Network Convergence

Network convergence, encompassing the integration of computing and network resources for efficient resource allocation and task execution, aims to optimize performance and address resource scarcity in increasingly complex systems. Current research focuses on developing adaptable and intelligent orchestration mechanisms, often employing machine learning, particularly reinforcement learning, and distributed cooperative routing algorithms to dynamically manage resources and meet stringent quality-of-service requirements in diverse applications like the Metaverse and federated learning. This field is crucial for advancing 6G networks and enabling the efficient deployment of intelligent applications, impacting both the design of future network architectures and the optimization of resource utilization in various domains.