压缩无线传感器网络通信的能量和寿命分析

Celalettin Karakus, A. Gurbuz, B. Tavlı
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引用次数: 3

摘要

提高无线传感器网络(WSNs)的寿命直接关系到传感器节点计算和通信操作的能量效率。利用压缩感知(CS)理论的概念,可以用一定数量的随机线性测量来重建稀疏信号,这比传统信号重建技术所需的测量数量要少得多。在本研究中,我们建立了能量耗散模型,定量比较了CS和传统信号处理技术的能量耗散特性。该模型用于构建线性规划(LP)框架,该框架共同捕获基于CS的技术和传统技术的计算和通信的能源成本。观察到CS延长了稀疏信号的网络生存期。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Energy and lifetime analysis of compressed Wireless Sensor Network communication
Improving the lifetime of Wireless Sensor Networks (WSNs) is directly related with the energy efficiency of computation and communication operations in the sensor nodes. By employing the concepts of Compressive Sensing (CS) theory it is possible to reconstruct a sparse signal with a certain number of random linear measurements, which is much less than the number of measurements necessary in conventional signal reconstruction techniques. In this study, we built an energy dissipation model to quantitatively compare the energy dissipation characteristics of CS and conventional signal processing techniques. This model is used to construct a Linear Programming (LP) framework that jointly captures the energy costs for computing and communication both for CS based techniques and conventional techniques. It is observed that CS prolongs the network lifetime for sparse signals.
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