CNS Core: Small: Designing Efficient Cloud Datacenter Network Fabrics

云数据中心网络的任务是在数量不断增加的终端主机之间提供连接，这些主机的链路速率每隔几年就会提高几个数量级。网络运营商最理想的是一个可以以全速率连接每个端点的全带宽交换机。这种理想化的网络将使他们能够在方便的地方放置作业和数据，而不必担心带宽瓶颈、热点和其他网络限制。不幸的是，保留这种具有全带宽的单一网络的“大交换机”错觉的成本越来越高，而且可能很快就不可行了。本项目将探索一种基于可证明的最优拓扑结构（扩展图）构建数据中心网络结构的替代方法。如果成功，该项目将产生比现有最先进的方法更灵活、更有能力和可扩展的网络结构。该项目将开发一系列基于扩展图的云数据中心网络拓扑，消除分层基于clos的拓扑中固有的容量瓶颈，同时最大限度地减少由于间接路由而产生的带宽税。一个单一的、大的展开图网络拓扑可以由多个不相交的展开图构成；该项目将展示明智的租户安置如何在最大限度地减少带宽税的同时提供隔离和动态容量。此外，通过采用可重新配置的网络组件（即电路交换机），甚至可以在不同的时间尺度上发展组成扩展图集，从而允许云数据中心运营商更好地满足其当前租户的需求。实际上，如果时间尺度足够小（例如，100毫秒），租户可能会选择缓冲流量，直到有特别有利的（一组）路径可用，从而进一步降低整体带宽效率低下或“税收”。如果网络拓扑以快速的速度发展，则可以根据每个数据包选择是否(1)立即通过当前实例化的任何静态扩展器发送数据包，从而对这一小部分流量产生适度的税，或者(2)缓冲数据包并等待建立到最终目的地的直接链接，从而消除绝大多数字节的带宽税。该项目将通过参与美国国家科学基金会资助的加州大学圣地亚哥分校早期研究学者计划（ERSP），通过结构化的课程，密集的指导和实践研究活动，吸引研究生和本科生。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Cloud datacenter networks are tasked with providing connectivity between an ever-increasing number of end hosts whose link rates improve by orders of magnitude every few years. What network operators would ideally like is a single, full-bandwidth switch that could connect every endpoint at full rate. Such an idealized network would enable them to place jobs and data where it is convenient, without worrying about bandwidth bottlenecks, hotspots, and other network-induced limitations. Unfortunately, preserving this ``big-switch'' illusion of a single network with full bandwidth is increasingly cost prohibitive and likely soon infeasible.This project will explore an alternative method of constructing datacenter network fabrics based upon a provably optimal topological construct, an expander graph. If successful, the project will result in network fabrics that are more flexible, capable, and scalable than existing state-of-the-art approaches. This project will develop a family of cloud datacenter network topologies based on expander graphs that eliminate the capacity bottlenecks inherent in hierarchical Clos-based topologies while minimizing the bandwidth tax incurred due to indirect routing. A single, large expander-graph network topology can be constructed out of multiple, disjoint expander graphs; this project will show how judicious tenant placement can then provide both isolation and dynamic capacity while minimizing the bandwidth tax. Moreover, by employing reconfigurable network components (i.e., circuit switches), it is even possible to evolve the set of constituent expander graphs over various time scales, allowing cloud datacenter operators to better suit the needs of their current tenants. Indeed, if the timescales are sufficiently small (e.g., 100s of milliseconds) tenants may then choose to buffer traffic until a particularly favorable (set of) path(s) is available, further decreasing the overall bandwidth inefficiency or "tax". If the network topology evolves at a rapid rate, it is possible to choose, on a per-packet basis, whether to either (1) immediately send a packet over whatever static expander is currently instantiated, incurring a modest tax on this small fraction of traffic, or (2) buffer the packet and wait until a direct link is established to the ultimate destination, eliminating the bandwidth tax on the vast majority of bytes.This project will engage graduate and undergraduate students through structured courses, intense mentorship, and hands-on research activities through participation in the NSF-funded UC San Diego Early Research Scholars Program (ERSP).This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.