NeTS: Small: Designing Networks for High Throughput

并行性和大数据分析这两个不可阻挡的趋势的结合意味着计算系统迫切需要高效的高容量网络，能够在服务器之间非常快速地交付数据。由谷歌、亚马逊、Facebook等大型互联网服务运营的现代仓库规模的数据中心需要连接数万台服务器的网络。高容量有助于支持数据密集型应用程序，如Map-Reduce和科学模拟。在云计算中，高容量网络使运营商可以自由地将虚拟机放置在任何物理服务器上，而无需担心主机之间的容量限制。这种自由转化为更高的服务器利用率，更低的管理开销，从而降低运营成本。随着云应用对服务器之间通信的要求越来越高，最近提出了许多数据中心网络架构。 在这些网络中，网络的路由和拓扑（即路由器和服务器之间的链路模式）对于协同工作以获得高容量至关重要。然而，我们缺乏一个基本的理解，网络拓扑结构实现高容量和由此产生的系统设计的权衡是什么，以及如何建立实时路由算法，实现在任意拓扑结构接近最佳的容量。 主要研究人员（PI）将开发高容量的网络架构，包括高效灵活的路由和拓扑结构。 他们将开发一套软件，以有效地计算各种网络流量模式、拓扑和路由协议下的网络架构容量，并建立一个硬件测试平台来测试设计。 然后，他们将着手实现一个雄心勃勃的目标--开发一个系统，在真实的时间内实现接近最佳的多商品流动（例如，几十或几百毫秒）。 最后，PI将应用这些路由的进步，使新的更有效和灵活的数据中心网络拓扑。该项目的更广泛的影响在于预期的研究影响和教育影响。 与当前的数据中心相比，该项目中产生的数据中心网络设计预计将提供显著的效率和运营灵活性，在与当前大规模数据中心网络相同的设备下，可能实现25-40%的高容量。 PI还将开发一个课程模块和电子书，调查如何实现网络高容量的基本主题，包括过去的工作和本项目的工作。 最后，该项目将包括一个免费发布的软件套件，以促进开放和可复制的研究。

The combination of two inexorable trends - increasing parallelism and increasing big data analytics - means computing systems urgently need efficient high-capacity networks, capable of very rapidly delivery of data among servers. Modern warehouse-scale data centers, operated by large Internet services like Google, Amazon, Facebook, and many others, require networks connecting tens of thousands of servers. High capacity is useful to support data intensive applications such as Map-Reduce and scientific simulations. In cloud computing, a high-capacity network gives operators the freedom to place virtual machines on any physical server, without needing to worry about capacity constraints between hosts. This freedom translates into higher server utilization, lower management overhead, and thus lower operating costs.As cloud applications have demanded greater communication among servers, numerous data center network architectures have recently been proposed. In these networks, both the routing and the topology of the network - that is, the pattern of links among routers and servers - are critical in working together to obtain high capacity. However, we lack a fundamental understanding about which network topologies achieve high capacity and what the resulting systems design tradeoffs are, as well as how to build real-time routing algorithms that achieve near-optimal capacity in arbitrary topologies.The project spans theory and systems design. The principal investigators (PIs) will develop high-capacity network architectures, including routing and topologies that are efficient and flexible. They will develop a suite of software to efficiently compute capacity of network architectures in a variety of network traffic patterns, topologies, and routing protocols, as well as build a hardware testbed to test the designs. They will then tackle an ambitious goal -- developing a system which achieves near-optimal multicommodity flow in real time (e.g., tens or hundreds of milliseconds) in arbitrary network topologies. Finally, the PIs will apply these routing advances to enable new more efficient and flexibile data center network topologies.The broader impact of this project lies in expected research impact and educational impact. The data center network designs produced in this project are expected to provide significant efficiency and operational flexibility compared to today's data centers, potentially achieving 25-40% higher capacity with the same equipment as current large-scape data center networks. The PIs will also develop a course module and e-book surveying the fundamental topic of how to achieve high capacity in networks, including past work and that of this project. Finally, the project will include a free release of a software suite to facilitate open and reproducible research.