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Butterfly: μW Level ULP Sensor Nodes with High Task Throughput

delete2022-04-17
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OA
AI
C
Chong Zhang
L
Li Lu *
Y
Yihang Song
Q
Qianhe Meng
J
Junqin Zhang
X
Xiandong Shao
G
Guangyuan Zhang
M
Mengshu Hou
DOI:10.3390/s22083082delete
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Abstract

Abstract

En 中文
The rapid development of Internet of Things (IoT) applications calls for light-weight IoT sensor nodes with both low-power consumption and excellent task execution efficiency. However, in the existing system framework, designers must make trade-offs between these two. In this paper, we propose an edge-to-end integration design paradigm, Butterfly, which assists sensor nodes to perform sensing tasks more efficiently with lower power consumption through their (high-performance) network infrastructures (i.e., a gateway). On the one hand, to optimize the power consumption, Butterfly offloads the energy-intensive computational tasks from the nodes to the gateway with only microwatt-level power budget, thereby eliminating the power-consuming Microcontroller (MCU) from the node. On the other hand, we address three issues facing the optimization of task execution efficiency. To start with, we buffer the frequently used instructions and data to minimize the volume of data transmitted on the downlink. Furthermore, based on our investigation on typical sensing data structures, we present a novel last-bit transmission and packaging mechanism to reduce the data amount on the uplink. Finally, we design a task prediction mechanism on the gateway to support efficient scheduling of concurrent tasks on multiple MCU-free Butterfly nodes. The experiment results show that Butterfly can speed up the task rate by 4.91 times and reduce the power consumption of each node by 94.3%, compared to the benchmarks. In addition, Butterfly nodes have natural security advantages (e.g., anti-capture) as they offload the control function with all application information up to the gateway.
Keywords:
IoT
data efficiency
wireless sensing
ultra-low-power
security
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Journal

Sensors cover
Sensors
IF:
3.5
Papers:
7.1W
Citations:
20.9W

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