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A Lossless Compression Approach Based on Delta Encoding and T-RLE in WSNs

机译:基于WSN的Delta编码和T-RLE的无损压缩方法

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The sending/receiving of data (data communication) is the most power consuming in wireless sensor networks (WSN) since the sensor nodes are depending on batteries not generally rechargeable characterized by limited capacity. Data compression is among the techniques that can help to reduce the amount of the exchanged data between wireless sensor nodes resulting in power saving. Nevertheless, there is a lack of effective methods to improve the efficiency of data compression algorithms and to increase nodes’ energy efficiency. In this paper, we proposed a novel lossless compression approach based on delta encoding and two occurrences character solving (T-RLE) algorithms. T-RLE is an optimization of the RLE algorithm, which aims to improve the compression ratio. This method will lead to less storage cost and less bandwidth to transmit the data, which positively affects the sensor nodes’ lifetime and the network lifetime in general. We used real deployment data (temperature and humidity) from the sensor scope project to evaluate the performance of our approach. The results showed a significant improvement compared with some traditional algorithms.
机译:数据(数据通信)的发送/接收是无线传感器网络(WSN)中最功耗的功耗,因为传感器节点取决于不可充电的电池,其特征在于容量有限。数据压缩是可以有助于减少无线传感器节点之间交换数据量的技术之一,从而导致省电。然而,缺乏有效的方法来提高数据压缩算法的效率并提高节点的能效。在本文中,我们提出了一种基于Delta编码的新型无损压缩方法和两个出现的字符求解(T-RLE)算法。 T-RLE是RLE算法的优化,旨在提高压缩比。这种方法将导致较少的存储成本和较少的带宽来传输数据,这通常会影响传感器节点的生命周期和网络寿命。我们使用传感器范围项目的实际部署数据(温度和湿度)来评估我们方法的性能。与一些传统算法相比,结果表明显着改善。

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