Energy-efficient Communications for Improving Timely Progress of Intermittent Powered BLE Devices

IF 2.8 3区 计算机科学 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE
Chen-Tui Hung, Kai Xuan Lee, Yi-Zheng Liu, Ya-Shu Chen, Zhong-Han Chan
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引用次数: 0

Abstract

Battery-less devices offer potential solutions for maintaining sustainable Internet of Things (IoT) networks. However, limited energy harvesting capacity can lead to power failures, limiting the system’s quality of service (QoS) . To improve timely task progress, we present ETIME, a scheduling framework that enables energy-efficient communication for intermittent-powered IoT devices. To maximize energy efficiency while meeting the timely requirements of intermittent systems, we first model the relationship between insufficient harvesting energy and task behavior time. We then propose a method for predicting response times for battery-less devices. Considering both delays from multiple task interference and insufficient system energy, we introduce a dynamic wake-up strategy to improve timely task progress. Additionally, to minimize power consumption from connection components, we propose a dynamic connection interval adjustment to provide energy-efficient communication. The proposed algorithms are implemented in a lightweight operating system on real devices. Experimental results show that our approach can significantly improve progress for timely applications while maintaining task progress.
提高间歇供电BLE设备及时进度的节能通信
无电池设备为维持可持续的物联网(IoT)网络提供了潜在的解决方案。然而,有限的能量收集能力可能导致电源故障,从而限制了系统的服务质量(QoS)。为了提高任务进度的及时性,我们提出了ETIME,这是一个调度框架,可以为间歇性供电的物联网设备实现节能通信。为了最大限度地提高能源效率,同时满足间歇系统的及时性要求,我们首先建立了收集能量不足与任务行为时间之间的关系模型。然后,我们提出了一种预测无电池设备响应时间的方法。同时考虑多任务干扰造成的延迟和系统能量不足,引入动态唤醒策略,提高任务进度的及时性。此外,为了最大限度地减少连接组件的功耗,我们建议动态调整连接间隔以提供节能通信。所提出的算法在实际设备上的轻量级操作系统中实现。实验结果表明,我们的方法可以在保持任务进度的同时显著提高实时应用程序的进度。
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来源期刊
ACM Transactions on Embedded Computing Systems
ACM Transactions on Embedded Computing Systems 工程技术-计算机:软件工程
CiteScore
3.70
自引率
0.00%
发文量
138
审稿时长
6 months
期刊介绍: The design of embedded computing systems, both the software and hardware, increasingly relies on sophisticated algorithms, analytical models, and methodologies. ACM Transactions on Embedded Computing Systems (TECS) aims to present the leading work relating to the analysis, design, behavior, and experience with embedded computing systems.
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