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An efficient and adaptive data compression technique for energy conservation in wireless sensor networks

机译:无线传感器网络中节能的高效和自适应数据压缩技术

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Wireless sensor networks are superior to wired sensing systems from the economical side provided that the latter require a separate twisted shielded-pair wire connection. Thus, implementation costs for the latter are high. However, wireless sensors have to function for an extensive period of time in order to achieve cost minimization and to successfully complete their particular mission. Therefore, conserving the allocated energy is very important and represents a major dilemma which stands against the wide-spreading of this technology. In this paper, a novel local adaptive data compression based on Fuzzy transform is proposed to minimize the bandwidth, the memory space, and the energy consumed in radio communication. An evaluation of the compression technique is provided. During this evaluation, the proposed technique is examined using real temperature data. The results have shown that the proposed technique can highly reduce the overall power consumption by up to 90 percent. Moreover, a modification of the proposed technique is presented which improves the accuracy of the recovered signal even with high compression ratios.
机译:无线传感器网络优于来自经济侧的有线传感系统,只要后者需要单独的双绞线对线连接。因此,后者的实施成本很高。然而,无线传感器必须在广泛的时间内起作用,以实现成本最小化并成功完成其特定的任务。因此,节省分配的能量非常重要,代表了一种主要的困境,这些困境具有抗于这种技术的广泛传播。在本文中,提出了一种基于模糊变换的新型自适应数据压缩,以最小化无线电通信中消耗的带宽,存储空间和消耗的能量。提供了对压缩技术的评估。在该评估期间,使用真实温度数据检查所提出的技术。结果表明,该技术可以高达90%的技术可以高度降低整体功耗。此外,介绍了所提出的技术的修改,其即使具有高压缩比而提高了回收信号的精度。

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