基于寿命预测的可充电无线传感器网络充电方案研究

Yang Yang, He Li, Xue-song Qiu, Shaoyong Guo, XiaoXiao Zeng, Kangting Zhao, Haoran Xin
{"title":"基于寿命预测的可充电无线传感器网络充电方案研究","authors":"Yang Yang, He Li, Xue-song Qiu, Shaoyong Guo, XiaoXiao Zeng, Kangting Zhao, Haoran Xin","doi":"10.1109/NOMS.2018.8406304","DOIUrl":null,"url":null,"abstract":"In order to reduce the cost and energy consumption in wireless sensor network's charging process, this paper proposes a Recharging Scheme based on Lifetime Prediction (RSLP) for wireless rechargeable sensor networks. First of all, based on the historical quantity of electricity variation sequence of the sensor nodes, the lifetime prediction scheme of the sensor nodes is established; and then, considering the sensor nodes need to be recharged and the Sink nodes chosen by the mobile charger (MC) according to the charging value to establish an undirected complete diagram. A Hamilton charging circuit is established by using the Gene-Expressive cuckoo algorithm to solve the charging problem of the rechargeable sensor networks. The simulation experiments show that the proposed algorithm can improve charging efficiency and reduce the mobile energy consumption.","PeriodicalId":19331,"journal":{"name":"NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Research on lifetime prediction-based recharging scheme in rechargeable WSNs\",\"authors\":\"Yang Yang, He Li, Xue-song Qiu, Shaoyong Guo, XiaoXiao Zeng, Kangting Zhao, Haoran Xin\",\"doi\":\"10.1109/NOMS.2018.8406304\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to reduce the cost and energy consumption in wireless sensor network's charging process, this paper proposes a Recharging Scheme based on Lifetime Prediction (RSLP) for wireless rechargeable sensor networks. First of all, based on the historical quantity of electricity variation sequence of the sensor nodes, the lifetime prediction scheme of the sensor nodes is established; and then, considering the sensor nodes need to be recharged and the Sink nodes chosen by the mobile charger (MC) according to the charging value to establish an undirected complete diagram. A Hamilton charging circuit is established by using the Gene-Expressive cuckoo algorithm to solve the charging problem of the rechargeable sensor networks. The simulation experiments show that the proposed algorithm can improve charging efficiency and reduce the mobile energy consumption.\",\"PeriodicalId\":19331,\"journal\":{\"name\":\"NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-04-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NOMS.2018.8406304\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"NOMS 2018 - 2018 IEEE/IFIP Network Operations and Management Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NOMS.2018.8406304","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

为了降低无线传感器网络充电过程中的成本和能耗,提出了一种基于寿命预测(RSLP)的无线可充电传感器网络充电方案。首先,根据传感器节点的历史电量变化序列,建立传感器节点的寿命预测方案;然后,考虑需要充电的传感器节点和移动充电器(MC)根据充电值选择的Sink节点,建立无向完全图。利用基因表达布谷鸟算法建立了Hamilton充电电路,解决了可充电传感器网络的充电问题。仿真实验表明,该算法可以提高充电效率,降低移动能耗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Research on lifetime prediction-based recharging scheme in rechargeable WSNs
In order to reduce the cost and energy consumption in wireless sensor network's charging process, this paper proposes a Recharging Scheme based on Lifetime Prediction (RSLP) for wireless rechargeable sensor networks. First of all, based on the historical quantity of electricity variation sequence of the sensor nodes, the lifetime prediction scheme of the sensor nodes is established; and then, considering the sensor nodes need to be recharged and the Sink nodes chosen by the mobile charger (MC) according to the charging value to establish an undirected complete diagram. A Hamilton charging circuit is established by using the Gene-Expressive cuckoo algorithm to solve the charging problem of the rechargeable sensor networks. The simulation experiments show that the proposed algorithm can improve charging efficiency and reduce the mobile energy consumption.
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
期刊最新文献
SSH Kernel: A Jupyter Extension Specifically for Remote Infrastructure Administration Visual emulation for Ethereum's virtual machine Analyzing throughput and stability in cellular networks Network events in a large commercial network: What can we learn? Economic incentives on DNSSEC deployment: Time to move from quantity to quality
×
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