利用人工神经网络提高无线传感器网络的服务质量

A. Eshmuradov, A. Khaytbaev
{"title":"利用人工神经网络提高无线传感器网络的服务质量","authors":"A. Eshmuradov, A. Khaytbaev","doi":"10.1109/ICISCT55600.2022.10146881","DOIUrl":null,"url":null,"abstract":"The article presents the results of improving the quality of service in a wireless sensor network using artificial neural networks. Improved quality of service for some QoS parameters such as packet loss and congestion. Classification of nodes into qualified and unqualified categories was done using parameters. A new method of improving QoS based on artificial neural network (ANN) was implemented by converting unqualified nodes into good ones. Wireless sensor networks face many limitations such as memory and energy, the cost and computation time are somewhat reduced by using artificial neural networks. Modeling results showed that the proposed system achieved improved QoS by increasing network lifetime and reducing packet loss ratio.","PeriodicalId":332984,"journal":{"name":"2022 International Conference on Information Science and Communications Technologies (ICISCT)","volume":"134 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Improving quality of service in a wireless sensor network using artificial neural networks\",\"authors\":\"A. Eshmuradov, A. Khaytbaev\",\"doi\":\"10.1109/ICISCT55600.2022.10146881\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The article presents the results of improving the quality of service in a wireless sensor network using artificial neural networks. Improved quality of service for some QoS parameters such as packet loss and congestion. Classification of nodes into qualified and unqualified categories was done using parameters. A new method of improving QoS based on artificial neural network (ANN) was implemented by converting unqualified nodes into good ones. Wireless sensor networks face many limitations such as memory and energy, the cost and computation time are somewhat reduced by using artificial neural networks. Modeling results showed that the proposed system achieved improved QoS by increasing network lifetime and reducing packet loss ratio.\",\"PeriodicalId\":332984,\"journal\":{\"name\":\"2022 International Conference on Information Science and Communications Technologies (ICISCT)\",\"volume\":\"134 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-09-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Conference on Information Science and Communications Technologies (ICISCT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICISCT55600.2022.10146881\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Information Science and Communications Technologies (ICISCT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICISCT55600.2022.10146881","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本文介绍了利用人工神经网络提高无线传感器网络服务质量的结果。改进了某些QoS参数(如丢包和拥塞)的服务质量。利用参数将节点划分为合格和不合格类别。提出了一种基于人工神经网络(ANN)的QoS改进方法,将不合格节点转化为良好节点。无线传感器网络面临着存储和能量等诸多限制,使用人工神经网络可以在一定程度上降低成本和计算时间。建模结果表明,该系统通过提高网络生存期和降低丢包率来提高服务质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improving quality of service in a wireless sensor network using artificial neural networks
The article presents the results of improving the quality of service in a wireless sensor network using artificial neural networks. Improved quality of service for some QoS parameters such as packet loss and congestion. Classification of nodes into qualified and unqualified categories was done using parameters. A new method of improving QoS based on artificial neural network (ANN) was implemented by converting unqualified nodes into good ones. Wireless sensor networks face many limitations such as memory and energy, the cost and computation time are somewhat reduced by using artificial neural networks. Modeling results showed that the proposed system achieved improved QoS by increasing network lifetime and reducing packet loss ratio.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信