Shortest Path Algorithms for Sensor Node Localization for Internet of Things

Ajay Kumar, V. Jain, P. Bhattacharya
{"title":"Shortest Path Algorithms for Sensor Node Localization for Internet of Things","authors":"Ajay Kumar, V. Jain, P. Bhattacharya","doi":"10.1109/ICONC345789.2020.9117301","DOIUrl":null,"url":null,"abstract":"Internet of Things have gained the interest of researchers and other academic communities due to their applications in various fields. Determining the location of a sensor node within the specified area consisting of number of sensors and smart devices is very crucial, which requires association between the devices and the sensor nodes[1]. Localization is the basic requirement for other services of any smart network like communication, clustering, distribution, routing etc. Multidimensional scaling is one of the approach used effectively for the sensor node localization. In this approach the process to obtain the minimum distance path between the pair of sensors are used which helps in estimating the relative positions of the nodes. This paper includes the explanation and comparison of different types shortest path algorithms. Then, we discuss about the use of multidimensional scaling process to obtain the absolute positions of nodes with reduced error cumulation in a smart network. It is mandatory to have a efficient, economic and scalable sensor node position estimation process for a wireless sensor network and hence for internet of Things. The results obtained experimentally proves the efficiency and effectiveness of the methods discussed for use in Internet of Things with various routing, topology and area.","PeriodicalId":155813,"journal":{"name":"2020 International Conference on Emerging Trends in Communication, Control and Computing (ICONC3)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 International Conference on Emerging Trends in Communication, Control and Computing (ICONC3)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICONC345789.2020.9117301","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Internet of Things have gained the interest of researchers and other academic communities due to their applications in various fields. Determining the location of a sensor node within the specified area consisting of number of sensors and smart devices is very crucial, which requires association between the devices and the sensor nodes[1]. Localization is the basic requirement for other services of any smart network like communication, clustering, distribution, routing etc. Multidimensional scaling is one of the approach used effectively for the sensor node localization. In this approach the process to obtain the minimum distance path between the pair of sensors are used which helps in estimating the relative positions of the nodes. This paper includes the explanation and comparison of different types shortest path algorithms. Then, we discuss about the use of multidimensional scaling process to obtain the absolute positions of nodes with reduced error cumulation in a smart network. It is mandatory to have a efficient, economic and scalable sensor node position estimation process for a wireless sensor network and hence for internet of Things. The results obtained experimentally proves the efficiency and effectiveness of the methods discussed for use in Internet of Things with various routing, topology and area.
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
物联网传感器节点定位的最短路径算法
物联网由于其在各个领域的应用而引起了研究人员和其他学术界的兴趣。在由多个传感器和智能设备组成的指定区域内确定传感器节点的位置至关重要,这需要设备与传感器节点之间的关联[1]。本地化是任何智能网络的通信、集群、分布、路由等其他服务的基本要求。多维尺度是传感器节点定位的有效方法之一。该方法利用获取传感器对之间最小距离路径的过程,有助于估计节点的相对位置。本文对不同类型的最短路径算法进行了说明和比较。然后,我们讨论了在智能网络中使用多维尺度过程来获得节点的绝对位置,并减少了误差累积。对于无线传感器网络和物联网来说,必须有一个高效、经济和可扩展的传感器节点位置估计过程。实验结果证明了所讨论的方法在各种路由、拓扑和区域的物联网中应用的效率和有效性。
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
自引率
0.00%
发文量
0
期刊最新文献
A Novel Planar Inverted-F Antenna for Dual Band Operations Comparing the Existing ERP Modules in Selected Private Universities of Punjab- An Empirical Study Shortest Path Algorithms for Sensor Node Localization for Internet of Things Diabetes Prognostication – An Aptness of Machine Learning Laguerre Function based Model Predictive Control for Multiple Product Inventory System
×
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