能量收集系统的自适应占空循环

Jason Hsu, S. Zahedi, A. Kansal, M. Srivastava, V. Raghunathan
{"title":"能量收集系统的自适应占空循环","authors":"Jason Hsu, S. Zahedi, A. Kansal, M. Srivastava, V. Raghunathan","doi":"10.1145/1165573.1165616","DOIUrl":null,"url":null,"abstract":"Harvesting energy from the environment is feasible in many applications to ameliorate the energy limitations in sensor networks. In this paper, we present an adaptive duty cycling algorithm that allows energy harvesting sensor nodes to autonomously adjust their duty cycle according to the energy availability in the environment. The algorithm has three objectives, namely: (a) achieving energy neutral operation, i.e., energy consumption should not be more than the energy provided by the environment; (b) maximizing the system performance based on an application utility model subject to the above energy-neutrality constraint; and (c) adapting to the dynamics of the energy source at run-time. We present a model that enables harvesting sensor nodes to predict future energy opportunities based on historical data. We also derive an upper bound on the maximum achievable performance assuming perfect knowledge about the future behavior of the energy source. Our methods are evaluated using data gathered from a prototype solar energy harvesting platform and we show that our algorithm can utilize up to 58% more environmental energy compared to the case when harvesting-aware power management is not used","PeriodicalId":119229,"journal":{"name":"ISLPED'06 Proceedings of the 2006 International Symposium on Low Power Electronics and Design","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"243","resultStr":"{\"title\":\"Adaptive Duty Cycling for Energy Harvesting Systems\",\"authors\":\"Jason Hsu, S. Zahedi, A. Kansal, M. Srivastava, V. Raghunathan\",\"doi\":\"10.1145/1165573.1165616\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Harvesting energy from the environment is feasible in many applications to ameliorate the energy limitations in sensor networks. In this paper, we present an adaptive duty cycling algorithm that allows energy harvesting sensor nodes to autonomously adjust their duty cycle according to the energy availability in the environment. The algorithm has three objectives, namely: (a) achieving energy neutral operation, i.e., energy consumption should not be more than the energy provided by the environment; (b) maximizing the system performance based on an application utility model subject to the above energy-neutrality constraint; and (c) adapting to the dynamics of the energy source at run-time. We present a model that enables harvesting sensor nodes to predict future energy opportunities based on historical data. We also derive an upper bound on the maximum achievable performance assuming perfect knowledge about the future behavior of the energy source. Our methods are evaluated using data gathered from a prototype solar energy harvesting platform and we show that our algorithm can utilize up to 58% more environmental energy compared to the case when harvesting-aware power management is not used\",\"PeriodicalId\":119229,\"journal\":{\"name\":\"ISLPED'06 Proceedings of the 2006 International Symposium on Low Power Electronics and Design\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-10-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"243\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ISLPED'06 Proceedings of the 2006 International Symposium on Low Power Electronics and Design\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1165573.1165616\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ISLPED'06 Proceedings of the 2006 International Symposium on Low Power Electronics and Design","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1165573.1165616","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 243

摘要

从环境中收集能量在许多应用中是可行的,以改善传感器网络中的能量限制。在本文中,我们提出了一种自适应占空比算法,该算法允许能量收集传感器节点根据环境中的能量可用性自主调整其占空比。该算法有三个目标,即:(a)实现能量中性运行,即能耗不超过环境提供的能量;(b)基于受上述能量中性约束的应用实用新型的系统性能最大化;(c)适应能源运行时的动态变化。我们提出了一个模型,使收集传感器节点能够根据历史数据预测未来的能源机会。我们还推导出了最大可实现性能的上限,假设对能源的未来行为有充分的了解。使用从原型太阳能收集平台收集的数据对我们的方法进行了评估,我们表明,与不使用收集感知电源管理的情况相比,我们的算法可以利用高达58%的环境能源
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive Duty Cycling for Energy Harvesting Systems
Harvesting energy from the environment is feasible in many applications to ameliorate the energy limitations in sensor networks. In this paper, we present an adaptive duty cycling algorithm that allows energy harvesting sensor nodes to autonomously adjust their duty cycle according to the energy availability in the environment. The algorithm has three objectives, namely: (a) achieving energy neutral operation, i.e., energy consumption should not be more than the energy provided by the environment; (b) maximizing the system performance based on an application utility model subject to the above energy-neutrality constraint; and (c) adapting to the dynamics of the energy source at run-time. We present a model that enables harvesting sensor nodes to predict future energy opportunities based on historical data. We also derive an upper bound on the maximum achievable performance assuming perfect knowledge about the future behavior of the energy source. Our methods are evaluated using data gathered from a prototype solar energy harvesting platform and we show that our algorithm can utilize up to 58% more environmental energy compared to the case when harvesting-aware power management is not used
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
×
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:481959085
Book学术官方微信