Collaborative Research: NeTS-FIND: Model Based Diagnosis in the Knowledge Plane

合作研究：NeTS-FIND：知识平面中基于模型的诊断

• 批准号: 0626687
• 负责人: John Wroclawski
• 金额: $ 9.43万
• 依托单位: University of Southern California
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-09-15 至 2008-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0626687&HistoricalAwards=false
• 关键词: Collaborative; Research; NeTS; FIND; Model

The Knowledge Plane (KP) architecture enables next-generation computer networks to be self-describing, self-analyzing, and ultimately more self-managing. This one-year project is laying out an initial high-level design for the KP and applying it to focused test problems, with the aim of identifying key steps towards full development and deployment of a KP-enabled network. A fully KP-enabled network will be able to detect and diagnose its own failures and faults, and often advise on its own repair.The project would first define a three-part KP architecture consisting of (1) an agent system to decompose distributed and partitionable learning and analysis, (2) a knowledge representation framework and (3) knowledge routing and management. Key design criteria are scaling, distribution, and reconciliation of incomplete or incorrect knowledge.The KP postulates that sharing knowledge across multiple problem domains will strengthen solution performance in each domain. To motivate the architecture design and validate this postulate, the research focuses initially on a model-based hard fault diagnosis application, which is then extended to discovery of security failures. Following preliminary fault diagnosis work at MIT, the PIs focus on ISI's DETER network security testbed as a test environment for diagnosing hard fault and security-related configuration failures. DETER offers a controllable and constrained to simplify initial research, while being sufficiently large and complex to motivate many of the KP mechanisms required for a commercial Internet. The intended outputs of this project are (1) an architecture, including principles, goals, and an initial design, (2) a specific application of these to the separate yet overlapping problems of hard fault and security failures, and (3) identification of key questions to be addressed in the next steps of the research. Results will be disseminated through incorporation in the operational DETER testbed, publication of papers and related code, and PI participation in NETS-FIND community.

知识平面(KP)体系结构使下一代计算机网络能够自我描述、自我分析，并最终更加自我管理。这一为期一年的项目正在为金伯利进程制定初步的高级别设计，并将其应用于重点测试问题，目的是确定全面发展和部署金伯利进程网络的关键步骤。一个完全支持KP的网络将能够检测和诊断自己的故障和故障，并经常为自己的修复提供建议。该项目将首先定义一个由三部分组成的KP体系结构，包括(1)用于分解分布式和可划分的学习和分析的代理系统，(2)知识表示框架和(3)知识路由和管理。关键设计标准是不完整或不正确知识的扩展、分发和协调。KP假设跨多个问题领域共享知识将增强每个领域的解决方案性能。为了推动体系结构设计和验证这一假设，研究最初集中在基于模型的硬故障诊断应用程序上，然后扩展到发现安全故障。继麻省理工学院的初步故障诊断工作之后，PI将重点放在ISI的威慑网络安全试验台上，作为诊断硬故障和与安全相关的配置故障的测试环境。威慑提供了一个可控和受限的机制，以简化初始研究，同时足够大和复杂，可以激发商业互联网所需的许多知识获取机制。该项目的预期输出是(1)包括原则、目标和初始设计的体系结构，(2)对硬故障和安全故障这两个独立但重叠的问题的具体应用，以及(3)确定要在研究的下一步中解决的关键问题。结果将通过纳入业务威慑试验台、发表论文和相关代码以及PI参与NETS-FIND社区传播。