论文标题
最佳多播服务链控制：数据包处理，路由和重复
Optimal Multicast Service Chain Control: Packet Processing, Routing, and Duplication
论文作者
论文摘要
分布式计算（云）网络，例如移动边缘计算（MEC），在有效的托管，运行和交付实时流处理应用程序（例如工业自动化，沉浸式视频和增强现实）中起着越来越重要的作用。尽管此类应用程序需要及时处理对多个用户/设备同时有用的实时流，但现有技术缺乏有效的机制来处理其日益多样性的性质，从而导致不必要的流量冗余和相关的网络拥塞。在本文中，我们介绍了分布式数据包处理，路由和重复策略的设计，以最佳控制多播流处理服务。我们介绍了由于有效的数据包重复而导致的扩大能力区域的表征，并设计了第一个完全分布的多播交通管理政策，该政策稳定了容量区域内部的任何输入率，同时最大程度地降低了整体运营成本。数值结果证明了拟议的政策在分布式计算网络上实现流程处理服务的吞吐量和成本优势的有效性。
Distributed computing (cloud) networks, e.g., mobile edge computing (MEC), are playing an increasingly important role in the efficient hosting, running, and delivery of real-time stream-processing applications such as industrial automation, immersive video, and augmented reality. While such applications require timely processing of real-time streams that are simultaneously useful for multiple users/devices, existing technologies lack efficient mechanisms to handle their increasingly multicast nature, leading to unnecessary traffic redundancy and associated network congestion. In this paper, we address the design of distributed packet processing, routing, and duplication policies for optimal control of multicast stream-processing services. We present a characterization of the enlarged capacity region that results from efficient packet duplication, and design the first fully distributed multicast traffic management policy that stabilizes any input rate in the interior of the capacity region while minimizing overall operational cost. Numerical results demonstrate the effectiveness of the proposed policy to achieve throughput- and cost-optimal delivery of stream-processing services over distributed computing networks.
