Public defence in Networking Technology, M.Sc. Si-Ahmed Naas

The title of the thesis: An AI-based Framework to Optimize Mobile Services

Doctoral student: Si-Ahmed Naas
Opponent: Prof. Christian Becker, University of Stuttgart, Germany
Custos: Prof. Stephan Sigg, Aalto University School of Electrical Engineering, Department of Information and Communications Engineering 

The number of mobile network subscribers is expected to reach 7.7 billion by 2028, which poses unprecedented requirements for sustaining emerging mobile networks. With the development of the Internet of Things (IoT), new services for 5G verticals, and new autonomous mobile participants such as vehicles, drones, and robots, mobile networks need to meet increasingly stringent performance requirements, particularly in terms of latency and bandwidth. 

To address these challenges, adaptivity propelled by artificial intelligence (AI) is emerging as a necessary design feature for future mobile networks. In recent years, many studies have introduced AI to improve various key performance indicators and reduce the operational costs of mobile services. 

This dissertation addresses the challenges emerging from the need for practical orchestrator architecture that optimizes mobile services. Specifically, an AI-based orchestrator is proposed that improves low data rate mobile services by integrating emotion information to enhance the level of personalization. It also improves high data rate mobile services (virtual reality(VR)) using efficient schemes that ensure a smooth and lightweight streaming VR experience. Additionally, a novel knowledge-sharing mechanism empowered by an encryption scheme is proposed to enable a secure and practical alternative to data sharing, which improves the mobile service inference accuracy and protects user data privacy.

Thesis available for public display 10 days prior to the defence at: https://aaltodoc.aalto.fi/doc_public/eonly/riiputus/

Doctoral theses in the School of Electrical Engineering: https://aaltodoc.aalto.fi/handle/123456789/53