AitF: FULL: Collaborative Research: Compact Data Structures for Traffic Measurement in Software-Defined Networks

AitF：完整：协作研究：软件定义网络中流量测量的紧凑数据结构

• 批准号: 1535948
• 负责人: Jennifer Rexford
• 金额: $ 36万
• 依托单位: Princeton University
• 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: 2015-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1535948&HistoricalAwards=false
• 关键词: AitF; FULL; Collaborative; Research; Compact

Software-Defined Networking (SDN) is changing the way networks are designed and managed, by separating the "control plane" (which decides how to handle the traffic) from the "data plane" (which actually forwards each packet). Many large companies---like Google, Microsoft, and Facebook---have already deployed SDN technology, and many equipment vendors support open interfaces for programming their switches. While most work on SDN focuses on how to control the network, measuring the traffic in the network is equally important. Traffic measurement is useful to identify congested links, denial-of-service attacks, performance problems, and configuration mistakes, and also drives decisions of how the network should forward traffic in the future. However, the support for traffic measurement in today's commodity switches is quite primitive. In this proposal, the PIs bring algorithmic research on so-called "compact data structures" to bear on the problem of programmable traffic measurement in SDNs. Compact data structures can give approximate answers to measurement questions with limited overhead in terms of switch memory and processing resources. The project is interdisciplinary, bringing together researchers in computer networking and theoretical computer science to match practical problems with novel solutions. The proposed research starts with designing new query abstractions for collecting traffic statistics on existing SDN switches, and then progresses to identifying new compact data structures so that future switches can support much richer traffic measurement at reasonable overhead. The researchers have close ties with network administrators and switch vendors, allowing them to ground the project in a strong understanding of both operational requirements and hardware constraints, and also influence future SDN technology.This project aims to identify a switch data-plane architecture for collecting diverse traffic statistics, as well as a small set of programmable sketches and samples for variety of analyses to trade-off accuracy and resources. The architecture will include a measurement control API between the controller and the switch, and this needs a communication-efficient interface, along with a high-level language for specifying traffic queries, and with that, a run-time system on the controller that compiles these queries into commands to the switches with suitable CDSs. These challenges will be addressed using OpenFlow API that is widely popular for SDNs and in new redesigns. This is a conversation between the networking and algorithmic communities, mutually informing each other on what is possible, what is required, and ultimately what is effective and useful.

软件定义网络 (SDN) 通过将“控制平面”（决定如何处理流量）与“数据平面”（实际转发每个数据包）分离，正在改变网络的设计和管理方式。 许多大公司（例如谷歌、微软和 Facebook）已经部署了 SDN 技术，并且许多设备供应商支持开放接口来对其交换机进行编程。 虽然 SDN 的大多数工作都集中在如何控制网络，但测量网络中的流量也同样重要。 流量测量有助于识别拥塞的链路、拒绝服务攻击、性能问题和配置错误，还可以推动网络未来如何转发流量的决策。 然而，当今的商用交换机对流量测量的支持相当原始。 在该提案中，PI 引入了所谓“紧凑数据结构”的算法研究，以解决 SDN 中的可编程流量测量问题。 紧凑的数据结构可以在交换机内存和处理资源方面以有限的开销给出测量问题的近似答案。 该项目是跨学科的，汇集了计算机网络和理论计算机科学领域的研究人员，将实际问题与新颖的解决方案相匹配。 所提出的研究首先设计新的查询抽象来收集现有 SDN 交换机上的流量统计数据，然后继续识别新的紧凑数据结构，以便未来的交换机能够以合理的开销支持更丰富的流量测量。 研究人员与网络管理员和交换机供应商有着密切的联系，使他们能够深入了解操作要求和硬件限制，并影响未来的 SDN 技术。该项目旨在确定一种交换机数据平面架构，用于收集各种流量统计数据，以及一小组可编程草图和示例，用于各种分析，以权衡准确性和资源。 该架构将包括控制器和交换机之间的测量控制 API，这需要一个高效通信的接口，以及用于指定流量查询的高级语言，并且需要控制器上的运行时系统来编译这些查询转化为具有合适 CDS 的交换机的命令。 这些挑战将使用在 SDN 和新的重新设计中广泛流行的 OpenFlow API 来解决。 这是网络和算法社区之间的对话，相互告知什么是可能的、需要什么，以及最终什么是有效和有用的。