Indian Journal of Education and Information Management

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Improved Fuzzy Logic Based Clustering Algorithm for Enhancing the Lifetime of Wireless Sensor Network


Affiliations
1 Dept. of Information Technology, Govt Arts College, Coimbatore-641018, Tamil Nadu, India
 

Objectives: The major objective is enhancing the network lifetime and overall performance of the system and reducing the energy consumption of the nodes by using Improved Fuzzy Logic based Clustering (IFLC) algorithm.

Methods: In this paper, a Sugeno-type Fuzzy Inference based Clustering (SFIC) algorithm is proposed along with regression based threshold estimation for improving the network lifetime as well as reducing the energy consumption.

Findings: In wireless sensor networks (WSN), the sensor nodes are densely arranged in an aggressive environment for monitoring, detecting, and analyzing the physical phenomenon and large amount of energy is consumed during information transmission. Therefore, the replacement of battery is not possible regularly and maintaining the network lifetime is also difficult. Hence, these issues are the major challenges in WSN.

Applications/improvements: The experimental results show that the proposed sugeno-type fuzzy inference system based clustering algorithm has better performance than the other clustering algorithms.


Keywords

Wireless Sensor Network, Fuzzy Logic Clustering, Sugeno-Type Fuzzy Inference, Regression Based Threshold Estimation.
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  • S. Zairi, B. Zouari, E. Niel, E. Dumitrescu. Nodes self-scheduling approach for maximising wireless sensor network lifetime based on remaining energy. IET Wireless Sensor Systems.2012; 2(1), 52-62.

  • T. Shankar, T. James, R. Mageshvaran, A. Rajesh. Lifetime Improvement in WSN using Flower Pollination Meta Heuristic Algorithm Based Localization Approach. Indian Journal of Science and Technology.2016; 9(37), 1-10 .

  • P. Nayak, A. Devulapalli. A fuzzy logic-based clustering algorithm for WSN to extend the network lifetime. IEEE Sensors Journal. 2016; 16(1), 137-144.

  • S. Srividhya, V. Ganapathy, V. Rajaram. Fuzzy based hierachicalunequal clustering in wireless sensor networks. Indian Journal of Science and Technology, 2016; 9(37), 1-7.

  • H. Taheri, P. Neamatollahi, O.M. Younis, S. Naghibzadeh, M.H. Yaghmaee. An energy-aware distributed clustering protocol in wireless sensor networks using fuzzy logic. Ad Hoc Networks. 2012; 10(7), 1469-1481.

  • A. Alkesh, A.K. Singh, N. Purohit. A moving base station strategy using fuzzy logic for lifetime enhancement in wireless sensor network. Communication Systems and Network Technologies (CSNT), 2011 International Conference, IEEE. 2011, 198-202.

  • T. Sharma, B. Kumar. F-MCHEL: fuzzy based master cluster head election leach protocol in wireless sensor network. International Journal of Computer Science and Telecommunications. 2012; 3(10), 8-13.

  • Z. W. Siew, C.F. Liau, A. Kiring, M.S. Arifianto, K.T.K. Teo. Fuzzy logic based cluster head election for wireless sensor network. Proceedings of 3rd CUTSE International Conference. Malaysia. 2011; 301-306.

  • G. Ran, H. Zhang, S. Gong. Improving on LEACH protocol of wireless sensor networks using fuzzy logic. Journal of Information & Computational Science. 2010; 7(3), 767-775.

  • Z. Arabi. HERF: A hybrid energy efficient routing using a fuzzy method in wireless sensor networks. Intelligent and Advanced Systems (ICIAS), 2010 International Conference, IEEE. 2010, 1-6.

  • Y.C. Wang, F.J. Wu, Y.C. Tseng. Mobility management algorithms and applications for mobile sensor networks. Wireless Communications and Mobile Computing. 2012; 12(1), 7-21.

  • A.M. Saravanan, C.J. Venkateswaran. Clustering technique using K-means Dempster-shafer theory of evidence. Indian Journal of Education and Information Management.2012; 1(5), 223-227.


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  • Improved Fuzzy Logic Based Clustering Algorithm for Enhancing the Lifetime of Wireless Sensor Network

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Authors

K. Nithyadevi
Dept. of Information Technology, Govt Arts College, Coimbatore-641018, Tamil Nadu, India
S. Radhapriya
Dept. of Information Technology, Govt Arts College, Coimbatore-641018, Tamil Nadu, India

Abstract


Objectives: The major objective is enhancing the network lifetime and overall performance of the system and reducing the energy consumption of the nodes by using Improved Fuzzy Logic based Clustering (IFLC) algorithm.

Methods: In this paper, a Sugeno-type Fuzzy Inference based Clustering (SFIC) algorithm is proposed along with regression based threshold estimation for improving the network lifetime as well as reducing the energy consumption.

Findings: In wireless sensor networks (WSN), the sensor nodes are densely arranged in an aggressive environment for monitoring, detecting, and analyzing the physical phenomenon and large amount of energy is consumed during information transmission. Therefore, the replacement of battery is not possible regularly and maintaining the network lifetime is also difficult. Hence, these issues are the major challenges in WSN.

Applications/improvements: The experimental results show that the proposed sugeno-type fuzzy inference system based clustering algorithm has better performance than the other clustering algorithms.


Keywords


Wireless Sensor Network, Fuzzy Logic Clustering, Sugeno-Type Fuzzy Inference, Regression Based Threshold Estimation.

References