Convergence Orchestration

Convergence orchestration focuses on the efficient and intelligent management of diverse, interconnected resources—from computing and networking to energy and data—to optimize performance and minimize costs across various domains. Current research emphasizes the use of machine learning, particularly reinforcement learning and deep learning models like Graph Neural Networks, to dynamically allocate resources and adapt to changing conditions in applications ranging from distributed learning to intelligent transportation systems. This field is significant for its potential to improve the efficiency and scalability of complex systems, impacting areas like cloud computing, edge AI, and industrial automation.