使用无线电力传输快速补充传感器能量的无人机的最佳位置

C. Caillouet, Tahiry Razafindralambo, Dimitrios Zorbas
{"title":"使用无线电力传输快速补充传感器能量的无人机的最佳位置","authors":"C. Caillouet, Tahiry Razafindralambo, Dimitrios Zorbas","doi":"10.1109/WD.2019.8734203","DOIUrl":null,"url":null,"abstract":"Lifetime is the main issue of wireless sensors networks. Since the nodes are often placed in inaccessible places, the replacement of their battery is not an easy task. Moreover, the node maintenance is a costly and time consuming operation when the nodes are high in numbers. Energy harvesting technologies have recently been developed to replenish part or all of the required energy that allows a node to function. In this paper, we use dedicated chargers carried by drones that can fly over the network and transmit energy to the nodes using radio-frequency (RF) signals. We formulate and optimally solve the Optimal Drone Placement and Planning Problem (OD3P) by using a given number of flying drones, in order to efficiently recharge wireless sensor nodes. Unlike other works in the literature, we assume that the drones can trade altitude with coverage and recharge power, while each drone can move across different positions in the network to extend coverage. We present a linear program as well as a fast heuristic algorithm to meet the minimum energy demands of the nodes in the shortest possible amount of time. Our simulation results show the effectiveness of our approaches for network scenarios with up to 50 sensors and a 50 × 50m terrain size.","PeriodicalId":432101,"journal":{"name":"2019 Wireless Days (WD)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Optimal placement of drones for fast sensor energy replenishment using wireless power transfer\",\"authors\":\"C. Caillouet, Tahiry Razafindralambo, Dimitrios Zorbas\",\"doi\":\"10.1109/WD.2019.8734203\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Lifetime is the main issue of wireless sensors networks. Since the nodes are often placed in inaccessible places, the replacement of their battery is not an easy task. Moreover, the node maintenance is a costly and time consuming operation when the nodes are high in numbers. Energy harvesting technologies have recently been developed to replenish part or all of the required energy that allows a node to function. In this paper, we use dedicated chargers carried by drones that can fly over the network and transmit energy to the nodes using radio-frequency (RF) signals. We formulate and optimally solve the Optimal Drone Placement and Planning Problem (OD3P) by using a given number of flying drones, in order to efficiently recharge wireless sensor nodes. Unlike other works in the literature, we assume that the drones can trade altitude with coverage and recharge power, while each drone can move across different positions in the network to extend coverage. We present a linear program as well as a fast heuristic algorithm to meet the minimum energy demands of the nodes in the shortest possible amount of time. Our simulation results show the effectiveness of our approaches for network scenarios with up to 50 sensors and a 50 × 50m terrain size.\",\"PeriodicalId\":432101,\"journal\":{\"name\":\"2019 Wireless Days (WD)\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-04-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 Wireless Days (WD)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WD.2019.8734203\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Wireless Days (WD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WD.2019.8734203","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9

摘要

寿命是无线传感器网络的主要问题。由于节点通常被放置在难以接近的地方,因此更换电池不是一件容易的事情。当节点数量较多时,维护成本高,耗时长。能量收集技术最近被开发出来,以补充部分或全部所需的能量,使节点能够正常工作。在本文中,我们使用无人机携带的专用充电器,这些充电器可以飞越网络并使用射频(RF)信号将能量传输到节点。为了有效地为无线传感器节点充电,我们利用给定数量的飞行无人机,制定并优化解决了最优无人机布局和规划问题(OD3P)。与文献中的其他作品不同,我们假设无人机可以用覆盖和充电来交换高度,而每架无人机可以在网络中的不同位置移动以扩大覆盖范围。为了在最短的时间内满足节点的最小能量需求,我们提出了一种线性规划和快速启发式算法。我们的仿真结果表明,我们的方法在网络场景中具有多达50个传感器和50 × 50米地形尺寸的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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
Optimal placement of drones for fast sensor energy replenishment using wireless power transfer
Lifetime is the main issue of wireless sensors networks. Since the nodes are often placed in inaccessible places, the replacement of their battery is not an easy task. Moreover, the node maintenance is a costly and time consuming operation when the nodes are high in numbers. Energy harvesting technologies have recently been developed to replenish part or all of the required energy that allows a node to function. In this paper, we use dedicated chargers carried by drones that can fly over the network and transmit energy to the nodes using radio-frequency (RF) signals. We formulate and optimally solve the Optimal Drone Placement and Planning Problem (OD3P) by using a given number of flying drones, in order to efficiently recharge wireless sensor nodes. Unlike other works in the literature, we assume that the drones can trade altitude with coverage and recharge power, while each drone can move across different positions in the network to extend coverage. We present a linear program as well as a fast heuristic algorithm to meet the minimum energy demands of the nodes in the shortest possible amount of time. Our simulation results show the effectiveness of our approaches for network scenarios with up to 50 sensors and a 50 × 50m terrain size.
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
Time-Optimized Task Offloading Decision Making in Mobile Edge Computing Enhancing User Fairness in OFDMA Radio Access Networks Through Machine Learning In-network Predictive Analytics in Edge Computing New Multi-Carrier Candidate Waveform For the 5G Physical Layer of Wireless Mobile Networks Credit-Based Relay Selection Algorithm Using Stackelberg Game
×
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