Optimal delivery of multi-media content over networks

Arthur Allen
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引用次数: 6

Abstract

In this paper, we describe scalable optimal methods for delivering archived and live multi-media content from servers to multi-media client players endowed with substantial RAM or disk-based buffers. These methods result from the application of linearoptimization theory (linear programming) to the problem of how best to modulate the flow rate of constant-bit-rate (CBR) content for all sessions linking a server to its clients, in which session flow rates are subject to upper and lower bound constraints, and aggregate flow cannot exceed a specified maximum. An efficient O(n) algorithm to maximize aggregate flow is described. We propose a tunable minimum constraint on session flows that is shown to result in a rapid and sustained accumulation of reserve content within a player's buffer. An associated Call Admission Control (CAC) algorithm is also described. The benefits of the methods described include improved server efficiency, enhanced end-user experience (QOS), cost effective end to-end content delivery, directly from origin servers to clients without need of intervening edge-caching technology.
多媒体内容在网络上的最佳交付
在本文中,我们描述了可扩展的最佳方法,用于将存档和实时多媒体内容从服务器传送到具有大量RAM或基于磁盘的缓冲区的多媒体客户端播放器。这些方法是将线性优化理论(线性规划)应用于如何最好地调节连接服务器与其客户端的所有会话的恒定比特率(CBR)内容的流量问题,其中会话流量速率受上限和下限约束,并且聚合流量不能超过指定的最大值。描述了一种有效的O(n)算法来最大化聚合流量。我们建议在会话流中设置一个可调的最小约束,这将导致玩家缓冲区中储备内容的快速和持续积累。还描述了一种相关的呼叫允许控制(CAC)算法。所描述的方法的好处包括提高服务器效率,增强终端用户体验(QOS),具有成本效益的端到端内容交付,直接从原始服务器到客户机,而不需要中间的边缘缓存技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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