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Low-energy algorithm for self-controlled Wireless Sensor Nodes

机译:自控无线传感器节点的低能耗算法

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In Internet of Things (IoT), the lifespan of Wireless Sensor Networks (WSN) has often become an issue. Sensor nodes are typically battery powered. However, high energy consumption by Radio Frequency (RF) module limits the lifespan of sensor nodes. In conventional WSN, the frequency of data transmission is normally fixed or adjusted according to requests from the gateway. In this paper, we present a WSN system for intelligent sensing. We propose a low-energy algorithm for sensor data transmission from sensor nodes for such system. In this algorithm, the sensor nodes are able to self-control their data transmission according to the trends of data. We adopt Adaptive Duty Cycle for adjustment of data transmission frequency and Compressive Sensing (CS) for sensor data compression. The simulation results show that Collective Transmission with CS-based data compression achieves 83.34% of RF energy reduction for the best-case transmission and 83.31% of RF energy reduction in the worst-case transmission, compared to the Continuous Transmission.
机译:在物联网(IoT)中,无线传感器网络(WSN)的寿命通常成为一个问题。传感器节点通常由电池供电。但是,射频(RF)模块的高能耗限制了传感器节点的寿命。在常规的WSN中,数据传输的频率通常根据网关的请求是固定的或调整的。在本文中,我们提出了一种用于智能传感的WSN系统。对于这种系统,我们提出了一种用于从传感器节点传输传感器数据的低能耗算法。在该算法中,传感器节点能够根据数据趋势自控其数据传输。我们采用自适应占空比来调整数据传输频率,并采用压缩传感(CS)进行传感器数据压缩。仿真结果表明,与连续传输相比,具有基于CS的数据压缩的集体传输在最佳情况下的传输可减少83.34%的RF能量,在最坏情况下的传输可减少83.31%的RF能量。

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