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Energy-Efficient Secure Adaptive Neuro Fuzzy Based Clustering Technique for Mobile Adhoc Networks

Maganti Srinivas*, M. Ramesh Patnaik

Department of Instrument Technology, A. U. College of Engineering, Andhra University, Visakhapatnam, Andhra Pradesh, 530003, India

* Corresponding Author: Maganti Srinivas. Email: email

Intelligent Automation & Soft Computing 2022, 34(3), 1755-1767. https://doi.org/10.32604/iasc.2022.026355

Abstract

In recent times, Mobile Ad Hoc Network (MANET) becomes a familiar research field owing to its applicability in distinct scenarios. MANET comprises a set of autonomous mobile nodes which independently move and send data through wireless channels. Energy efficiency is considered a critical design issue in MANET and can be addressed by the use of the clustering process. Clustering is treated as a proficient approach, which partitions the mobile nodes into groups called clusters and elects a node as cluster head (CH). On the other hand, the nature of wireless links poses security as a major design issue. Therefore, this paper proposes a non-probabilistic and energy-efficient secure adaptive neuro fuzzy-based clustering scheme (NPEE-SANFC) for MANET. The proposed NPEE-SANFC techniques elects CHs in two levels such as tentative CH election and final CH election. Besides, a non-probabilistic way of Tentative CH (TCH) selection takes place by the use of a back-off timer. In addition, ANFC technique is applied for the election of Final CH (FCH)s. The presented model involves a set of input parameters such as residual energy, intra-cluster distance, inter-cluster distance, and trust degree. The incorporation of the trust degree of the node enables to elect secure CHs. Furthermore, the application of two processes for optimal CH selection will result in enhanced network lifetime and energy efficiency. To validate the results regarding the effectiveness of the presented NPEE-SANFC technique, a set of experiments was performed; and the results were determined using distinct measures such as the energy consumption, network lifetime, throughput, and end-to-end delay.

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APA Style
Srinivas, M., Patnaik, M.R. (2022). Energy-efficient secure adaptive neuro fuzzy based clustering technique for mobile adhoc networks. Intelligent Automation & Soft Computing, 34(3), 1755-1767. https://doi.org/10.32604/iasc.2022.026355
Vancouver Style
Srinivas M, Patnaik MR. Energy-efficient secure adaptive neuro fuzzy based clustering technique for mobile adhoc networks. Intell Automat Soft Comput . 2022;34(3):1755-1767 https://doi.org/10.32604/iasc.2022.026355
IEEE Style
M. Srinivas and M.R. Patnaik, "Energy-Efficient Secure Adaptive Neuro Fuzzy Based Clustering Technique for Mobile Adhoc Networks," Intell. Automat. Soft Comput. , vol. 34, no. 3, pp. 1755-1767. 2022. https://doi.org/10.32604/iasc.2022.026355



cc Copyright © 2022 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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