Public defence in Computer and Information Science, M.Sc. Harrison Mfula

Title of the thesis: Adaptive OSS: Principles and Design of an Adaptive OSS for 5G Networks

Doctoral student: Harrison Mfula
Opponent: Assistant professor Erkki Harjula, University of Oulu
Custos: Professor Antti Ylä-Jääski, Aalto University, School of Science, Department of Computer Science

Today, the major development in the telecommunication industry that is having the most impact around the world is 5G technology. However, despite the continued success of worldwide deployments of 5G networks, the ability to fully harness the transformative power of this technology has been hindered by a significant gap in the research and development of the Operations Support Systems (OSS). This suite of software tools and hardware, are essential for the daily operations, monitoring, and control of telecommunication networks, has thus far been fragmented and lacked a cohesive and adaptive approach.

The subject of the study revolved around the evolution and management of critical resources in telecommunication networks, specifically, addressing the gap in evolution and development of OSS solutions towards 5G.

The purpose of the study was to conduct research on emerging trends, challenges and to develop solutions for operation, monitoring and control of telecommunication networks.

The research results presented in this study extend the knowledge in the field of telecommunications and network management.

Key research outputs include, the development of an adaptable big data architecture, machine learning-based adaptive algorithms, a cloud-native dynamic OSS infrastructure management solution, and an artificial intelligence-based solution for conducting OSS operations at scale.

As a whole, the main result of the study is the proposal and development of Adaptive OSS for 5G Networks. It is a comprehensive solution for end-to-end critical resource management throughout the operational lifecycle of telecommunication networks.

The research brings new insights into the challenges and opportunities associated with OSS evolution towards 5G and beyond. By implementing Adaptive OSS solutions, stakeholders can dynamically allocate resources, optimize network performance, and respond proactively to changing demands and conditions in the operating environment.

The findings from the study can be applied by telecommunication infrastructure vendors, communication service providers (CSPs), and researchers in the field.

Overall, the research results show that as networks continue to evolve and expand towards 5G, the management of network resources will become increasingly critical. Hence, the proposed Adaptive OSS solution presents a practical way of meeting the demanding requirements and performance benchmarks of 5G  applications and provide a credible evolution path to 6G.

Keywords: Adaptive OSS, 5G, MEC, SON, Cloud-native OSS, AIOps, AI/ML

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

Contact information: 

Doctoral theses of the School of Science: https://aaltodoc.aalto.fi/handle/123456789/52