Keynote: Transforming Networking Through Artificial Intelligence: From Best Effort to Knowledge Aware Networking

Prof Antoine Bagula: (ISAT Laboratory (Head) Department of Computer Science University of the Western Cape South Africa).

Abstract:

The Internet has evolved into a universal platform for all forms of modern communication. Initially, it was constructed on the principle of an intelligent edge and a core dump, utilizing a best-effort routing model that enabled it to scale massively and support hundreds of millions of nodes. The shift towards a more intelligent Internet began with the introduction of virtualization and the Software-Defined Networking (SDN) paradigm, which successfully separated the control and data planes. A major advancement was achieved with the incorporation of Artificial Intelligence (AI) into networking through the Knowledge-Defined Networking (KDN) paradigm, allowing networks to extract valuable insights from data process.

Building on this foundation, Knowledge-Aware Networking (KAN) introduces a ground-breaking paradigm that utilizes multi-controller SDN architectures to create innovative learning models for cooperative, competitive, and diverse environments. This approach aims to significantly enhance security, resilience, and intelligence within the network. In KAN, cooperative learning employs the Federated Learning model, where multiple clients collaboratively train machine learning models. Competitive learning involves choosing the most suitable model for a particular use case from a pool of models. Diversity learning replicates the same model across different servers and uses a voting mechanism to ensure fault tolerance.

Knowledge-Aware Networking holds the potential to redefine the landscape of networking, embedding intelligence, efficiency, and robustness into the core of our communication infrastructure. This keynote is dedicated to elucidating the transformative impact of artificial intelligence on networking, emphasizing the transition from traditional best-effort approaches to the more sophisticated realm of knowledge-aware networking. Throughout this presentation, we will delve into the intricacies of the KAN architecture, unravelling its layers and exploring the myriad learning models it accommodates. Moreover, we will examine how KAN empowers networks to operate with greater intelligence and autonomy, facilitated by collaborative, competitive, and diversity learning.