Video Stream Caching Based on Digital Twin Cooperative Caching

The rapid growth of short-form video and the emergence of a large number of video entertainment applications have placed greater demands on video delivery and video caching, and video streaming analytics is of great value in scenarios such as smart surveillance, smart cities, and autonomous driving, but the high computational load, high bandwidth demand, and strict latency requirements make it difficult to deploy video streaming analytics through the traditional cloud computing paradigm. The recent emergence of the edge computing paradigm, which sinks computing tasks from the cloud to end devices and edge servers located at the edge of the network, can effectively solve these problems, which makes mobile edge computing (MEC) important. As a result, many edge computing studies for real-time video streaming analysis are emerging. However, existing techniques rarely consider digital twin (DT) technology. Therefore, in this paper, on the one hand, we study the problem of intelligent offloading of video stream cache (VSC) in mobile edge server cluster (MESC). On the other hand, Digital Twin Collaborative Caching (DTCC) algorithm is used to selectively store computation results of tasks and reduce system consumption.