具有成本效益的低延迟云视频会议

M. Hajiesmaili, Lok To Mak, Zhi Wang, Chuan Wu, Minghua Chen, A. Khonsari
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引用次数: 12

摘要

在最近的视频会议系统设计中提倡云计算范式,利用分布式云中丰富的跨多个地理区域的按需资源,提供更好的会议体验。云环境中典型的架构设计是在每个云站点中创建视频会议代理,即虚拟机,将用户分配给代理,并通过代理实现用户间通信。考虑到设备的多样性和用户的网络连接,代理还可以将会议流转码为最佳格式和比特率。在这个体系结构中,存在两个关键问题,即如何有效地将用户分配给代理,以及如何确定执行Transco编码任务的最佳代理,这是非常重要的,原因如下:(1)现有的基于邻近度的分配在用户间延迟方面可能不是最优的,因为它没有考虑会议会话中其他用户的位置;(2)代理可能具有异构带宽和处理可用性,因此应该仔细识别最佳的转码代理,以实现成本最小化,同时最好地服务所有需要转码流的用户。为了解决这些问题,我们提出了用户到代理分配和跨界代理选择问题,其目标是最小化会议提供商的运营成本,同时保持较低的会议延迟。优化问题本质上是组合问题,求解困难。利用马尔可夫近似框架,设计了一种分散算法,可证明收敛到最优解的有界邻域。提出了一种智能体排序方案,对算法进行适当的初始化,提高算法的收敛性。原型系统实现的结果表明,与普遍采用的替代方案相比,我们的设计在一组互联网规模的场景中降低了77%的运营成本,同时降低了会议延迟。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cost-Effective Low-Delay Cloud Video Conferencing
The cloud computing paradigm has been advocated in recent video conferencing system design, which exploits the rich on-demand resources spanning multiple geographic regions of a distributed cloud, for better conferencing experience. A typical architectural design in cloud environment is to create video conferencing agents, i.e., Virtual machines, in each cloud site, assign users to the agents, and enable inter-user communication through the agents. Given the diversity of devices and network connectivities of the users, the agents may also transcode the conferencing streams to the best formats and bitrates. In this architecture, two key issues exist on how to effectively assign users to agents and how to identify the best agent to perform a Transco ding task, which are nontrivial due to the following: (1) the existing proximity-based assignment may not be optimal in terms of inter-user delay, which fails to consider the whereabouts of the other users in a conferencing session, (2) the agents may have heterogeneous bandwidth and processing availability, such that the best Transco ding agents should be carefully identified, for cost minimization while best serving all the users requiring the transcoded streams. To address these challenges, we formulate the user-to-agent assignment and Transco ding-agent selection problems, which targets at minimizing the operational cost of the conferencing provider while keeping the conferencing delay low. The optimization problem is combinatorial in nature and difficult to solve. Using Markov approximation framework, we design a decentralized algorithm that provably converges to a bounded neighborhood of the optimal solution. An agent ranking scheme is also proposed to properly initialize our algorithm so as to improve its convergence. The results from a prototype system implementation show that our design in a set of Internet-scale scenarios reduces the operational cost by 77% as compared to a commonly-adopted alternative, while simultaneously yielding lower conferencing delays.
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