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

IF 0.5 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS Journal of ICT Research and Applications Pub Date : 2020-10-31 DOI:10.5614/10.5614/ITBJ.ICT.RES.APPL.2020.14.2.2
A. Khaytbaev
{"title":"Decision Routing Problems in A Wireless Sensor Network Based on A Neural Mechanism","authors":"A. Khaytbaev","doi":"10.5614/10.5614/ITBJ.ICT.RES.APPL.2020.14.2.2","DOIUrl":null,"url":null,"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.","PeriodicalId":42785,"journal":{"name":"Journal of ICT Research and Applications","volume":null,"pages":null},"PeriodicalIF":0.5000,"publicationDate":"2020-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of ICT Research and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5614/10.5614/ITBJ.ICT.RES.APPL.2020.14.2.2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
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.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
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.
期刊最新文献
Smart Card-based Access Control System using Isolated Many-to-Many Authentication Scheme for Electric Vehicle Charging Stations The Evaluation of DyHATR Performance for Dynamic Heterogeneous Graphs Machine Learning-based Early Detection and Prognosis of the Covid-19 Pandemic Improving Robustness Using MixUp and CutMix Augmentation for Corn Leaf Diseases Classification based on ConvMixer Architecture Generative Adversarial Networks Based Scene Generation on Indian Driving Dataset
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1