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。理想情况下，网络运营商希望的是一台能够以全速连接每个终端的全带宽交换机。这样一个理想化的网络将使他们能够将作业和数据放置在方便的地方，而不必担心带宽瓶颈、热点和其他网络引起的限制。不幸的是，保留这种单一网络具有全带宽的“大开关”错觉成本越来越高，而且可能很快就不可行了。本项目将探索一种基于可证明最优的拓扑结构--扩展图--来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、更有能力和更具可扩展性的网络交换矩阵。该项目将开发一系列基于扩展图的云数据中心网络拓扑，消除基于分层CLOS的拓扑中固有的容量瓶颈，同时最大限度地减少间接路由所产生的带宽税。单个大型扩展图网络拓扑可以由多个互不相交的扩展图构建；本项目将展示明智的租户放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范围内发展一组组成扩展器图，从而使云数据中心运营商能够更好地满足其当前租户的需求。实际上，如果时间标度足够小(例如，100毫秒)，则租户可以选择缓冲流量，直到有特别有利的(一组)路径(S)可用，从而进一步降低整体带宽低效或“负担”。如果网络拓扑快速发展，则可以在每个数据包的基础上选择是否(1)立即通过当前实例化的任何静态扩展器发送数据包，对这一小部分流量产生适度的税收；或(2)缓冲数据包并等待，直到建立到最终目的地的直接链路，从而消除对绝大多数字节的带宽税。该项目将通过结构化课程、密集的指导、通过参与NSF资助的加州大学圣地亚哥分校早期研究学者计划(ERSP)和实践研究活动。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.