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Context Aware Compression for Environmental Edge Devices using LPWAN
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DOI：10.1109/IECON48115.2021.9589620.png)
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摘要
En 中文
Internet-of-Things (IoT) devices and their sensors are capable of monitoring diverse environments and generate a massive amount of data to he communicated to a sink node (base station) for further analysis. In many cases they are located outdoors in harsh conditions and are powered by battery. It is highly desired to avoid accessing them for battery replacement and for many a battery lifespan of about 10 years or more is considered a prominent advantage. The main contributor for power consumption of IoT constrained devices with limited processing and memory performance is the communication module, and in Low-Power Wide-Area Network (LPWAN) it is the transmit operation. The aim of this paper will be to minimize power consumption of edge devices by reducing the transmitted bits. This paper will first review existing studies and evaluate the most appropriate compression algorithms for LPWAN constrained edge devices. Our results show that by adjusting the latency and the algorithms thresholds a great deal of energy could be saved, up to 70%-99% depending on applications and data types. We then propose a novel context-aware adaptive data compression algorithm which takes into account the operating environment and sensor data types which balances system response and power consumption.
Keyword:
Internet-of-Things
IoT
data compression
LP-WAN
Algorithm
data transmission
energy efficient
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