IRNC: AMI: Collaborative Research: Software-Defined and Privacy-Preserving Network Measurement Instrument and Services for Understanding Data-Driven Science Discovery

IRNC：AMI：协作研究：软件定义和隐私保护的网络测量仪器和服务，用于理解数据驱动的科学发现

• 批准号: 1450996
• 负责人: Yan Luo
• 金额: $ 125.49万
• 依托单位: University of Massachusetts Lowell
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-04-01 至 2020-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1450996&HistoricalAwards=false
• 关键词: IRNC; AMI; Collaborative; Research; Software

Data intensive science discovery at a global scale has imposed new requirements on the speed and management of international research and education networks. At the connection points of these international networks, it is critical to measure the network data flows to understand network traffic patterns, identify network anomalies and provide insights to network control and planning. However, the ever-increasing network speed, the massive amount of network flows and the changing measurement objectives have made the flow-level measurement on very high-speed networks extremely challenging. The Advanced Measurement Instrument and Services (AMIS) project leverages many-core, programmable network processors to prototype and deploy an advanced measurement instrument to enable services for accurate network monitoring and in-depth traffic analysis. The instrument supports flow-granularity measurement at line rate up to 100Gbps and software application programming interfaces to examine selected flows, with no impact to the performance of user traffic. With scalable hardware and an open source software stack, the measurement services equip network operators with effective tools to quantify flow-level network performance and study network flows through privacy-preserving computational analytics. This project is built on a consortium of academia, industrial partners, network operators and international alliances, who bring unique expertise and resources to achieve the objectives of high performance, programmable flow-granularity network measurement. The outcomes from this project will significantly benefit data driven science discovery, such as astronomy and space weather studies, and will promote broadened participation of underrepresented groups (such as Hispanic and female students) through the involvement of multiple universities, including an EPSCoR university and a Hispanic Serving Institution.

数据密集的科学发现在全球范围内对国际研究和教育网络的速度和管理提出了新的要求。在这些国际网络的连接点上，测量网络数据流以了解网络流量模式，识别网络异常并为网络控制和计划提供见解至关重要。但是，不断增加的网络速度，大量的网络流量和不断变化的测量目标使非常高的高速网络上的流级测量极具挑战性。高级测量工具和服务（AMIS）项目利用多核，可编程的网络处理器原型和部署高级测量工具，以启用服务以进行准确的网络监控和深入的流量分析。该仪器以高达100Gbps的线路速率和软件应用程序编程界面的线路速率测量，以检查选定的流量，对用户流量的性能没有影响。借助可扩展的硬件和开源软件堆栈，该测量服务为网络运营商提供了有效的工具，可以通过隐私保护计算分析来量化流量级网络性能和研究网络流。该项目建立在学术界，工业合作伙伴，网络运营商和国际联盟的联盟上，他们带来了独特的专业知识和资源，以实现高性能，可编程的流动粒度网络测量的目标。 该项目的结果将显着受益于数据驱动的科学发现，例如天文学和太空天气研究，并通过包括Epscor大学和西班牙裔美国人服务机构在内的多个大学的参与来促进代表性不足的群体（例如西班牙裔和女学生）的扩大参与。