Wireless Sensor Networks (WSNs) have significant limitations in terms of available bandwidth and energy. The limited bandwidth in WSNs can cause delays in message delivery, which does not suit the real-time sensing applications such as a gas leak. Moreover, in such applications, there are multi-modal sensors whose values like temperature, gas concentration, location, and CO $$_2$$ 2 levels must be transmitted together for correct and timely detection of a gas leak. In this paper, we propose a novel Z-order based data compression scheme, Z-compression, to reduce energy consumption and save bandwidth without increasing message delivery latency. Instead of using the popular Huffman tree style based encoding, the Z-compression uses Z-order encoding to map the multidimensional sensing data into one-dimensional binary stream transmitted using a single packet. Our experimental evaluations using different real-world datasets show that the Z-compression has a much better compression ratio, energy, and bandwidth savings than known schemes like LEC, Adaptive-LEC, FELACS, and TinyPack for multi-modal sensor data. Through the extensive experiments, we show that Z-compression is suitable for real-world sensing applications requiring high-stream rate WSNs and delay-tolerant low-power listening WSNs. In high-stream rate WSNs, the Z-compression can save bandwidth and increases the throughput. In low-power listening WSNs, by concatenating the Z-compressed data at selected reporting nodes, we can reduce the duty cycles of the nodes in WSNs, thus prolong the lifetime of the network, and still maintain the low distortion rate.

中文翻译：

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用于高速数据流和低功耗无线传感器网络的多模型 Z 压缩

无线传感器网络 (WSN) 在可用带宽和能量方面存在重大限制。WSN 中有限的带宽会导致消息传递延迟，这不适合气体泄漏等实时传感应用。此外，在此类应用中，存在多模式传感器，其温度、气体浓度、位置和 CO$_2$$ 2 水平等值必须一起传输，以便正确及时地检测气体泄漏。在本文中，我们提出了一种新颖的基于 Z 顺序的数据压缩方案 Z 压缩，以在不增加消息传递延迟的情况下降低能耗并节省带宽。而不是使用流行的基于霍夫曼树风格的编码，Z 压缩使用 Z 顺序编码将多维传感数据映射到使用单个数据包传输的一维二进制流。我们使用不同的真实世界数据集进行的实验评估表明，对于多模态传感器数据，Z 压缩比 LEC、Adaptive-LEC、FELACS 和 TinyPack 等已知方案具有更好的压缩比、能量和带宽节省。通过大量实验，我们表明 Z 压缩适用于需要高流率 WSN 和延迟容忍低功耗侦听 WSN 的现实世界传感应用。在高流率 WSN 中，Z 压缩可以节省带宽并增加吞吐量。在低功耗监听 WSN 中，通过在选定的报告节点连接 Z 压缩数据，我们可以减少 WSN 中节点的占空比，