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Energy-Efficient Clustering-Based Byzantine Fault Tolerance Algorithm in Manet (EECBFT)
Subject area: Science,Engineering and Technology · Area of research: Computer Networks
Abstract
Mobile Ad-Hoc Networks (MANETs) have witnessed significant growth, driven by the proliferation of wireless-enabled portable devices. This article explores critical aspects of MANETs, including cluster formation, fault tolerance, and the innovative concept of Energy-Based Byzantine Fault Tolerance (BFT). Cluster formation is essential for efficient communication and resource management in MANETs. This article delves into proximity-based clustering, node distance calculation, and cluster head election to create robust communication structures. Fault tolerance is paramount in MANETs, where node failures can occur due to various factors. Clustering-based fault tolerance is discussed, emphasizing fault detection, isolation, and redundancy to ensure network resilience. The article introduces the concept of Energy-Based Byzantine Fault Tolerance (BFT) as a novel approach to address the unique challenges of MANETs. Energy-aware strategies are integrated with Byzantine Fault Tolerance to enhance network reliability and energy efficiency. The Energy-Based BFT algorithm aims to optimize cluster formation, Byzantine fault tolerance, energy-efficient communication, dynamic energy management, energy-aware quorum selection, fault detection with energy conservation, and head election based on energy reserves. The expected outcomes of this research include developing and validating the Energy-Based BFT algorithm, tailored for MANET clustering, to improve fault tolerance, energy efficiency, and network reliability. The article highlights the promising potential of Energy-Based BFT in fortifying MANETs against malicious attacks while extending their operational lifespan. Further research and empirical evaluations are suggested to fully understand its practical implications.
Keywords
MANET, Fault tolerance, BFT, Energy Efficiency
How to cite this paper
@article{1705101,
author = {A. Mahendran, Dr. C. Kavitha, Dr. K. Sakthivel},
title = {Energy-Efficient Clustering-Based Byzantine Fault Tolerance Algorithm in Manet (EECBFT)},
journal = {Iconic Research And Engineering Journals},
year = {2023},
volume = {7},
number = {4},
pages = {116-134},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1705101.pdf},
abstract = {Mobile Ad-Hoc Networks (MANETs) have witnessed significant growth, driven by the proliferation of wireless-enabled portable devices. This article explores critical aspects of MANETs, including cluster formation, fault tolerance, and the innovative concept of Energy-Based Byzantine Fault Tolerance (BFT). Cluster formation is essential for efficient communication and resource management in MANETs. This article delves into proximity-based clustering, node distance calculation, and cluster head election to create robust communication structures. Fault tolerance is paramount in MANETs, where node failures can occur due to various factors. Clustering-based fault tolerance is discussed, emphasizing fault detection, isolation, and redundancy to ensure network resilience. The article introduces the concept of Energy-Based Byzantine Fault Tolerance (BFT) as a novel approach to address the unique challenges of MANETs. Energy-aware strategies are integrated with Byzantine Fault Tolerance to enhance network reliability and energy efficiency. The Energy-Based BFT algorithm aims to optimize cluster formation, Byzantine fault tolerance, energy-efficient communication, dynamic energy management, energy-aware quorum selection, fault detection with energy conservation, and head election based on energy reserves. The expected outcomes of this research include developing and validating the Energy-Based BFT algorithm, tailored for MANET clustering, to improve fault tolerance, energy efficiency, and network reliability. The article highlights the promising potential of Energy-Based BFT in fortifying MANETs against malicious attacks while extending their operational lifespan. Further research and empirical evaluations are suggested to fully understand its practical implications.},
keywords = {MANET, Fault tolerance, BFT, Energy Efficiency},
month = {October},
}