论文标题
使用选择性边缘压缩优化物联网和网络流量
Optimizing IoT and Web Traffic Using Selective Edge Compression
论文作者
论文摘要
物联网（IoT）设备和应用程序正在生成和传达大量数据，并且数据收集速度正在迅速提高。这些高通信量对于能源约束，数据封闭，无线移动设备和网络传感器的挑战。压缩通常用于减少网络流量，节省能源并使网络传输更快。但是，如果不明智地使用，压缩会损害性能。这项工作提出并评估基于数据特征和网络条件在网络边缘采用选择性压缩的机制。这种方法（i）改善了物联网环境中网络传输的性能，而（ii）提供了大量的数据节省。我们证明，在固定和动态变化的网络条件下，我们的库平均速度平均为2.18倍和2.03倍。此外，它还提供一致的数据节省，将数据压实到原始数据大小的19％。
Internet of Things (IoT) devices and applications are generating and communicating vast quantities of data, and the rate of data collection is increasing rapidly. These high communication volumes are challenging for energy-constrained, data-capped, wireless mobile devices and networked sensors. Compression is commonly used to reduce web traffic, to save energy, and to make network transfers faster. If not used judiciously, however, compression can hurt performance. This work proposes and evaluates mechanisms that employ selective compression at the network's edge, based on data characteristics and network conditions. This approach (i) improves the performance of network transfers in IoT environments, while (ii) providing significant data savings. We demonstrate that our library speeds up web transfers by an average of 2.18x and 2.03x under fixed and dynamically changing network conditions respectively. Furthermore, it also provides consistent data savings, compacting data down to 19% of the original data size.
