  Multicast short video streaming (MSVS) can effectively reduce network traffic
load by delivering identical video sequences to multiple users simultaneously.
The existing MSVS schemes mainly rely on the aggregated video requests to
reserve bandwidth and computing resources, which cannot satisfy users' diverse
and dynamic service requirements, particularly when users' swipe behaviors
exhibit spatiotemporal fluctuation. In this paper, we propose a user-centric
resource management scheme based on the digital twin (DT) technique, which aims
to enhance user satisfaction as well as reduce resource consumption. Firstly,
we design a user DT (UDT)-assisted resource reservation framework.
Specifically, UDTs are constructed for individual users, which store users'
historical data for updating multicast groups and abstracting useful
information. The swipe probability distributions and recommended video lists
are abstracted from UDTs to predict bandwidth and computing resource demands.
Parameterized sigmoid functions are leveraged to characterize multicast groups'
user satisfaction. Secondly, we formulate a joint non-convex bandwidth and
computing resource reservation problem which is transformed into a convex
piecewise problem by utilizing a tangent function to approximately substitute
the concave part. A low-complexity scheduling algorithm is then developed to
find the optimal resource reservation decisions. Simulation results based on
the real-world dataset demonstrate that the proposed scheme outperforms
benchmark schemes in terms of user satisfaction and resource consumption.
