An Innovative Resource-based Dynamic Scheduling Video Computing and Network Convergence System

Live video streaming services have experienced significant growth, and it has imposed more stringent requirements on current media delivery networks. However, traditional media distribution methods have difficulty meeting the low latency and high bandwidth requirements of emerging live-streaming services. Therefore, for the live video service scenario, we propose a video computing and network convergence (VNCN) model containing multiple nodes and multiple users, which integrates the network and computing resource occupancy of each node in the system and the impact of the media delivery method on the live service. In addition, we also propose a resource-aware dynamic scheduling (RDS) algorithm, which dynamically schedules user requests based on the resources of each node to maximize user Quality of Service (QoS). Finally, the experimental results show that, compared with the commonly used Round-robin (RR) algorithm and the K-Nearest Neighbor (KNN) algorithm, our system can not only provide users with a high QoS live streaming service but also ensure a more balanced load on the resources of each node.