基于数字孪生的以用户为中心的多播短视频流资源管理

IF 8.7 1区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Journal of Selected Topics in Signal Processing Pub Date : 2023-12-18 DOI:10.1109/JSTSP.2023.3343626
Xinyu Huang;Wen Wu;Shisheng Hu;Mushu Li;Conghao Zhou;Xuemin Shen
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引用次数: 0

摘要

多播短视频流(MSVS)通过同时向多个用户传输相同的视频序列,可以有效降低网络流量负荷。现有的 MSVS 方案主要依靠聚合视频请求来预留带宽和计算资源,无法满足用户多样化的动态服务需求,尤其是当用户的刷卡行为呈现时空波动时。本文提出了一种基于数字孪生(DT)技术的以用户为中心的资源管理方案,旨在提高用户满意度并减少资源消耗。首先,我们设计了一个用户数字孪生(UDT)辅助资源预订框架。具体来说,为单个用户构建 UDT,存储用户的历史数据,用于更新组播组和抽象有用信息。从 UDT 中抽象出刷卡概率分布和推荐视频列表,以预测带宽和计算资源需求。利用参数化的西格莫德函数来描述组播组的用户满意度。其次,我们提出了一个非凸带宽和计算资源联合预订问题,通过利用切线函数近似替代凹部分,该问题被转化为一个凸片段问题。然后,我们开发了一种低复杂度调度算法,以找到最优的资源预留决策。基于真实世界数据集的仿真结果表明,所提出的方案在用户满意度和资源消耗方面优于基准方案。
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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' 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.
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来源期刊
IEEE Journal of Selected Topics in Signal Processing
IEEE Journal of Selected Topics in Signal Processing 工程技术-工程:电子与电气
CiteScore
19.00
自引率
1.30%
发文量
135
审稿时长
3 months
期刊介绍: The IEEE Journal of Selected Topics in Signal Processing (JSTSP) focuses on the Field of Interest of the IEEE Signal Processing Society, which encompasses the theory and application of various signal processing techniques. These techniques include filtering, coding, transmitting, estimating, detecting, analyzing, recognizing, synthesizing, recording, and reproducing signals using digital or analog devices. The term "signal" covers a wide range of data types, including audio, video, speech, image, communication, geophysical, sonar, radar, medical, musical, and others. The journal format allows for in-depth exploration of signal processing topics, enabling the Society to cover both established and emerging areas. This includes interdisciplinary fields such as biomedical engineering and language processing, as well as areas not traditionally associated with engineering.
期刊最新文献
Front Cover Table of Contents IEEE Signal Processing Society Information Introduction to the Special Issue Near-Field Signal Processing: Algorithms, Implementations and Applications IEEE Signal Processing Society Information
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