无电池LoRaWAN网络的动态传输自适应算法

IF 7.6 3区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Fabrizio Giuliano , Antonino Pagano , Daniele Croce , Gianpaolo Vitale , Ilenia Tinnirello
{"title":"无电池LoRaWAN网络的动态传输自适应算法","authors":"Fabrizio Giuliano ,&nbsp;Antonino Pagano ,&nbsp;Daniele Croce ,&nbsp;Gianpaolo Vitale ,&nbsp;Ilenia Tinnirello","doi":"10.1016/j.iot.2025.101706","DOIUrl":null,"url":null,"abstract":"<div><div>Demand for sustainable IoT solutions has increased over the years, with energy-harvesting technologies coming to the fore, and environmental-powered sensors gaining much importance. Indeed, the benefits can be outstanding for batteryless sensors in terms of increased durability, reduced maintenance (no need for battery replacement), and higher resistance to environmental factors. However, such batteryless devices must be accurately designed to cope with time-varying energy sources, such as solar or wind power. In particular, this work investigates adaptive transmission algorithms to optimize the performance and lifetime of LoRa-based batteryless IoT sensors. First, a thorough characterization is carried out concerning the device’s power consumption, focusing on both sensor measurement and data transmission operations. The performed analysis takes into account also different network scenarios, considering possible changes of the device parameters. Second, a transmission adaptation scheme for the optimizing data transmission intervals, named <em>Uniform Transmission Adaptation</em> (UTA), is proposed. Finally, tailored energy storage solutions are developed, depending on the available energy capacity and considering direct coupling and the use of renewable sources, like photovoltaic cells. Through large-scale simulations in a massive IoT scenario, we quantitatively assess network performance, energy consumption and network efficiency. Simulations show that in massive network conditions, the Packet Delivery Ratio (PDR) reaches 87% with UTA, compared to about 70% achieved with fixed interval transmission strategies. Furthermore, the loss of energy productivity (LoEP) in the fixed transmission scenario is around 3.75% during winter, whereas with UTA it is reduced to near 0%, demonstrating a reduction in energy losses. The findings provide a basis for the design of sensor devices with optimal energy management, in order to meet given reliability requirements, and tackling important challenges of batteryless IoT networks.</div></div>","PeriodicalId":29968,"journal":{"name":"Internet of Things","volume":"33 ","pages":"Article 101706"},"PeriodicalIF":7.6000,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Dynamic transmission adaptation algorithms for battery-free LoRaWAN networks\",\"authors\":\"Fabrizio Giuliano ,&nbsp;Antonino Pagano ,&nbsp;Daniele Croce ,&nbsp;Gianpaolo Vitale ,&nbsp;Ilenia Tinnirello\",\"doi\":\"10.1016/j.iot.2025.101706\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Demand for sustainable IoT solutions has increased over the years, with energy-harvesting technologies coming to the fore, and environmental-powered sensors gaining much importance. Indeed, the benefits can be outstanding for batteryless sensors in terms of increased durability, reduced maintenance (no need for battery replacement), and higher resistance to environmental factors. However, such batteryless devices must be accurately designed to cope with time-varying energy sources, such as solar or wind power. In particular, this work investigates adaptive transmission algorithms to optimize the performance and lifetime of LoRa-based batteryless IoT sensors. First, a thorough characterization is carried out concerning the device’s power consumption, focusing on both sensor measurement and data transmission operations. The performed analysis takes into account also different network scenarios, considering possible changes of the device parameters. Second, a transmission adaptation scheme for the optimizing data transmission intervals, named <em>Uniform Transmission Adaptation</em> (UTA), is proposed. Finally, tailored energy storage solutions are developed, depending on the available energy capacity and considering direct coupling and the use of renewable sources, like photovoltaic cells. Through large-scale simulations in a massive IoT scenario, we quantitatively assess network performance, energy consumption and network efficiency. Simulations show that in massive network conditions, the Packet Delivery Ratio (PDR) reaches 87% with UTA, compared to about 70% achieved with fixed interval transmission strategies. Furthermore, the loss of energy productivity (LoEP) in the fixed transmission scenario is around 3.75% during winter, whereas with UTA it is reduced to near 0%, demonstrating a reduction in energy losses. The findings provide a basis for the design of sensor devices with optimal energy management, in order to meet given reliability requirements, and tackling important challenges of batteryless IoT networks.</div></div>\",\"PeriodicalId\":29968,\"journal\":{\"name\":\"Internet of Things\",\"volume\":\"33 \",\"pages\":\"Article 101706\"},\"PeriodicalIF\":7.6000,\"publicationDate\":\"2025-07-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Internet of Things\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2542660525002203\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Internet of Things","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2542660525002203","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0

摘要

多年来,随着能源收集技术的出现,对可持续物联网解决方案的需求不断增加,环境驱动的传感器变得越来越重要。事实上,无电池传感器在耐用性、减少维护(不需要更换电池)和对环境因素的更高抵抗力方面的优势是突出的。然而,这种无电池设备必须精确设计,以应对时变能源,如太阳能或风能。特别是,本工作研究了自适应传输算法,以优化基于lora的无电池物联网传感器的性能和寿命。首先,对器件的功耗进行了全面的表征,重点关注传感器测量和数据传输操作。所进行的分析还考虑到不同的网络场景,考虑到设备参数可能发生的变化。其次,提出了一种优化数据传输间隔的传输自适应方案——统一传输自适应(UTA)。最后,根据可用的能量容量,考虑直接耦合和使用可再生能源(如光伏电池),开发量身定制的储能解决方案。通过大规模物联网场景的大规模模拟,我们定量评估网络性能、能耗和网络效率。仿真结果表明,在大规模网络环境下,采用UTA的分组投递率(Packet Delivery Ratio, PDR)达到87%,而采用固定间隔传输策略的PDR仅为70%左右。此外,冬季固定输电方案的能源生产力损失(LoEP)约为3.75%,而UTA则降至近0%,表明能量损失减少。研究结果为设计具有最佳能量管理的传感器设备提供了基础,以满足给定的可靠性要求,并解决无电池物联网网络的重要挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dynamic transmission adaptation algorithms for battery-free LoRaWAN networks
Demand for sustainable IoT solutions has increased over the years, with energy-harvesting technologies coming to the fore, and environmental-powered sensors gaining much importance. Indeed, the benefits can be outstanding for batteryless sensors in terms of increased durability, reduced maintenance (no need for battery replacement), and higher resistance to environmental factors. However, such batteryless devices must be accurately designed to cope with time-varying energy sources, such as solar or wind power. In particular, this work investigates adaptive transmission algorithms to optimize the performance and lifetime of LoRa-based batteryless IoT sensors. First, a thorough characterization is carried out concerning the device’s power consumption, focusing on both sensor measurement and data transmission operations. The performed analysis takes into account also different network scenarios, considering possible changes of the device parameters. Second, a transmission adaptation scheme for the optimizing data transmission intervals, named Uniform Transmission Adaptation (UTA), is proposed. Finally, tailored energy storage solutions are developed, depending on the available energy capacity and considering direct coupling and the use of renewable sources, like photovoltaic cells. Through large-scale simulations in a massive IoT scenario, we quantitatively assess network performance, energy consumption and network efficiency. Simulations show that in massive network conditions, the Packet Delivery Ratio (PDR) reaches 87% with UTA, compared to about 70% achieved with fixed interval transmission strategies. Furthermore, the loss of energy productivity (LoEP) in the fixed transmission scenario is around 3.75% during winter, whereas with UTA it is reduced to near 0%, demonstrating a reduction in energy losses. The findings provide a basis for the design of sensor devices with optimal energy management, in order to meet given reliability requirements, and tackling important challenges of batteryless IoT networks.
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
Internet of Things
Internet of Things Multiple-
CiteScore
3.60
自引率
5.10%
发文量
115
审稿时长
37 days
期刊介绍: Internet of Things; Engineering Cyber Physical Human Systems is a comprehensive journal encouraging cross collaboration between researchers, engineers and practitioners in the field of IoT & Cyber Physical Human Systems. The journal offers a unique platform to exchange scientific information on the entire breadth of technology, science, and societal applications of the IoT. The journal will place a high priority on timely publication, and provide a home for high quality. Furthermore, IOT is interested in publishing topical Special Issues on any aspect of IOT.
×
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:604180095
Book学术官方微信