arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2407.00552cs.NIcs.GR
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组播短视频流系统中的高效资源管理

Efficient Resource Management in Multicast Short Video Streaming Systems

Betty Searcy, Zurh Farus, Bronny Bush, Kevin Muhammad, Zubair Clinton

AI总结:

针对短视频流量激增下传统单播低效、组播资源分配复杂的问题,提出新型组播资源管理框架,通过动态优化分配平衡成本与体验,实验验证其可降带宽、减延迟、提升用户满意度。

摘要:

短视频内容的爆火(尤其是通过TikTok、Instagram这类平台)已导致数据流量呈指数级增长,给网络资源管理带来了严峻挑战。传统单播流方法虽然原理简单,但在需要同时向大量用户分发视频的场景下效率低下。组播流通过向多个用户发送单条流,可大幅降低所需带宽,但也带来了资源分配的复杂性,在带宽有限、用户需求异构的无线环境中尤为突出。本文提出了一种专为短视频内容高效分发设计的新型组播资源管理框架。该框架动态优化资源分配,以提升多用户的服务质量(QoS)和体验质量(QoE),在成本、效率与用户满意度之间实现权衡平衡。我们实现了一系列优化算法,这些算法考虑了多样的网络条件与用户需求,可确保在不同网络拓扑下实现最优服务交付。实验结果表明,与传统组播方法相比,我们的框架能有效降低带宽占用、减少视频启动延迟,显著提升整体用户满意度。本研究不仅深化了对组播流动态特性的理解,还为拥塞网络环境下可扩展的高效视频分发策略提供了实践参考。

英文摘要:

The surge in popularity of short-form video content, particularly through platforms like TikTok and Instagram, has led to an exponential increase in data traffic, presenting significant challenges in network resource management. Traditional unicast streaming methods, while straightforward, are inefficient in scenarios where videos need to be delivered to a large number of users simultaneously. Multicast streaming, which sends a single stream to multiple users, can drastically reduce the required bandwidth, yet it introduces complexities in resource allocation, especially in wireless environments where bandwidth is limited and user demands are heterogeneous. This paper introduces a novel multicast resource management framework tailored for the efficient distribution of short-form video content. The proposed framework dynamically optimizes resource allocation to enhance Quality of Service (QoS) and Quality of Experience (QoE) for multiple users, balancing the trade-offs between cost, efficiency, and user satisfaction. We implement a series of optimization algorithms that account for diverse network conditions and user requirements, ensuring optimal service delivery across varying network topologies. Experimental results demonstrate that our framework can effectively reduce bandwidth usage and decrease video startup delay compared to traditional multicast approaches, significantly improving overall user satisfaction. This study not only advances the understanding of multicast streaming dynamics but also provides practical insights into scalable and efficient video distribution strategies in congested network environments.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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