Author: IVAN DAVID ALFONSO DIAZ
Programme: Doctoral Programme in Network and Information Technologies
Language: English
Supervisors: Dr. Jordi Cabot, Dr. Kelly Garcés, Dr. Harold Castro
Faculty / Institute: Doctoral School UOC
Subjects: Computer Science
Key words: Internet of things, model-driven engineering, self-adaptive systems, domain specific language, edge and fog computing

Area of knowledge: Network and Information Technologies

Summary

Today, most Internet of Things (IoT) systems leverage edge and fog computing to meet increasingly restrictive requirements and improve quality of service (QoS). Although these multi-layer architectures can improve system performance, their design is challenging because the dynamic and changing IoT environment can impact the QoS and system operation. In this thesis, we propose a modeling-based approach that addresses the limitations of existing studies to support the design, deployment, and management of self-adaptive IoT systems. We have designed a domain specific language (DSL) to specify the self-adaptive IoT system, a code generator that generates YAML manifests for the deployment of the IoT system, and a framework based on the MAPE-K loop to monitor and adapt the IoT system at runtime. Finally, we have conducted several experimental studies to validate the expressiveness and usability of the DSL and to evaluate the ability and performance of our framework to address the growth of concurrent adaptations on an IoT system.