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

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School of Science | Doctoral thesis (article-based) | Defence date: 2024-05-31

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en

Pages

95 + app. 65

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Aalto University publication series DOCTORAL THESES, 69/2024

Abstract

In recent years, the rise and continued popularity of connected applications has resulted in explosive growth in the demand for wireless broadband services of high speed, massive capacity, and ultra-low latency, such as video-on-demand services, Internet of Things, and mission critical applications. 5G technology is designed to provide the required connectivity in these applications. As a consequence of its continued success, seamless connectivity has become synonymous to a human right. Suffice to say, at the moment, due to the vast potential benefits of 5G technology, there is a kind of gold rush driving rapid worldwide deployments of 5G networks that has led to a significant gap in investment, research, and development of suitable operation support system (OSS) solutions for daily operation, monitoring and control of 5G networks. Furthermore, as the number of 5G deployments continue to rise, high data traffic volumes and stakeholder expectation of seamless connectivity from anything to anything has become the norm. In this regard, the need for suitable OSS solutions has become critical. This dissertation fills the identified gap in the following way, first, we design a scalable architecture that enables batch and stream processing of high throughput, high volume, and ultra-low-latency data driven OSS solutions to effectively support existing and 5G OSS use cases. Building on the resulting architecture, we extend existing, and in some cases develop new SON algorithms to meet 5G requirements. Particularly, we develop adaptive algorithms which focus on self-configuration, self-optimization, self-healing, and SON-coordination use cases. Furthermore, we introduce solutions for transitioning from the current mainly proprietary OSS hardware to vendor agnostic cloud-native dynamic infrastructure. Lastly, we make digitization of OSS operations more efficient. Specifically, we develop an artificial intelligence based solution (AIOps) for conducting OSS operations efficiently at cloud scale. Using the findings and proposed solutions in this dissertation, vendors, and service providers can design and implement suitable solutions that meet stringent business and technical requirements of applications running on top of 5G networks and beyond.

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Supervising professor

Ylä-Jääski, Antti, Prof., Department of Computer Science, Aalto University, Finland

Thesis advisor

Nurminen, Jukka K., Prof., University of Helsinki, Finland

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Parts

  • [Publication 1]: Mfula, H., Isotalo,T., Nurminen, J.K. Self-Optimization of Power Parameters in WCDMA Networks. In proceedings of the IEEE International Conference on High Performance Computing and Simulation, Amsterdam, The Netherlands, pages 80-87, July 2015.
    DOI: 0.1109/HPCSim.2015.72370241 View at publisher
  • [Publication 2]: Mfula, H., Nurminen, J.K. Business-aware SON Coordinator for LTEA Networks. In proceedings of the IEEE International Conference on High Performance Computing and Simulation, Innsbruck, Austria, pages 246-252, July 2016.
    DOI: 10.1109/HPCSim.2016.7568342 View at publisher
  • [Publication 3]: Mfula, H., Nurminen, J.K. Adaptive Root Cause Analysis for Self-Healing in 5G Networks. In proceedings of the IEEE International Conference on High Performance Computing and Simulation, Genoa, Italy, pages 100-108, July 2017.
    DOI: 10.1109/HPCS.2017.31 View at publisher
  • [Publication 4]: Mfula, H., Nurminen, J.K. Self-Healing Cloud Services in Private Multi-Clouds. In proceedings of the IEEE International Conference on High Performance Computing and Simulation, Orleans, France, pages 100-108, July 2018.
    DOI: 10.1109/HPCS.2018.00041 View at publisher
  • [Publication 5]: Mfula, H., Nurminen, J. K. A Unified Framework for 5G Radio Access Network Optimization Tool Development. In proceedings of the 11th IEEE International Conference on Service Oriented Computing and Applications, Paris, France, pages 100-115, 19-22 November 2018.
    DOI: 10.1109/SOCA.2018.00013 View at publisher
  • [Publication 6]: Mfula, H., Ylä-Jääski, A., Nurminen, J. K. Seamless Kubernetes Cluster Management in Multi-Cloud and Edge 5G Applications. In proceedings of the 18th IEEE International Conference on High Performance Computing and Simulation, Barcelona, Spain (virtual), 22-27 March 2021.

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