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Huffman coding algorithm for compression of sensor data in wireless sensor networks

机译:用于无线传感器网络中传感器数据压缩的霍夫曼编码算法

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Sensor data exhibit strong correlation in both space and time. Many algorithms have been proposed to utilize these characteristics. However, each sensor just utilizes neighboring information, because its communication range is restrained. Information that includes the distribution and characteristics of whole sensor data provides other opportunities to enhance the compression technique. In this paper, we propose an orthogonal approach for compressing sensor readings based on a novel feedback technique. That is, the base station or a super node generates Huffman code for the compression of sensor data and broadcasts it into sensor networks as feedback information. All sensor nodes that have received the information compress their sensor data and transmit them to the base station. We call this approach as feedback-diffusion and this modified Huffman coding as sHuffman coding. In order to show the superiority of our approach, we compare it with the existing data compression algorithms in terms of the lifetime of the sensor network. As a result, our experimental results show that the whole network lifetime was prolonged by about 30%.
机译:传感器数据在时空上都表现出很强的相关性。已经提出了许多算法来利用这些特性。但是,每个传感器仅利用邻近信息,因为其通信范围受到限制。包括整个传感器数据的分布和特征的信息为增强压缩技术提供了其他机会。在本文中,我们提出了一种基于新颖反馈技术的用于压缩传感器读数的正交方法。即,基站或超级节点生成用于压缩传感器数据的霍夫曼码,并将其作为反馈信息广播到传感器网络中。接收到该信息的所有传感器节点压缩其传感器数据,并将其发送到基站。我们将这种方法称为反馈扩散,将这种经过修改的霍夫曼编码称为sHuffman编码。为了展示我们方法的优越性,我们将其与现有数据压缩算法在传感器网络的寿命方面进行了比较。结果,我们的实验结果表明,整个网络的寿命延长了约30%。

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