Abstract
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 Huffman code. 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%.
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