Experimental Serverless Architecture for Real-Time Sensor Data Monitoring in Fog Computing Environments

The rapid growth of IoT (Internet of Things) and Fog Computing technologies has brought about new opportunities and challenges in data monitoring and processing. This research focuses on the feasibility of using a Function-as-a-Service (FaaS) solution, specifically OpenWhisk, for monitoring sensor data in a Fog Computing environment. The study includes an analysis of existing tools, the development of an experimental use case, and evaluation of the solution's real-time properties and scalability. The objectives are to assess the practical viability of the proposed serverless architecture for edge device monitoring and provide insights into its benefits and challenges. The thesis presents an introduction, background information, analysis of FaaS tools, exploration of OpenWhisk, use case definition, architecture details, experimental deployment, feasibility demonstration, and conclusions. This research contributes to the understanding of efficient sensor data monitoring in Fog Computing environments, offering valuable insights for future studies.