Improved Cluster Based Data Gathering Using Ant Lion Optimization in Wireless Sensor Networks

Yogarajan, G.; Revathi, T.

doi:10.1007/s11277-017-4996-3

Cited by 47 publications

(14 citation statements)

References 18 publications

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“…In the scheme, [42] authors proposed an improved method based on clustering for data collecting using ant lion optimization in WSN to improve the overall performance of the network in terms of high throughput and low delay. Moreover, the ant lion optimization algorithm is applied for clustering in WSN.…”

Section: Literature Reviewmentioning

confidence: 99%

Ant Lion Optimizer Based Clustering Algorithm for Wireless Body Area Networks in Livestock Industry

et al. 2021

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Wireless Body Area Networks (WBANs) are emerging in the livestock industry for remote monitoring of cattle using wireless body sensors (WBS). The random mobility of animals acting as nodes causes the network's topology to change rapidly, originating from scalability and reliability issues. Stable transmission of acquired data to the base station requires an intelligent clustering mechanism that reduces the energy consumption and fulfills the network's constraints. Several clustering techniques are available as a solution, but these techniques yield numerous cluster heads, resulting in more energy utilization. Higher energy utilization lessens the effective life of WBSs and increases monitoring costs. This paper presents a metaheuristic approach for selecting optimal clusters in WBANs to realize an energy-efficient routing protocol for livestock health and behavior monitoring. The proposed approach employs Ant Lion Optimizer (ALO) to select the optimal clusters for different pasturage sizes using sensors of different transmission ranges considering user's preferences about cluster density. The proposed technique with ALO is compared with other recent techniques such as Ant Colony Optimization, Grasshopper Optimization, and Moth Flame Optimization. The comparison results show the proposed technique's effectiveness in realizing energyefficient protocols of WBANs for remote monitoring applications.

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Section: Literature Reviewmentioning

confidence: 99%

Ant Lion Optimizer Based Clustering Algorithm for Wireless Body Area Networks in Livestock Industry

et al. 2021

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“…In Yogarajan and Revathi (2018), an ant lion optimization (ALO) based clustering algorithm was proposed. The fitness function is used by the ALO for the CH selection.…”

Section: Ant Lion Optimization Clustering (Aloc)mentioning

confidence: 99%

A survey on clustering protocols in wireless sensor network: taxonomy, comparison, and future scope

Rawat

Chauhan

2021

J Ambient Intell Human Comput

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The wireless sensor network is growing as a powerful technology in various domains. The applications of wireless sensor networks are increasing rapidly and providing services to different sectors. The nodes employed in the sensor networks are outfitted with restricted battery power and the proper management is required for the utilization of the limited sensor energy. The clustering protocols in sensor networks are designed for handling the energy issue in the network. The clustering protocols proposed in the past has used different techniques and ideas for improving the network lifetime and performance. In order to provide a quick and easy understanding of the key aspects of any domain surveys are very helpful. Keeping this viewpoint in mind, this paper focuses on providing a survey for the clustering protocols which can help the researchers in getting a comprehensive overview of the different aspects of the clustering techniques. In this survey, the clustering protocols are classified on the basis of their clustering methodologies and working capabilities into three categories: traditional clustering protocols, fuzzy logic based clustering protocols, and heuristic based clustering protocols. The protocols of different categories are compared by employing the feature based, methodology based, and performance based comparison parameters to help the researchers in getting an easier understanding of different clustering concepts.

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“…These days, wireless sensor networks (WSNs) becomes more popular and common among human societies due to its enormous applications such as smart buildings, healthcare, environment control, and surveillance. Yogarajan and Revathi [181] tried to improve cluster based routing by modeling cluster head selection as a fitness function and tried to improve the network performance by using ALO. They argued that their simulation results improved network lifetime, and reduced individual nodes number.…”

Section: Wireless Networkmentioning

confidence: 99%

Ant Lion Optimization: Variants, Hybrids, and Applications

2020

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Ant Lion Optimizer (ALO) is a recent novel algorithm developed in the literature that simulates the foraging behavior of a Ant lions. Recently, it has been applied to a huge number of optimization problems. It has many advantages: easy, scalable, flexible, and have a great balance between exploration and exploitation. In this comprehensive study, many publications using ALO have been collected and summarized. Firstly, we introduce an introduction about ALO. Secondly, we categorized the recent versions of ALO into 3 Categories mainly Modified, Hybrid and Multi-Objective. we also introduce the applications in which ALO has been applied such as power, Machine Learning, Image processing problems, Civil Engineering, Medical, etc. The review paper is ended by giving a conclusion of the main ALO foundations and providing some suggestions & possible future directions that can be investigated.

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Improved Cluster Based Data Gathering Using Ant Lion Optimization in Wireless Sensor Networks

Cited by 47 publications

References 18 publications

Ant Lion Optimizer Based Clustering Algorithm for Wireless Body Area Networks in Livestock Industry

Ant Lion Optimizer Based Clustering Algorithm for Wireless Body Area Networks in Livestock Industry

A survey on clustering protocols in wireless sensor network: taxonomy, comparison, and future scope

Ant Lion Optimization: Variants, Hybrids, and Applications

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