Signal Characteristics on Sensor Data Compression in IoT -An Investigation
Signal Characteristics on Sensor Data Compression in IoT -An Investigation
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物联网中传感器数据压缩的信号特征 - 一项调查
DOI：
10.1109/sahcn.2016.7733016
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发表时间：
2016
期刊：
影响因子：
--
通讯作者：
A. Pal
中科院分区：
文献类型：
--
作者：
Tulika Bose;S. Bandyopadhyay;Sudhir Kumar;Abhijan Bhattacharyya;A. Pal
在物联网（IoT）中，众多不同类型的传感器生成大量数据，这些数据需要以最小的信息损失进行存储和处理。这就需要有效的压缩机制，使信息的损失最小化。因此，由具有不同信号特征的不同传感器生成的数据需要在压缩增益和信息损失之间实现最佳平衡。本文提出了一个独特的分析当代有损压缩算法应用于真实的现场传感器数据与不同的传感器动态。工作的目的是分类的压缩算法的基础上的传感器数据的信号特征，并将它们映射到不同的传感器数据类型，以确保有效的压缩。目前的工作是一个未来的推荐系统选择首选的压缩技术，为给定类型的传感器数据的垫脚石。
In Internet of Things (IoT), numerous and diverse types of sensors generate a plethora of data that needs to be stored and processed with minimum loss of information. This demands efficient compression mechanisms where loss of information is minimized. Hence data generated by diverse sensors with different signal features require optimum balance between compression gain and information loss. This paper presents a unique analysis of contemporary lossy compression algorithms applied on real field sensor data with different sensor dynamics. The aim of the work is to classify the compression algorithms based on the signal characteristics of sensor data and to map them to different sensor data types to ensure efficient compression. The present work is the stepping stone for a future recommender system to choose the preferred compression techniques for the given type of sensor data.