383 (2015). https://doi.org/10.1109/JSEN.2015.2445796CrossRef

17.

Ng, A.Y.; Jordan, M.I.: On spectral clustering: analysis and an algorithm. In: Int. Advances in Neural Information Processing Systems, pp. 849–856 (2002)

18.

Mazumdar, N.; Om, H.: Distributed fuzzy approach to unequal clustering and routing algorithm for wireless sensor networks. Int. J. Commun. Syst. (2018). https://doi.org/10.1002/dac.3709

19.

Leu, J.; Chiang, T.; Yu, M.; Su, K.: Energy efficient clustering scheme for prolonging the lifetime of wireless sensor network with isolated nodes. IEEE Commun. Lett. 19, 259–262 (2015)CrossRef

20.

Baranidharan, B.; Santhi, B.: DUCF: Distributed load balancing unequal clustering in wireless sensor networks using fuzzy approach. Appl. Soft Comput. J. 40, 495–506 (2016). https://doi.org/10.1016/j.asoc.2015.11.044CrossRef

21.

Mehra, P.S.; Doja, M.N.; Alam, B.: Fuzzy based enhanced cluster head selection (FBECS) for WSN. J. King Saud Univ. Sci. 32, 390–401 (2020). https://doi.org/10.1016/j.jksus.2018.04.031CrossRef

22.

Hamzah, A.; Shurman, M.; Al-Jarrah, O.; Taqieddin, E.: Energy-efficient fuzzy-logic-based clustering technique for hierarchical routing protocols in wireless sensor networks. Sensors (Switzerland) 19, 14–16 (2019). https://doi.org/10.3390/s19030561CrossRef

23.

Bayrakdar, M.E.: Energy-efficient technique for monitoring of agricultural areas with terrestrial wireless sensor networks. J. Circuits Syst. Comput. 29, 1–17 (2020). https://doi.org/10.1142/S0218126620501418

24.

Parwekar, P.; Reddy, R.: An efficient fuzzy localization approach in wireless sensor networks. IEEE Int. Conf. Fuzzy Syst. (2013). https://doi.org/10.1109/FUZZ-IEEE.2013.6622548CrossRef

25.

Bayrakdar, M.E.: Enhancing sensor network sustainability with fuzzy logic based node placement approach for agricultural monitoring. Comput. Electron. Agric. 174, 105461 (2020). https://doi.org/10.1016/j.compag.2020.105461CrossRef

26.

Bayrakdar, M.E.: Cooperative communication based access technique for sensor networks. Int. J. Electron. 107, 212–225 (2020). https://doi.org/10.1080/00207217.2019.1636313CrossRef

Title: FEECS: Fuzzy-Based Energy-Efficient Cluster Head Selection Algorithm for Lifetime Enhancement of Wireless Sensor Networks
Authors: Ganesh Jayaraman
V. R. Sarma Dhulipala
Publication date: 09-08-2021
Publisher: Springer Berlin Heidelberg
Published in: Arabian Journal for Science and Engineering / Issue 2/2022
Print ISSN: 2193-567X
Electronic ISSN: 2191-4281
DOI: https://doi.org/10.1007/s13369-021-06030-7

Springer Professional

Abstract

Please log in to get access to your license.

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

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Other articles of this Issue 2/2022

A Non-Probabilistic Neutrosophic Entropy-Based Method For High-Order Fuzzy Time-Series Forecasting

A Simple, Precise, and High-Speed Die Edge Detection Framework Based on Improved K-Mean and Landscape Analysis for the Semiconductor Industry

A Severity-Based Classification Assessment of Code Smells in Kotlin and Java Application

The Archerfish Hunting Optimizer: A Novel Metaheuristic Algorithm for Global Optimization

Novel Arabic e-Text Watermarking Supporting Partial Dishonesty Based on Counting-Based Secret Sharing

COLCONF: Collaborative ConvNet Features-based Robust Visual Place Recognition for Varying Environments

Premium Partners