Content Delivery Networks (CDNs) have enabled large-scale, reliable, and efficient content distribution over the Internet. Although CDNs have been very successful in serving a large portion of Internet traffic, they have several drawbacks. Despite their distributed nature, they rely on largely centralized management and replication. This can affect availability in case of node failure. Further, CDNs are complex infrastructures that span multiple layers of the networking stack. To address these issues, in this paper, we introduce NCDN, a novel highly distributed system for large-scale delivery of content and services. NCDN is designed to provide resilience against node failure through location-independent storage and replication of content. This is achieved through a two-layer architecture: the first layer (exposure layer) exposes services implemented by NCDN (e.g., Web, SFTP) to clients; the second layer (hidden layer) provides reliable distributed storage of content and application state. Content in NCDN’s hidden layer is stored and exchanged as Named Data Network (NDN) content packets. We employ the reinforcement learning (RL) to dynamically learn the optimal numbers of duplicates for different type of contents, because the RL agent has the advantage of not requiring expert labels or knowledge and instead the ability to learn directly from its own interaction with the world. The combination of NDN and RL brings NCDN fine-grained, fully decentralized content replication mechanisms. We compare the performance and resilience of NCDN to those of an idealized CDN via extensive simulations. Our results show that NCDN is able to provide higher availability than CDNs (between 8% and 100% higher under the same conditions), without substantially increasing content retrieval delay.

中文翻译：

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NCDN：具有强化学习优化功能的节点故障弹性CDN解决方案

内容分发网络（CDN）使得可以通过Internet进行大规模，可靠和高效的内容分发。尽管CDN在提供很大一部分Internet流量方面非常成功，但是它们也有一些缺点。尽管它们具有分布式特性，但它们很大程度上依赖于集中式管理和复制。如果节点发生故障，这可能会影响可用性。此外，CDN是跨越网络堆栈多层的复杂基础架构。为了解决这些问题，在本文中，我们介绍了NCDN，这是一种用于大规模交付内容和服务的新型高度分布式系统。NCDN旨在通过与位置无关的存储和内容复制提供抵御节点故障的弹性。这是通过两层体系结构实现的：第一层（暴露层）向客户端公开由NCDN实现的服务（例如Web，SFTP）；第二层（隐藏层）提供内容和应用程序状态的可靠分布式存储。NCDN隐藏层中的内容将作为命名数据网络（NDN）内容数据包进行存储和交换。我们采用强化学习（RL）来动态学习针对不同类型内容的最佳副本数，因为RL代理的优点是不需要专家标签或知识，而是可以直接从自己与世界的互动中学习。NDN和RL的结合带来了NCDN细粒度，完全分散的内容复制机制。通过广泛的仿真，我们将NCDN的性能和弹性与理想CDN的性能和弹性进行了比较。