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Survey on Clustering Techniques for Wireless Sensor Networks and Cluster Head Selection Model

Ahmed, Muhammed. K. and Farej, Ziyad. K. (2024) Survey on Clustering Techniques for Wireless Sensor Networks and Cluster Head Selection Model. European Journal of Computer Science and Information Technology, 12 (2). pp. 1-21. ISSN 2054-0957 (Print), 2054-0965 (Online)

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Abstract

Low-powered wirelessly connected devices create a system that is self-contained and called Wireless sensor network (WSN), this system has a number of practical applications in the modern world. Nodes in WSN are spread out spatially and have wireless communication with other nodes in the network, these nodes are primarily dedicated to sensing the vicinity and recording the physical properties of the area, including collect observations pertaining to humidity, noise, load, temperature Sensors and other factors at a central station. From there, the end user analyzes the information. After distribution, a cluster is formed between nodes, called a cluster. One of the nodes is selected as the cluster's head, which is used to migrate the data across the network. Clustering is essential in addressing many issues in WSN, particularly in regards to their lifetime, energy savings, and interoperability. Many approaches exist for clustering WSN, the difference between them is in the choice of CH, the number of clusters, the structure of clusters, the policy for data aggregation, the efficiency of communication between clusters, and the choice of communication between internal and external clusters. This article provides a comprehensive comparison of various methods of clustering and their advantages and disadvantages in WSNs. It also describes the principles of CH selection and how it works within each category. This helps the end user to choose the most suitable one protocol for their needs, and also will assist researchers in addressing the problems revealed in the process of clustering WSN.

Item Type: Article
Subjects: T Technology > T Technology (General)
Depositing User: Professor Mark T. Owen
Date Deposited: 20 Apr 2024 14:33
Last Modified: 20 Apr 2024 14:33
URI: https://tudr.org/id/eprint/2886

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