CAREER: A Programmable Measurement Architecture for Network Operations

职业生涯：用于网络运营的可编程测量架构

• 批准号: 1701754
• 负责人: Minlan Yu
• 金额: $ 47.94万
• 依托单位: Yale University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-07-01 至 2018-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1701754&HistoricalAwards=false
• 关键词: CAREER; Programmable; Measurement; Architecture; Network

Many companies (e.g., Google, Microsoft, Facebook, Amazon) put huge capital investments into building larger data center networks with higher link speeds. It becomes increasingly important to carefully manage such large data center networks to support multiple tenants, meet service level agreements of applications, and reduce operation cost. Most network management tasks, such as traffic accounting, traffic engineering, load balancing, and performance diagnosis, rely on accurate and timely measurement of time-varying traffic across the entire network. Unfortunately, there are three key problems in today's measurement support: (1) Network device vendors often treat measurement as a second-class citizen, devoting most of the resources to meet the networking control functions (forwarding, firewalls, load balancing, etc.), leaving limited resources for supporting measurement. (2) Operators have limited control over what (not) to measure and when to measure. As a result, the already limited measurement resources are sometimes wasted to measure flows that operators do not care, leaving even fewer resources for measuring important flows. (3) These solutions are device oriented instead of network wide. Operators have to dive into the limited measurement support at multiple devices, taking great efforts to understand these measurement results offline, and find it challenging to answer their network-wide queries.This project aims to design and build a programmable measurement architecture MAP, which transforms today's network measurement practice in enterprise and data center networks. Inspired by software-defined networking, MAP allows operators to flexibly program their network-wide measurement queries in a controller. To answer these queries, MAP automatically configures and coordinates new measurement primitives at different places across the network stack. MAP also allows operators to dynamically change their queries and automatically reconfigure the primitives accordingly to handle network dynamics.There are three key research directions: First, the project will bring novel measurement algorithms and designs throughout the network stack (VMs, hypervisors, switches, and packet sniffers). The researcher will redesign the measurement primitives at these devices to make them both generic in supporting diverse measurement requirements, and efficient in packet processing performance with limited resources and capabilities. Second, the researcher will design new declarative measurement abstractions for operators to clearly express what to measure at the network level and their accuracy/timeliness requirements. The researcher will also design and implement a runtime system that automatically matches the measurement abstractions with primitives at devices, dynamically allocates resources across tasks and handles network dynamics such as mobile hosts and routing changes. Finally, the researcher will study how to support several important and novel measurement tasks with MAP?s primitives, abstractions, and runtime, and evaluate them on MAP. The proposed research, if successful, will fundamentally change network measurement and management practice in enterprise and data centers, and lead to new designs of network devices. The research will facilitate inter-discipline research between theory, programming languages, and networking. The project also has a significant education component, including the design and innovations of graduate courses and course material on software-defined networking and computer networking, as well as research experiences for undergraduate students and members of under-represented groups.

许多公司（如b谷歌，微软，Facebook，亚马逊）投入大量资金建设更大的数据中心网络和更高的连接速度。仔细管理这样的大型数据中心网络以支持多个租户、满足应用程序的服务水平协议并降低运营成本变得越来越重要。大多数网络管理任务，如流量计费、流量工程、负载均衡和性能诊断等，都依赖于对整个网络中时变流量的准确、及时的测量。遗憾的是，在当今的测量支持中存在三个关键问题：(1)网络设备供应商往往将测量视为二等公民，将大部分资源用于满足网络控制功能（转发、防火墙、负载平衡等），而用于支持测量的资源有限。(2)操作者对测量什么（不测量）和何时测量的控制有限。因此，本已有限的度量资源有时会被浪费在度量操作员不关心的流上，从而使用于度量重要流的资源更少。(3)这些解决方案是面向设备的，而不是面向网络的。运营商必须在多个设备上深入研究有限的测量支持，付出巨大的努力来理解这些离线测量结果，并且发现回答他们的全网查询具有挑战性。该项目旨在设计和构建一个可编程的测量架构MAP，以改变当今企业和数据中心网络中的网络测量实践。受软件定义网络的启发，MAP允许操作员在控制器中灵活地编程其网络范围的测量查询。为了回答这些查询，MAP在网络堆栈的不同位置自动配置和协调新的测量原语。MAP还允许操作符动态更改查询，并自动重新配置相应的原语，以处理网络动态。主要研究方向有三个：首先，该项目将在整个网络堆栈（虚拟机、管理程序、交换机和数据包嗅探器）中引入新颖的测量算法和设计。研究人员将重新设计这些设备上的测量原语，使它们既能支持不同的测量需求，又能在有限的资源和能力下有效地处理数据包。其次，研究人员将为运营商设计新的声明性测量抽象，以清楚地表达在网络层面测量的内容及其准确性/及时性要求。研究人员还将设计并实现一个运行时系统，该系统将自动匹配测量抽象与设备上的原语，动态地跨任务分配资源，并处理网络动态，如移动主机和路由变化。最后，研究人员将研究如何支持几个重要的和新颖的测量任务与MAP？s原语、抽象和运行时，并在MAP上对它们求值。该研究如果成功，将从根本上改变企业和数据中心的网络测量和管理实践，并导致网络设备的新设计。这项研究将促进理论、编程语言和网络之间的跨学科研究。该项目还有一个重要的教育组成部分，包括设计和创新研究生课程和软件定义网络和计算机网络的课程材料，以及为本科生和代表性不足的群体成员提供研究经验。