能量感知聚类与高效簇头选择

IF 0.5 Q4 ENGINEERING, ELECTRICAL & ELECTRONIC
El Idrissi Nezha, Najid Abdellah, El Alami Hassan
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引用次数: 6

摘要

摘要聚类是一种高效组织网络资源的技术,在无线传感器网络(WSNs)通信中,它用于将具有相似特征的传感器分组,这些传感器由一个被称为簇头(CH)的选定传感器管理。为此,本文提出了一种新的方法,即能量感知聚类和高效簇头选择(EAC-ECHS),以优化无线传感器网络在网络寿命方面的性能并提高能耗。在EAC-ECHS中,传感器网络分为互网格和公平聚类网格。此外,对于每个聚类网格,CH的选择是基于传感器的剩余能量、到邻居的距离和到基站的距离。仿真实验验证了EAC-ECHS方法和现有方法的性能,结果表明,EAC-ECHS方法在能耗、网络寿命和数据包传输率方面达到了设计目标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Energy-Aware Clustering and Efficient Cluster Head Selection
Abstract Clustering is an efficient technique to organize network resources efficiently and, in wireless sensor Networks (WSNs) communications it is used to group sensors with similar characteristics managed by a selected sensor called a Cluster Head (CH). Thus, this paper presents a new approach, namely Energy-Aware Clustering and Efficient Cluster Head Selection (EAC-ECHS) to optimize the performances of WSNs in terms of the network lifetime and enhance energy consumption. In EAC-ECHS, the sensor network is divided into an inter grid and fair clustered Grids. Furthermore, for each clustered Grid, the CH selection is based on the residual energy of sensor, distance to neighbors, and distance to the base station. Simulation experiments have been conducted to examine the performance of EAC-ECHS and previous approaches, and the results demonstrate that EAC-ECHS approach achieves the design objectives in terms energy consumption, network lifetime, and packet delivery ratio.
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来源期刊
CiteScore
2.70
自引率
8.30%
发文量
15
审稿时长
8 weeks
期刊介绍: nternational Journal on Smart Sensing and Intelligent Systems (S2IS) is a rapid and high-quality international forum wherein academics, researchers and practitioners may publish their high-quality, original, and state-of-the-art papers describing theoretical aspects, system architectures, analysis and design techniques, and implementation experiences in intelligent sensing technologies. The journal publishes articles reporting substantive results on a wide range of smart sensing approaches applied to variety of domain problems, including but not limited to: Ambient Intelligence and Smart Environment Analysis, Evaluation, and Test of Smart Sensors Intelligent Management of Sensors Fundamentals of Smart Sensing Principles and Mechanisms Materials and its Applications for Smart Sensors Smart Sensing Applications, Hardware, Software, Systems, and Technologies Smart Sensors in Multidisciplinary Domains and Problems Smart Sensors in Science and Engineering Smart Sensors in Social Science and Humanity
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