A comprehensive review of clustering approaches for energy efficiency in wireless sensor networks

IF 1.2 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY Pub Date : 2023-01-01 DOI:10.1504/ijcat.2023.133035
Wesal Bassem Nedham, Ali Kadhum M. Al Qurabat
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Abstract

Wireless Sensor Networks (WSNs) have become more popular in recent years due to their vast range of applications. The utilisation of WSNs is an absolute requirement for future revolutionary domains such as smart cities, the Internet of Things, or ecological fields, where hundreds or thousands of sensor nodes are placed. Moreover, because WSNs are energy-constrained networks, implementing energy-aware protocols is critical. Hierarchical techniques enhance network performance and extend network lifetime in large-scale WSNs. Within a WSN, hierarchy is achieved by dividing the network into sub-networks known as clusters, which are directed by Cluster Heads (CH). Clustering is the most common energy-efficient approach, and it offers several benefits, like reduced latency, scalability, lifetime and energy efficiency. This study presents a detailed assessment of several clustering techniques, together with their aims, features, etc. Furthermore, clustering techniques are classified and evaluated based on numerous cluster features, cluster head attributes and clustering procedures.
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无线传感器网络能源效率的聚类方法综述
近年来,无线传感器网络(WSNs)由于其广泛的应用范围而变得越来越流行。无线传感器网络的使用是未来革命性领域的绝对要求,例如智能城市,物联网或生态领域,其中放置了数百或数千个传感器节点。此外,由于无线传感器网络是能量受限的网络,因此实现能量感知协议至关重要。在大规模无线传感器网络中,分层技术提高了网络性能,延长了网络寿命。在WSN中,层次结构是通过将网络划分为称为集群的子网来实现的,这些子网由簇头(CH)指导。集群是最常见的节能方法,它提供了几个好处,比如减少延迟、可伸缩性、生命周期和能源效率。本研究详细评估了几种聚类技术,以及它们的目的、特点等。此外,基于众多聚类特征、簇头属性和聚类过程对聚类技术进行了分类和评价。
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来源期刊
INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY
INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-
CiteScore
2.80
自引率
45.50%
发文量
49
期刊介绍: IJCAT addresses issues of computer applications, information and communication systems, software engineering and management, CAD/CAM/CAE, numerical analysis and simulations, finite element methods and analyses, robotics, computer applications in multimedia and new technologies, computer aided learning and training. Topics covered include: -Computer applications in engineering and technology- Computer control system design- CAD/CAM, CAE, CIM and robotics- Computer applications in knowledge-based and expert systems- Computer applications in information technology and communication- Computer-integrated material processing (CIMP)- Computer-aided learning (CAL)- Computer modelling and simulation- Synthetic approach for engineering- Man-machine interface- Software engineering and management- Management techniques and methods- Human computer interaction- Real-time systems
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