NeTS: Small: Understanding Network Failure

该项目旨在量化各种网络类别中故障的频率、持续时间、原因和影响。与以前依赖大量特殊用途仪器和监控基础设施的工作不同，PI仅使用常见的数据源进行分析，例如由网络运营人员维护的设备日志和配置记录。通过这种方式，他们不仅希望提供有关被评估的特定网络的具体数据，还希望定义一种可重复使用的方法，供其他研究人员甚至商业运营商使用，以评估其他网络的可靠性。通过与学术骨干网络(CENIC)、企业网络服务公司(Hewlett-Packard)和大型网络服务提供商(Microsoft)的伙伴关系，PI获得了对大量实际网络的设备日志、操作维护记录和配置信息的访问。具体地说，该项目致力于提供一种故障分析方法，其基础是随时可用的数据，如设备日志、配置信息和操作员记录，如电子邮件列表和故障单；关于广域、企业和数据中心网络的不同故障特征的比较研究；以及可用于评估不同应用程序和协议对各种网络设计的适用性和有效性的网络故障生成模型。广泛影响：除了这些具体的技术贡献外，该项目的更广泛影响包括可能促使网络运营商重新考虑当前网络的设计方式，使其不太可能发生故障，或者以更直接和更容易管理的方式发生故障。此外，这项研究工作正在向下一代计算机科学家传授必要的技能，以评估、分析和模拟作战网络的性能特征。该项目支持两名研究生，他们协助PI进行所述工作，并通过工业实习获得对商业网络环境的大量接触。

This project seeks to quantify the frequency, duration, causes, and impact of faults across a variety of network classes. Unlike previous efforts that have relied on substantial special-purpose instrumentation and monitoring infrastructure, the PIs are conducting their analysis using only commonly available data sources, such as device logs and configuration records maintained by network operations staff. In this way, they hope not only to provide concrete data regarding the particular networks being evaluated, but to define a repeatable methodology that can be employed by other researchers and even commercial operators to assess the reliability of other networks. Through partnerships with an academic backbone network (CENIC), an enterprise network services company (Hewlett-Packard), and large-scale Web services provider (Microsoft), the PIs have obtained access to device logs, operational maintenance records, and configuration information for a significant number of real networks.Concretely, this project is working to deliver a fault analysis methodology based on readily available data like device logs, configuration information, and operator records such as email lists and trouble tickets; comparative studies regarding the differing failure characteristics of wide-area, enterprise, and data center networks; and a generative model of network faults that can be used to evaluate the suitability and efficacy of different applications and protocols to various network designs.Broader Impact: In addition to these concrete technical contributions, the broader impacts of this project include the potential to cause network operators to reconsider how current networks are designed to make them less likely to fail, or to fail in more straightforward and easily manageable ways. Moreover, the research effort is imparting onto the next generation of computer scientists the skills necessary to assess, analyze, and model the performance characteristics of operational networks. This project supports two graduate students who assist the PIs in conducting the described work, and receive significant exposure to commercial network environments through industrial internships.