有期限和优先级限制的沉浸式视频流传输调度

Tongtong Feng, Qi Qi, Bo He, Jingyu Wang
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引用次数: 0

摘要

在身临其境的视频流中,对截止日期有感知的传输调度至关重要。其目标是保证多链路中至少有某一区块在截止日期前完全交付,即交付率。现有模型注重最大化吞吐量和超低延迟,这使得带宽资源分配和用户满意度局部最优化,相比之下,身临其境视频流需要保证更多高优先级区块在个性化期限内交付。本文提出了一种有期限和优先级限制的沉浸式视频流传输调度方案。它建立了一个精确的带宽预测模型,可以灵敏地辅助调度决策。它将视频流分为各种媒体元素,并根据用户的个性化延迟敏感度阈值和媒体元素的优先级执行调度。我们通过跟踪仿真评估了我们的方案。与现有模型相比,结果进一步证明了我们方案的优越性,体验质量(QoE)提高了 12{/%}-31{/%}。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Deadline and Priority Constrained Immersive Video Streaming Transmission Scheduling
Deadline-aware transmission scheduling in immersive video streaming is crucial. The objective is to guarantee that at least a certain block in multi-links is fully delivered within their deadlines, which is referred to as delivery ratio. Compared with existing models that focus on maximizing throughput and ultra-low latency, which makes bandwidth resource allocation and user satisfaction locally optimized, immersive video streaming needs to guarantee more high-priority block delivery within personalized deadlines. In this paper, we propose a deadline and priority-constrained immersive video streaming transmission scheduling scheme. It builds an accurate bandwidth prediction model that can sensitively assist scheduling decisions. It divides video streaming into various media elements and performs scheduling based on the user's personalized latency sensitivity thresholds and the media element's priority. We evaluate our scheme via trace-driven simulations. Compared with existing models, the results further demonstrate the superiority of our scheme with 12{\%}-31{\%} gains in quality of experience (QoE).
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