Network Lifetime and Throughput Analysis in Wireless Sensor Networks Using Fuzzy Logic

Author(s): Hradesh Kumar, Pradeep K. Singh*

Journal Name: Recent Advances in Electrical & Electronic Engineering
Formerly Recent Patents on Electrical & Electronic Engineering

Volume 13 , Issue 2 , 2020


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Graphical Abstract:


Abstract:

Background: Currently, Wireless sensor networks are the most prominent area in research. Energy consumption is one of the important challenges in wireless sensor networks.

Objective: The objective of this paper is to increase the network lifetime and throughput of the wireless sensor network.

Methods: The fuzzy logic approach is used to improve the network lifetime and throughput. The proposed approach gave better results in comparison to existing approaches of Low Energy Fuzzy Based Unequal Clustering Multi-hop Architecture (LEFUCMA) and Low Energy Adaptive Unequal Clustering Using Fuzzy C-Means (LAUCF).

Results: The proposed approach is 11.39 % better in terms of network lifetime in comparison to LEFUCMA and 34.27 % in terms of network lifetime in comparison to LAUCF.

Conclusion: The proposed approach is 34.29 % better in terms of network throughput as a comparison of LEFUCMA and 112.85 % in terms of network throughput in comparison to LAUCF.

Keywords: Wireless Sensor Networks, network lifetime, throughput, fuzzy logic, energy efficiency, fuzzy logic system.

[1]
G.S. Tomar, T. Sharma, and B. Kumar, "Fuzzy based ant colony optimization approach for wireless sensor network", Wirel. Pers. Commun., vol. 84, no. 1, pp. 361-375, 2015.
[2]
M. Toloueiashtian, and H. Motameni, "A new clustering approach in wireless sensor networks using fuzzy system", J. Supercomput., vol. 74, no. 2, pp. 717-737, 2018.
[3]
Y.K. Tamandani, and M.U. Bokhari, "SEPFL routing protocol based on fuzzy logic control to extend the lifetime and throughput of the wireless sensor network", Wirel. Netw., vol. 22, no. 2, pp. 647-653, 2016.
[4]
N.T. Tam, and D.T. Hai, "Improving lifetime and network connections of 3D wireless sensor networks based on fuzzy clustering and particle swarm optimization", Wirel. Netw., vol. 24, no. 5, pp. 1477-1490, 2018.
[5]
A. Sureshkumar, and R.S. Ravindran, "Swarm and fuzzy based cooperative caching framework to optimize energy consumption over multimedia wireless sensor networks", Wirel. Pers. Commun., vol. 90, no. 2, pp. 961-984, 2016.
[6]
H. Kumar, and P.K. Singh, "Node energy based approach to improve network lifetime and throughput in wireless sensor networks", J. Telecommun. Electron. Comput. Eng., vol. 9, pp. 79-88, 2017.
[7]
H. Kumar, and P.K. Singh, "Comparison and analysis on artificial intelligence based data aggregation techniques in wireless sensor networks", Procedia Comput. Sci., vol. 132, pp. 498-506, 2018.
[8]
H. Kumar, and P.K. Singh, "Analyzing data aggregation in wireless sensor networks", 4th International Conference on Computing for Sustainable Global Development INDIACom, pp. 4024-4029. 2017
[9]
N. Baccar, and R. Bouallegue, "Interval type 2 fuzzy localization for wireless sensor networks", EURASIP J. Adv. Sig. Process. Vol.2016, no. 1, 2016.
[10]
N. Abdolmaleki, M. Ahmadi, H.T. Malazi, and S. Milardo, "Fuzzy topology discovery protocol for SDN-based wireless sensor networks", Simul. Model. Pract. Theory, vol. 79, pp. 54-68, 2017.
[11]
D.R.D. Adhikary, and D.K. Mallick, "A congestion aware, energy efficient, on demand fuzzy logic based clustering protocol for multi-hop wireless sensor networks", Wirel. Pers. Commun., vol. 97, no. 1, pp. 1445-1474, 2017.
[12]
"R. Dutta, S. Gupta, M.K. Das,Low-energy adaptive unequal clustering protocol using fuzzy c-means in wireless sensor networks", Wirel. Pers. Commun., vol. 79, no. 2, pp. 1187-1209, 2014.
[13]
S. Gajjar, M. Sarkar, K. Dasgupta, and D. Chaniyara, "Low energy fuzzy based unequal clustering multihop architecture for wireless sensor networks", In: Proceedings of the National Academy of Sciences,India Section A: Physical Sciences,, Vol. 88, no. 4, pp. 539-556, 2018.
[14]
E.G. Julie, and S. Tamilselvi, "CDS-fuzzy opportunistic routing protocol for wireless sensor networks", Wirel. Pers. Commun., vol. 90, no. 2, pp. 903-922, 2016.
[15]
Y.H. Robinson, E.G. Julie, S. Balaji, and A. Ayyasamy, "Energy aware clustering scheme in wireless sensor network using neuro-fuzzy approach", Wirel. Pers. Commun., vol. 95, no. 2, pp. 703-721, 2017.
[16]
A. Jain, and B.R. Reddy, "A novel method of modeling wireless sensor network using fuzzy graph and energy efficient fuzzy based k-hop clustering algorithm", Wirel. Pers. Commun., vol. 82, no. 1, pp. 157-181, 2015.
[17]
K. Koosheshi, and S. Ebadi, Optimization energy consumption with multiple mobile sinks using fuzzy logic in wireless sensor networks. Wirel. Netw., 1-20.
[18]
S. Mao, C. Zhao, Z. Zhou, and Y. Ye, "An improved fuzzy unequal clustering algorithm for wireless sensor network", Mob. Netw. Appl., vol. 18, no. 2, pp. 206-214, 2013.
[19]
M. Mirzaie, and S.M. Mazinani, MACHFL-FT: A fuzzy logic based energy-efficient protocol to cluster heterogeneous nodes in wireless sensor networks. Wirel. Netw., pp. 1-13.
[20]
P. Neamatollahi, and M. Naghibzadeh, "Distributed unequal clustering algorithm in large-scale wireless sensor networks using fuzzy logic", J. Supercomput., vol. 74, no. 6, pp. 2329-2352, 2018.
[21]
N. Nokhanji, Z.M. Hanapi, S. Subramaniam, and M.A. Mohamed, "An energy aware distributed clustering algorithm using fuzzy logic for wireless sensor networks with non-uniform node distribution", Wirel. Pers. Commun., vol. 84, no. 1, pp. 395-419, 2015.
[22]
A.M. Ortiz, F. Royo, T. Olivares, J.C. Castillo, L. Orozco-Barbosa, and P.J. Marron, "Fuzzy-logic based routing for dense wireless sensor networks", Telecomm. Syst., vol. 52, no. 4, pp. 2687-2697, 2013.
[23]
S. Phoemphon, C.S. In, and T.G. Nguyen, "An enhanced wireless sensor network localization scheme for radio irregularity models using hybrid fuzzy deep extreme learning machines", Wirel. Netw., vol. 24, no. 3, pp. 799-819, 2018.
[24]
G. Sharma, and A. Kumar, "Fuzzy logic based 3D localization in wireless sensor networks using invasive weed and bacterial foraging optimization", Telecomm. Syst., vol. 67, no. 2, pp. 149-162, 2018.
[25]
S. Singh, S. Chand, and B. Kumar, "Multilevel heterogeneous network model for wireless sensor networks", Telecomm. Syst., vol. 64, no. 2, pp. 259-277, 2017.
[26]
S. Singh, "“Energy efficient multilevel network model for heterogeneous WSNs”, Eng. Sci. Technol", Int. J., vol. 20, no. 1, pp. 105-115, 2017.


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Article Details

VOLUME: 13
ISSUE: 2
Year: 2020
Published on: 26 April, 2020
Page: [227 - 235]
Pages: 9
DOI: 10.2174/2352096512666190212152631
Price: $25

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