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Neural-Fuzzy based effective clustering for large-scale wireless sensor networks with mobile sink

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Abstract

This paper presents the versatile approach, called Neural-Fuzzy based Effective Clustering (NFEC), for Large-Scale wireless sensor network (WSN) with Mobile Sink. The proposed protocol NFEC presents the effectiveness of existing approaches with proposed NFEC in terms of stability period and network lifetime for homogeneous and heterogeneous network environment. The NFEC protocol utilizes the concept of Neural-Fuzzy based model to enhance the network performance while considering the effect of random waypoint mobility in Sink/Base Station. The nature of the proposed NFEC is adaptive and can be varied accordingly for homogeneous and heterogeneous scalable WSN. The simulations analyse the performance of NFEC protocol with existing protocols.

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Acknowledgments

The fuzzy data set used in the manuscript has been provided as supplementary material in the journal. The material includes the following details:

1. Fuzzy model as fuzzyproposed.fis file.

2. Fuzzy input data as input.m file.

3. Fuzzy output data as output.m file.

4. Comprehensive detail of fuzzy reasoning can also be found at- https://ieeexplore.ieee.org/abstract/document/8970479

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Authors and Affiliations

  1. Department of Electronics and communication Engineering, Motilal Nehru National Institute of Technology Allahabad, Allahabad, India

    Akshay Verma, Sunil Kumar, Prateek Raj Gautam & Arvind Kumar

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  1. Akshay Verma
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  2. Sunil Kumar
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  3. Prateek Raj Gautam
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  4. Arvind Kumar
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Correspondence to Akshay Verma.

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Verma, A., Kumar, S., Gautam, P.R. et al. Neural-Fuzzy based effective clustering for large-scale wireless sensor networks with mobile sink. Peer-to-Peer Netw. Appl. 14, 3518–3539 (2021). https://doi.org/10.1007/s12083-021-01167-6

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