NeTS: Small: Do You See What I See: Finding and Measuring Faults in the Internet

NetS：小：你看到我看到的吗：在互联网中查找和测量故障

• 批准号: 1218977
• 负责人: Henning Schulzrinne
• 金额: $ 49.6万
• 依托单位: Columbia University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-03-01 至 2018-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1218977&HistoricalAwards=false
• 关键词: NeTS; Small; Do; See; What

Diagnosing network and network application faults remains one of the most challenging and frustrating aspects of using the Internet, particularly for non-technical users, but also for system administrators. A single VoIP application may depend on half a dozen protocols, and basic network access requires numerous network elements, from wireless access points to authorization servers, to function. On a larger scale, researchers have only anecdotal evidence of the most common network problems and their prevalence. This makes it difficult to use actual Internet experiences to improve existing protocols and implementations.The project proposes a new architecture and system, "Do You See What I See" (DYSWIS), to automate fault finding in residential, mobile, enterprise and data center networks in a systematic, extensible and scalable manner: Using protocol state analysis and packet timing analysis, DYSWIS automatically recognizes when network applications are likely malfunctioning. Leveraging social network graphs, the system finds suitable and mutually-trusting friends whose DYSWIS application can help with finding problems. As necessary, building on a programmable network platform, NetServ, in-network nodes are instantiated and discovered. DYSWIS then attempts to determine the cause of the fault, leveraging network views of other nodes to improve its diagnosis, by remotely invoking active probes at the network, transport and application layer.DYSWIS collects and aggregates statistics about faults and their resolution, allowing researchers and operators to see trends and determine common sources of problems. DYSWIS is designed to be extensible, so that new standardized and proprietary protocols and applications can be added selectively. The project explores how to scale DYSWIS to the Internet, evaluates its effectiveness, and extends it to use a programmable network platform.The project enhances undergraduate and graduate teaching, involves undergraduates in research projects, reaches out to industry and standardization organizations, provides tools and large data sets to researchers, and offers a data gathering platform and data for the benefit of Federal and State telecom regulators.

诊断网络和网络应用程序故障仍然是使用Internet的最具挑战性和最令人沮丧的方面之一，尤其是对于非技术用户，也适用于系统管理员。 单个VoIP应用程序可能取决于六个协议，基本网络访问需要许多网络元素，从无线访问点到授权服务器到功能。 在更大范围内，研究人员只有最常见的网络问题及其患病率的轶事证据。 这使得很难使用实际的Internet经验来改善现有协议和实施。该项目提出了一种新的体系结构和系统，“您看到我看到的东西了”（Dyswis），以自动化住宅，移动，企业和数据中心网络中的故障查找，以系统的，可扩展的方式和可扩展的方式使用协议状态分析和数据集时间分析时，MALF在MALF中识别，在DESSWIS上识别，DESSWIS在DESSWIS中识别，dysemations dynewions networming在DYSENTICS中均可在dysemations中识别。 在利用社交网络图的情况下，该系统找到了合适而相互信任的朋友，他们的dyswis应用程序可以帮助发现问题。 必要时，在可编程网络平台上构建NetServ，网络内节点是实例化和发现的。随后，多斯维斯（Dyswis）试图确定故障的原因，利用其他节点的网络视图来改善其诊断，通过在网络，运输和应用程序层中调用主动探测器。Dyswis收集和汇总了有关故障及其分辨率的统计信息，使研究人员和操作员可以看到趋势并确定问题的趋势，并确定问题的共同来源。 Dyswis设计为可扩展的，因此可以选择性地添加新的标准化和专有协议和应用程序。 该项目探讨了如何扩展发展到互联网，评估其有效性，并扩展了其使用可编程网络平台。该项目增强了本科和研究生教学，涉及研究项目的本科生，与行业和标准化组织联系，向研究人员提供工具和大型数据集，并为研究人员提供数据集会平台和数据集团的数据集和数据范围内的数据，并提供了数据集和数据范围内的数据，并为您提供了数据福利者和数据。