Understanding Data Analyzis in an End-to-End IoT Network

This is my Master Thesis in Communication Technology with specialization within Networks, Services and Applications from the Norwegian University of Science and Technology.

The thesis will describe how to build a full End-to-End IoT network to gather data from sensors using technologies as 6LoWPAN and Bluetooth Low Energy as well as physical sensors from Adafruit, the nRF52 from Nordic Semiconductor and the Raspberry Pi 2 and 3.

Abstract of the thesis:

The Internet of Things (IoT) is known as the concept of connecting everyday physical devices to the Internet. It is natural to assume that the popularity and development within this field will increase in the following years. This means that more and more things will be able to communicate over the Internet. In the process of developing IoT, an important part is to build reliable and scalable networks, and understanding where data should be processed concerning power consumption and costs of transferring data in various regions of the network.

The task of the thesis will be to access data in a complete prototype of an IoT network, and both collect and analyse the data. The goal is to study different alternatives for a typical IoT system and provide an overview of current state-of-the-art technologies, products and standards that can be used in such a setting. Data can be generated by using and comparing different sensors connected to end nodes in the network. A complete network of both microcontrollers and single-board computers will be built and explained in this thesis. The network will from now on be referred to as testbed.

Microcontrollers as end nodes in an IoT network will be the central element tested in this thesis. The primary focus is to establish a connection between two devices, A and B, and form a network between these that can transport data efficiently. A central point of discussion will be to find transfer protocols and technologies that can be used in such a system. It will be discussed the advantage and disadvantage of sending raw data, rather than doing the computation in the end nodes. The main focus will be on optimal throughput in the network. A deep understanding of the benefits of processing data in the end nodes, concerning power, costs and time is needed to achieve this.

Results from this work include graphs and discussions explaining in which case the different transport protocols suggested are preferred, from tests done in the testbed. These show that different protocols are suited for different usage and that one of the tested possibilities more stable than the other in the tests presented. Both protocols registered their highest measured goodput at approximately 600 bytes/second. Being a quite slow transfer rate, this opened up for another discussion about the possible use cases for future Bluetooth Low Energy (BLE)-based IoT applications.

Keywords: Optimizing payload sizes, fragmentation, maximizing through- put, power usage.