Region based low energy adaptive clustering hierarchy (R-LEACH) protocol

Saha, Anik; Khan, Md. Sharif Uddin; Rahman, Md. Mezanur

doi:10.1145/3362966.3362978

Cited by 7 publications

(4 citation statements)

References 4 publications

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“…(Anik Kumar Saha, 2020) [1] Wi-Fi Sensor Networks (WSNs) have grown in prominence as one of the most rapidly evolving internet data transmission technologies. At this point, WSN has a foot in practically every scientific and technological pond.…”

Section: Literature Surveymentioning

confidence: 99%

Mathematical Modeling and Statistical Analysis of Efficient Cluster Head Selection Based LEACH Protocol for Wireless Sensor Networks

Amit Gupta

2024

cana

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The collection of data from the physical environment, such as temperature and humidity readings, is an essential function of Wireless Sensor Networks (WSNs). Because of its ability to communicate data wirelessly, WSNs are crucial for connecting the digital and physical worlds. Nevertheless, WSN energy efficiency optimization has become a more complicated challenge because of their battery dependency and deployment in adverse locations. The emphasis of this research is the Improved Low-Energy Adaptive Clustering Hierarchy (ILEACH) protocol, which is used as an example of a mathematics-driven strategy to improve WSN energy efficiency. To tackle important problems with energy consumption and network lifetime, mathematical modelling and equation-based analysis are used to study and enhance ILEACH's performance. Particularly in faraway places with few resources, energy efficiency is of the utmost importance when discussing WSNs. This study's mathematical models explore the equations and probability distributions that control the lifetime, energy consumption, and behaviour of sensor nodes. Our goal is to shed light on the energy optimization processes of ILEACH by means of thorough mathematical analysis and derivations. Our method incorporates both theoretical modelling and empirical assessments of ILEACH's cluster head formation, throughput, and network performance as a whole. Our comparison of the mathematical formulations of ILEACH and LEACH shows that our Improved LEACH is better in terms of data throughput, network lifetime, and energy efficiency. Using a figure of merits criterion, we compare LEACH, ILEACH, and the proposed Improved LEACH in detail to help with decision-making and protocol selection. With its solid mathematical groundwork, this study is a great tool for improving the efficiency of WSNs' energy-saving algorithms, which in turn can help networks last longer and run better.

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Section: Literature Surveymentioning

confidence: 99%

Mathematical Modeling and Statistical Analysis of Efficient Cluster Head Selection Based LEACH Protocol for Wireless Sensor Networks

Amit Gupta

2024

cana

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“…However, an increased computational complexity has been observed in this case. An attempt to stabilize the cluster head count in the conventional LEACH methods has been investigated in the literature [23]. Another method investigated in the literature aims to balance the energy consumption in the conventional LEACH methods [Salim] Multi-objective LEACH based methods have also been addressed in the literature [24] - [25] where load balancing and energy efficiency are taken as objectives.…”

Section: Related Workmentioning

confidence: 99%

A Metaheuristic Approach Towards Enhancement of Network Lifetime in Wireless Sensor Networks

2023

KSII TIIS

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Sensor networks are now an essential aspect of wireless communication, especially with the introduction of new gadgets and protocols. Their ability to be deployed anywhere, especially where human presence is undesirable, makes them perfect choices for remote observation and control. Despite their vast range of applications from home to hostile territory monitoring, limited battery power remains a limiting factor in their efficacy. To analyze and transmit data, it requires intelligent use of available battery power. Several studies have established effective routing algorithms based on clustering. However, choosing optimal cluster heads and similarity measures for clustering significantly increases computing time and cost. This work proposes and implements a simple two-phase technique of route creation and maintenance to ensure route reliability by employing nature-inspired ant colony optimization followed by the fuzzy decision engine (FDE). Benchmark methods such as PSO, ACO and GWO are compared with the proposed HRCM's performance. The objective has been focused towards establishing the superiority of proposed work amongst existing optimization methods in a standalone configuration. An average of 15% improvement in energy consumption followed by 12% improvement in latency reduction is observed in proposed hybrid model over standalone optimization methods.

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“…Leach-MAC [ 32 ] is also the modification of this algorithm which works more efficiently in WSNs. Similarly, region-based (R-Leach) and modified weighted (W-Leach) proposed in [ 33 , 34 ].…”

Section: Related Workmentioning

confidence: 99%

Adaptive Node Clustering for Underwater Sensor Networks

Khan

Bibi

Aadil

et al. 2021

Sensors

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Monitoring of an underwater environment and communication is essential for many applications, such as sea habitat monitoring, offshore investigation and mineral exploration, but due to underwater current, low bandwidth, high water pressure, propagation delay and error probability, underwater communication is challenging. In this paper, we proposed a sensor node clustering technique for UWSNs named as adaptive node clustering technique (ANC-UWSNs). It uses a dragonfly optimization (DFO) algorithm for selecting ideal measure of clusters needed for routing. The DFO algorithm is inspired by the swarming behavior of dragons. The proposed methodology correlates with other algorithms, for example the ant colony optimizer (ACO), comprehensive learning particle swarm optimizer (CLPSO), gray wolf optimizer (GWO) and moth flame optimizer (MFO). Grid size, transmission range and nodes density are used in a performance matrix, which varies during simulation. Results show that DFO outperform the other algorithms. It produces a higher optimized number of clusters as compared to other algorithms and hence optimizes overall routing and increases the life span of a network.

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Region based low energy adaptive clustering hierarchy (R-LEACH) protocol

Cited by 7 publications

References 4 publications

Mathematical Modeling and Statistical Analysis of Efficient Cluster Head Selection Based LEACH Protocol for Wireless Sensor Networks

Mathematical Modeling and Statistical Analysis of Efficient Cluster Head Selection Based LEACH Protocol for Wireless Sensor Networks

A Metaheuristic Approach Towards Enhancement of Network Lifetime in Wireless Sensor Networks

Adaptive Node Clustering for Underwater Sensor Networks

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