Abstract
M.Ing. (Engineering Management)
In the last decade, there has been an increase in the number of IoT devices and applications. It is estimated that by 2020 more than 2 billion devices will be connected to the internet. With the increase in the number of devices, more data will be transferred to the servers. These huge amounts of data will require extraction, processing, and storage for future use. The current data management solutions cannot accommodate the increase in the data generated by these devices. The purpose of this work is to do research on data management considerations in IoT by asking the question of how we can design IoT networks that take into consideration data management and what solutions are available to address this increase in data. The aim of the research is to identify the key principles of data management, investigate techniques that can be used for data management, investigate the best possible frameworks that can be used for data management in IoT, and investigate data storage systems that would be suitable for use in IoT applications. The scope of the research is to study peer-reviewed articles on IoT and data management. This includes studying the different frameworks that exist currently, identifying their limitations and doing an analysis based on IoT design primitives to find a framework that attempts to meet all the desired requirements for an IoT data management framework.