无基础设施感知的收获感知最优通信方案

IF 3.5 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS ACM Transactions on Internet of Things Pub Date : 2020-06-19 DOI:10.1145/3395928
L. Sigrist, R. Ahmed, Andres Gomez, L. Thiele
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引用次数: 15

摘要

用于长期监测的传感系统是新兴的物联网的重要组成部分。在该领域,能量收集和无基础设施通信使传感器节点能够真正自主和免维护地收集长期环境数据。由于通信的无基础设施性质,接收器并不总是可用的。环境提供的可变能量和接收器的移动性导致节点可用性不确定。在这项工作中,我们研究了无基础设施的数据传输方案,以优化发送方和接收方都表现出间歇性行为时的通信。我们依靠数据效用的概念,描述感测数据对接收器的重要性,以确定最佳的通信方案。导出使接收数据效用最大化的通信策略是一个凸优化问题。最终方案在无电池蓝牙低功耗传感器节点上实现并验证,该节点可与普通智能手机通信。我们的评估表明,该模型准确地捕获了应用场景,数据接收概率的最大均方根误差小于0.016。在不同的采集条件下,实验证明了该通信方案对不同采集条件的适应性,并显示出显著提高数据利用率。
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Harvesting-Aware Optimal Communication Scheme for Infrastructure-Less Sensing
Sensing systems for long-term monitoring constitute an important part of the emerging Internet of Things. In this domain, energy harvesting and infrastructure-less communication enable truly autonomous and maintenance-free operation of sensor nodes gathering long-term environmental data. Due to the infrastructure-less nature of the communication, receivers are not always available. The variable energy provided by the environment and the receiver’s mobility lead to non-deterministic node availability. In this work, we study infrastructure-less data transmission schemes to optimize communication when both senders and receivers exhibit intermittent behavior. We rely on the notion of data utility, describing the importance of sensed data to the receiver, to determine an optimal communication scheme. Deriving the communication policy that maximizes the utility of the received data is shown to be a convex optimization problem. The resulting scheme is implemented and validated on a batteryless Bluetooth Low Energy sensor node that communicates to commodity smartphones. Our evaluation demonstrates that the model accurately captures the application scenario with a maximum root-mean-square error of less than 0.016 in data reception probability. The communication scheme’s adaptiveness to variable harvesting conditions is experimentally demonstrated under varying harvesting conditions and is shown to significantly increase the data utility.
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来源期刊
CiteScore
5.20
自引率
3.70%
发文量
0
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