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.

中文翻译：

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无线传感器网络中基于增量编码和T-RLE的无损压缩方法

在无线传感器网络（WSN）中，数据的发送/接收（数据通信）是最耗电的，因为传感器节点依赖于通常容量有限的不可充电电池。数据压缩是可以帮助减少无线传感器节点之间交换的数据量从而节省功耗的技术之一。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增量编码和两次出现字符求解（T-RLE）算法的新颖无损压缩方法。T-RLE是RLE算法的优化，旨在提高压缩率。这种方法将导致更少的存储成本和更少的带宽来传输数据，通常会对传感器节点的寿命和网络寿命产生积极影响。我们使用了传感器范围项目中的实际部署数据（温度和湿度）来评估我们方法的性能。与某些传统算法相比，结果显示出显着的改进。