Public defence in Computer Science, M.Sc. Asad Javed
The evolution of the Internet of Things (IoT) technology in smart city environments has led to an increase in the data volume, variety, and velocity. Consequently, the IoT-based systems need to process, manage, and preserve a large amount of real-time data closer to the data sources, also known as edge computing. Sometimes, the computing capabilities at the edge might be insufficient, requiring data processing to be moved towards another back-end server, called the cloud, to utilize high computational power, more memory, and storage space. However, data exchanges between IoT applications, the cloud, and the edge can suffer from a few weaknesses including network latency, bandwidth, security, and reliability. This raises the problem of separate software stacks used between the edge and the cloud with no unified fault-tolerant and scalable solution, hindering dynamic relocation of data processing.
This research investigates the scalability and fault tolerance of IoT applications in smart cities. The overall objective is to ensure that the smart city applications are resilient to failures and scale based on the increasing demands of users. The objective is pursued through three research questions, which identify some of the most significant challenges in smart cities: (i) How can IoT messaging standards enable real-time device-generated data processing and discovery? (ii) What is the role of edge computing in enabling scalable computation in dynamically changing environments? (iii) How can edge and cloud computing collectively provide fault tolerance capabilities? Each of the identified barriers is addressed through novel techniques presented in the research publications. Finally, the proposed solutions are validated by implementing them in various real-life case studies. The results indicate that, by adopting edge and cloud computing technologies, the proposed solutions can provide scalability, optimize network latency, and handle hardware- and network-based failures. The practical significance of this research is in the smart city environments that use data and technology to create economic development, improve sustainability, and enhance the quality of life for people living and working in the city.
Opponent: Associate Professor Jim Dowling, KTH Royal Institute of Technology, Sweden
Custos: Professor Kary Främling, Aalto University School of Science, Department of Computer Science
Contact details of the doctoral student: [email protected]
The public defence will be organised on campus and via Zoom. Link to the event
The thesis is publicly displayed 10 days before the defence in the publication archive Aaltodoc of Aalto University.