CNS Core: Small: Transparent Network Acceleration

CNS 核心：小型：透明网络加速

• 批准号: 2241818
• 负责人: Eric Keller
• 金额: $ 59.99万
• 依托单位: University of Colorado at Boulder
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-05-15 至 2026-04-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2241818&HistoricalAwards=false
• 关键词: CNS; Core; Small; Transparent; Network

With the increase in connected devices comes an increase in network traffic. Applications that we use every day, such as video conferencing, each need to have traffic processed to secure and optimize the application. Current network infrastructure is showing signs that in the near future it won't be able to keep up with the growing demand or increased needs, such as having higher definition video calls with more participants and imperceptible delays in the communication. While some solutions have been proposed to help solve this problem, they do so at the cost of compatibility, which would require rewriting a large body of software that has been developed and tested over the course of over a decade. This proposal introduces a new way of thinking about the way network traffic is handled that will enable both forward and backwards compatibility with modern software while meeting the needs of applications.In particular, this proposal introduces Transparent Network Acceleration (TNA), which is a novel architecture that decomposes Linux network functionality into fast-path and slow-path functions with explicitly optimized execution environments for each. TNA dynamically and automatically builds a minimal fast path that is instantiated and adjusted at run-time, leading to a transparently accelerated networking stack that fully retains the Linux networking interfaces. Two core mechanisms are introduced. First, to create a highly efficient fast path, TNA automatically and dynamically instantiates only the part of the network stack that is used. New techniques are introduced to introspect the Linux kernel, build a dependency graph of functions, and assemble and deploy an optimal fast path. Second, it targets two fast-path execution environments from a single source code description of modules: (i) the eXpress Data Path (XDP), for in-kernel processing, and (ii) a field programmable gate array (FPGA) based SmartNIC, for hardware accelerated processing. As part of these targets, the design of modules, the compilation to hardware or software, and synchronizing the state represent a novel and complete design flow. In order to demonstrate the effectiveness of these two core mechanisms, we complete the project with a case study of automatically accelerating a selective forwarding unit (SFU) video conferencing network function deployed with considerations such as firewalling and container networking.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.

随着连接设备的增加，网络流量也随之增加。 我们每天使用的应用程序（如视频会议）都需要处理流量以保护和优化应用程序。 目前的网络基础设施显示出在不久的将来它将无法跟上不断增长的需求或增加的需求的迹象，例如具有更多参与者的更高清晰度视频通话和通信中的不可察觉的延迟。 虽然已经提出了一些解决方案来帮助解决这个问题，但它们是以兼容性为代价的，这将需要重写已经开发和测试了十多年的大量软件。 该提案引入了一种新的思路来处理网络流量，在满足应用程序需求的同时，实现了与现代软件的前向和后向兼容。特别是，该提案引入了透明网络加速（TNA），这是一种新颖的架构，将Linux网络功能分解为快速路径和慢速路径功能，并为每个功能明确优化了执行环境。TNA动态自动地构建一个最小的快速路径，在运行时实例化和调整，从而产生一个完全保留Linux网络接口的透明加速网络堆栈。介绍了两种核心机制。 首先，为了创建一个高效的快速路径，TNA只自动地、动态地实例化网络栈中被使用的部分。 引入新的技术来反思Linux内核，建立一个依赖图的功能，并组装和部署一个最佳的快速路径。第二，它的目标是两个快速路径执行环境从一个单一的源代码描述的模块：（i）的eXpress数据路径（XDP），在内核处理，和（ii）一个现场可编程门阵列（FPGA）的SmartNIC，硬件加速处理。作为这些目标的一部分，模块的设计，硬件或软件的编译，以及状态同步代表了一个新颖而完整的设计流程。为了证明这两个核心机制的有效性，我们完成了一个案例研究的自动加速选择性转发单元（SFU）视频会议网络功能部署的考虑，如防火墙和容器网络。这个奖项反映了NSF的法定使命，并已被认为是值得支持的评估使用基金会的智力价值和更广泛的影响审查标准。