Optimization of the LEACH algorithm in the selection of cluster heads based on residual energy in wireless sensor networks

Q3 Mathematics
Ferry Fachrizal, Muhammad Zarlis, Poltak Sihombing, Suherman Suherman
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Abstract

This research has a research object, namely the optimization of the LEACH (Low-Energy Adaptive Clustering Hierarchy) algorithm in the context of wireless sensor networks. The problem in this research is the imbalance in energy consumption across clusters, which has an impact on battery life and affects network performance. Other problems include selecting a cluster head that is not focused so that it is difficult to balance network performance as well as computational limitations that require optimization. The results obtained from this research are in the form of optimizing the leaching algorithm by modifying the clustering-based leaching algorithm that will be used in wireless sensor networks. In carrying out modifications, this research uses several stages in the process of selecting sensor nodes that will become members who function as cluster heads in a cluster that will be used in a wireless sensor network. In the LEACH (Low-Energy Adaptive Clustering Hierarchy) algorithm the cluster head will be selected based on the modified probability value. Modifying the algorithm by considering two factors, namely distance and remaining energy used in the Cluster Head selection process on the network and increasing network usage time must be based on the energy consumption used and then compared with the remaining energy. When modifying the LEACH (Low-Energy Adaptive Clustering Hierarchy) algorithm, it is necessary to pay attention to the distance factor between the nodes on a sensor and the selected cluster so that it can result in increased network performance. Network lifetime is indicated by the average death time of the first Node in the network. This research is novel in producing a modified leaching algorithm by improving network performance and extending battery life so that it can be used for wireless sensor networks in the context of natural disaster mitigation
在无线传感器网络中基于残余能量选择簇头的 LEACH 算法优化
本研究有一个研究对象,即在无线传感器网络中优化 LEACH(低能耗自适应聚类层次)算法。本研究的问题是各簇之间的能量消耗不平衡,这会影响电池寿命并影响网络性能。其他问题包括选择的簇头不集中,因此难以平衡网络性能,以及需要优化的计算限制。本研究取得的成果是通过修改基于聚类的浸出算法来优化浸出算法,该算法将用于无线传感器网络。在进行修改时,本研究在选择传感器节点的过程中使用了几个阶段,这些节点将成为在无线传感器网络中使用的簇中担任簇头的成员。在 LEACH(低能量自适应聚类层次)算法中,簇头将根据修改后的概率值进行选择。修改算法时要考虑两个因素,即在网络簇头选择过程中使用的距离和剩余能量,增加网络使用时间必须以使用的能量消耗为基础,然后与剩余能量进行比较。在修改 LEACH(低能量自适应聚类分层)算法时,必须注意传感器上的节点与所选簇头之间的距离因素,这样才能提高网络性能。网络寿命由网络中第一个节点的平均死亡时间表示。这项研究通过提高网络性能和延长电池寿命,提出了一种改进的浸出算法,从而可用于自然灾害减灾背景下的无线传感器网络。
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来源期刊
Eastern-European Journal of Enterprise Technologies
Eastern-European Journal of Enterprise Technologies Mathematics-Applied Mathematics
CiteScore
2.00
自引率
0.00%
发文量
369
审稿时长
6 weeks
期刊介绍: Terminology used in the title of the "East European Journal of Enterprise Technologies" - "enterprise technologies" should be read as "industrial technologies". "Eastern-European Journal of Enterprise Technologies" publishes all those best ideas from the science, which can be introduced in the industry. Since, obtaining the high-quality, competitive industrial products is based on introducing high technologies from various independent spheres of scientific researches, but united by a common end result - a finished high-technology product. Among these scientific spheres, there are engineering, power engineering and energy saving, technologies of inorganic and organic substances and materials science, information technologies and control systems. Publishing scientific papers in these directions are the main development "vectors" of the "Eastern-European Journal of Enterprise Technologies". Since, these are those directions of scientific researches, the results of which can be directly used in modern industrial production: space and aircraft industry, instrument-making industry, mechanical engineering, power engineering, chemical industry and metallurgy.
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