The present master thesis covers the examination of Edge Computing frameworks using the Design Science Research (DSR) approach.
First, it analyzes the foundations and de velopment of the Internet of Things (IoT) and Edge Computing in order to explore their relation. It comes to the conclusion that the major distinction is located in the architectural composition whereas it also reveals that both paradigms do have a common historical background and Edge Computing is seen to be the next step in the evolution of IoT.
Next, a conceptual evaluation of present commercial and open-source Edge Computing frame works using the Analytic Hierarchy Process (AHP) is conducted. It reveals that Azure IoT Edge is the most suitable choice for the experimental edge intelligence use case. Sev eral evaluation criteria ranging from communication protocols, network capabilities, standardization, platform operations, development lifecycle, hardware requirements, and security aspects are developed and applied to the evaluation process. Finally, these results are evaluated in the course of a proof of concept (PoC) implementation for a data-driven Edge Computing use case using the prior evaluated framework of Azure IoT Edge.
It shows that the framework is suitable for implementing use cases of this type as it passes the validation against a subset of the previously used evaluation criteria.