In an increasingly connected world, the seamless mobile communication relies on the ability of network infrastructures to evolve and adapt. Enter Network Intelligence (NI) – an advanced concept that is poised to revolutionize future-generation mobile networks. The DAEMON (Data Analytics for Efficient and Mobile Network Management) project is at the forefront of this exciting development, aiming to optimize NI through the adoption of Artificial Intelligence (AI) models and integration into 6G mobile networks.
Importance of Network Intelligence in Future Generation Mobile Networks
To ensure the success of 6G and beyond, the quality of network intelligence (NI) running at schedulers, controllers, and orchestrators across network domains becomes crucial. The DAEMON project recognizes the significance of NI and emphasizes the need to enhance the current architectural vision of standardization bodies. By enabling comprehensive coordination across multiple NI instances operating within the network infrastructure, a powerful foundation for future mobile networks can be established.
Choosing the Right Models for Network Intelligence
The DAEMON project delves into the intricacies of selecting appropriate models for NI. The team specifically focuses on determining when to employ powerful yet non-interpretable deep learning (DL) models and when to prioritize statistical, analytical, or hybrid models. This thoughtful approach ensures that the chosen models align with the specific requirements of the network environment, striking a balance between accuracy and network-critical metrics.
Key Network Functionalities and NI Algorithms
In pursuit of its objectives, the DAEMON project has identified a specific list of key network functionalities. These functionalities serve as the foundation for the development and implementation of NI algorithms that fully exploit the potential of the proposed NI-native architecture. By addressing core network management tasks, this approach enables a smooth and efficient operation of future mobile networks.
Optimization of Machine Learning Solutions for Network Environments
The integration of Machine Learning (ML) solutions within network environments requires a fresh perspective. The DAEMON project focuses on rethinking the design and integration of ML solutions to tailor them to the unique challenges posed by network environments. By customizing AI techniques, practical NI algorithms can be empowered, catering specifically to the needs of network management functionalities.
The DAEMON Project’s Remarkable Achievements
Now in its third year of execution, the DAEMON project highlights a number of significant achievements, each aligned with its stated objectives. Notably, the project has generated five innovative patent applications, all of which have been selected for support by the prestigious Innovation Radar initiative of the European Commission. These accomplishments affirm the project’s dedication to pushing the boundaries of AI research and development.
As future mobile networks evolve, the role of Network Intelligence becomes increasingly vital. The DAEMON project’s unwavering focus on enhancing NI through the integration of AI models and its systematic approach to optimizing ML solutions is paving the way for a network landscape that is efficient, adaptive, and highly responsive to dynamic user demands. By embracing the potential of NI in future mobile network infrastructures, we are ushering in a new era of seamless connectivity and unparalleled user experiences.