Aggregation techniques for the internet of things: An overview

Internet of Thing (IoT) can be generally defined as a network connecting millions of smart objects, most of them equipped with sensors. Since sensors are devices generating a huge amount of data, the transmission of raw data to the edge nodes and then to higher level cloud nodes may give rise to transmission delays and energy consumption. Furthermore, sensors are characterized by limited resources. For all these reasons, aggregation techniques are required to reduce the size of data to be transmitted and stored, while maintaining a reasonable level of approximation. In this paper, we propose an overview of a set of aggregation techniques which may be exploited in IoT. We present a set of techniques, ranging from Space Filling Curves, to Q-digest, Wavelets, Gossip aggregation, and Compressive Sensing. We also show how these techniques are exploited in IoT applications.