The management of ultra-large-scale data center resources aims to improve resource utilization and system performance. By employing intelligent scheduling algorithms and dynamic resource allocation technologies, data centers can adjust resource allocation in real-time according to load demands, ensuring the maximization of service quality and efficiency. This optimization not only reduces operational costs but also enhances data processing speed and system responsiveness.

Distributed virtualization is a computing system that dynamically integrates and optimizes resource utilization through virtualization technology. It virtualizes computing, storage, and network resources from multiple physical hosts and manages these resources collaboratively through a distributed hypervisor. Distributed virtualization also supports dynamic load balancing and resource migration, ensuring stable service delivery even during peak customer loads.

Edge-cloud collaborative QoS assurance targets millions of distributed edge sites and tens of millions of edge applications in carrier networks. By leveraging the collaboration between edge computing and cloud computing, it supports business loads such as cloud containers and Serverless functions, enabling millisecond-level on-demand loading, construction, and orchestration scheduling across edge-cloud and edge-edge environments. This approach optimizes network latency and improves end-to-end data transmission efficiency.