Digital Twin Based User-Centric Resource Management for Multicast Short Video Streaming

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...

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Bibliographic Details
Published in:IEEE journal of selected topics in signal processing 2024-01, Vol.18 (1), p.50-65
Main Authors: Huang, Xinyu, Wu, Wen, Hu, Shisheng, Li, Mushu, Zhou, Conghao, Shen, Xuemin
Format: Article
Language:English
Subjects:
Algorithms
Bandwidth
Bandwidths
Behavioral sciences
Communications traffic
Computation
Consumption
Digital twin
Digital twins
multicast transmission
Multicasting
Real-time systems
Resource management
Servers
Streaming media
User requirements
User satisfaction
user-centric
Video transmission
Wireless networks
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Summary: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 article, 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.
ISSN:1932-4553
1941-0484
DOI:10.1109/JSTSP.2023.3343626