Decision Routing Problems in A Wireless Sensor Network Based on A Neural Mechanism

IF 0.5 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS
A. Khaytbaev
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引用次数: 2

Abstract

This article proposes a solution for the routing problem in wireless sensor networks (WSN) based on a neural mechanism. The basic concepts of wireless sensor networks, artificial neural networks (ANNs), and WSN routing protocols are presented. The Kohonen ANN was selected to solve the problem of routing in wireless sensor networks based on a neural mechanism. A radio visibility matrix is proposed, which is a mathematical description of the connectivity of network nodes and the radio visibility of each node with respect to all other network nodes. Based on the Kohonen ANN trained by the constructive method, a method for WSN neural network clustering was developed. Two software-modeling environments are presented that were created to confirm the theory with respect to the logic of the developed methods for WSN clustering, their correction and the verification of their adequacy. Numerical results of modeling the solution of the routing problem in a wireless sensor network based on a neural mechanism by neural network clustering, the WSN matrix clustering method and the energy distance neural clustering protocol (EDNCP) are presented. It was found that the developed EDNCP protocol was 29% more efficient than known analogs.
基于神经机制的无线传感器网络中的决策路由问题
本文提出了一种基于神经机制的无线传感器网络路由问题的解决方案。介绍了无线传感器网络、人工神经网络和无线传感器网络路由协议的基本概念。选择Kohonen神经网络来解决基于神经机制的无线传感器网络中的路由问题。提出了一个无线电可见性矩阵,它是网络节点连通性和每个节点相对于所有其他网络节点的无线电可见性的数学描述。基于构造方法训练的Kohonen神经网络,提出了一种WSN神经网络聚类方法。给出了两个软件建模环境,它们被创建来证实关于所开发的WSN聚类方法的逻辑、它们的校正和它们的充分性的验证的理论。给出了通过神经网络聚类、WSN矩阵聚类方法和能量距离神经聚类协议(EDNCP)对基于神经机制的无线传感器网络中路由问题的求解进行建模的数值结果。发现所开发的EDNCP方案比已知类似物的效率高29%。
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来源期刊
Journal of ICT Research and Applications
Journal of ICT Research and Applications COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
1.60
自引率
0.00%
发文量
13
审稿时长
24 weeks
期刊介绍: Journal of ICT Research and Applications welcomes full research articles in the area of Information and Communication Technology from the following subject areas: Information Theory, Signal Processing, Electronics, Computer Network, Telecommunication, Wireless & Mobile Computing, Internet Technology, Multimedia, Software Engineering, Computer Science, Information System and Knowledge Management. Authors are invited to submit articles that have not been published previously and are not under consideration elsewhere.
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