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On the performance of piecewise linear approximation techniques in WSNs

机译:论WSNS中分段线性近似技术的性能

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Energy consumption is the major constraint in the design and the deployment of Wireless Sensor Networks (WSNs). Since the transmission of data induces high energy costs in WSN device, many research efforts focus on reducing the transmission of the raw data by using lossy compression methods in order to improve energy efficiency with an acceptable data reconstruction tolerance. Thus, an intricate trade-off exists between energy saving using sampling compression, and the distortion of reconstructed data samples. In this paper, we present a survey on Piecewise Linear Approximation methods. A comparative analysis aims to evaluate the performance of the selected techniques in terms of energy consumption, compression ratio and distortion.
机译:能量消耗是设计和无线传感器网络(WSN)的部署的主要限制。由于数据的传输在WSN设备中引起高能量成本,因此许多研究努力通过使用有损压缩方法来减少原始数据的传输,以便提高能效具有可接受的数据重建公差。因此,使用采样压缩的节能之间存在复杂的权衡,以及重建数据样本的失真。在本文中,我们提出了一项关于分段线性近似方法的调查。比较分析旨在在能量消耗,压缩比和失真方面评估所选技术的性能。

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