Deployment of Multiple Computing Systems in Underwater Wireless Sensor Networks

Mohammad Alsulami, Raafat S. Elfouly, R. Ammar, Huda Aldosari
{"title":"Deployment of Multiple Computing Systems in Underwater Wireless Sensor Networks","authors":"Mohammad Alsulami, Raafat S. Elfouly, R. Ammar, Huda Aldosari","doi":"10.1109/ISSPIT51521.2020.9408925","DOIUrl":null,"url":null,"abstract":"Underwater Wireless Sensor Networks(UWSNs) have emerged as a promising technology that is used to monitor underwater environment. Applications of UWSNs are numerous such as oil and gas pipeline monitoring, underwater animal detection, and object of interest detection. Automated Underwater Vehicles (AUVs) have been used to monitor underwater environment [13]. One of the significant challenges of AUVs usage is that it does not meet real-time constraints [15]. Researchers in [1] developed a real-time computing system that can collect, process, and transmit data to a gateway in real-time using a single processing node (computer). Nevertheless, a single computer cannot handle the whole load; Resources and equipment in general are limited. Thus, in this paper, we propose two approaches/algorithms that can group master nodes in the network into groups and allocate a computer for each group. In the first algorithm, we cluster master nodes using bottom-up approach. The process of assigning master nodes, in this approach, to groups is based on the communication range. In the second algorithm, nodes are deployed not only homogeneously but also heterogeneously. We add more constraints in order to make our assumptions are closer to real life. In result section, we provide some insights about our experiments. Simulation results show the merit of our proposed approaches.","PeriodicalId":111385,"journal":{"name":"2020 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSPIT51521.2020.9408925","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Underwater Wireless Sensor Networks(UWSNs) have emerged as a promising technology that is used to monitor underwater environment. Applications of UWSNs are numerous such as oil and gas pipeline monitoring, underwater animal detection, and object of interest detection. Automated Underwater Vehicles (AUVs) have been used to monitor underwater environment [13]. One of the significant challenges of AUVs usage is that it does not meet real-time constraints [15]. Researchers in [1] developed a real-time computing system that can collect, process, and transmit data to a gateway in real-time using a single processing node (computer). Nevertheless, a single computer cannot handle the whole load; Resources and equipment in general are limited. Thus, in this paper, we propose two approaches/algorithms that can group master nodes in the network into groups and allocate a computer for each group. In the first algorithm, we cluster master nodes using bottom-up approach. The process of assigning master nodes, in this approach, to groups is based on the communication range. In the second algorithm, nodes are deployed not only homogeneously but also heterogeneously. We add more constraints in order to make our assumptions are closer to real life. In result section, we provide some insights about our experiments. Simulation results show the merit of our proposed approaches.
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
水下无线传感器网络中多计算系统的部署
水下无线传感器网络(UWSNs)是一种具有发展前景的水下环境监测技术。UWSNs的应用非常广泛,如油气管道监测、水下动物检测、感兴趣目标检测等。自动水下航行器(auv)已被用于水下环境监测[13]。使用auv的一个重大挑战是它不满足实时限制[15]。[1]研究人员开发了一种实时计算系统,可以使用单个处理节点(计算机)实时采集、处理数据并将数据传输到网关。然而,一台计算机无法处理全部负载;总的来说,资源和设备是有限的。因此,在本文中,我们提出了两种方法/算法,可以将网络中的主节点分组,并为每组分配一台计算机。在第一种算法中,我们使用自底向上的方法对主节点进行聚类。在这种方法中,将主节点分配给组的过程是基于通信范围的。在第二种算法中,节点不仅采用同质部署,而且采用异构部署。为了使我们的假设更接近现实生活,我们添加了更多的约束条件。在结果部分,我们提供了一些关于我们实验的见解。仿真结果表明了所提方法的优点。
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
Performance study of CFD Pressure-based solver on HPC Efficient Topology of Multilevel Clustering Algorithm for Underwater Sensor Networks Machine learning applied to diabetes dataset using Quantum versus Classical computation DOAV Estimation Using L-Shaped Antenna Array Configuration Sentiment analysis using an ensemble approach of BiGRU model: A case study of AMIS tweets
×
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