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

NeTS-FIND：知识平面中基于模型的诊断

• 批准号: 0626904
• 负责人: Karen Sollins
• 金额: --
• 依托单位: Massachusetts Institute of Technology
• 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=0626904&HistoricalAwards=false
• 关键词: NeTS; FIND; Model; Based; Diagnosis

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。 这个为期一年的项目是为KP制定最初的高级设计，并将其应用于集中的测试问题，目的是确定朝着全面开发和部署KP网络的关键步骤。 完全支持KP的网络将能够检测和诊断其自身的故障和故障，并经常在其自身维修时提供建议。该项目将首先定义一个三部分的KP架构，该架构由（1）代理系统组成，用于分解分布式和可分配的学习和分析，（2）知识表示框架以及（3）知识路由和管理。 关键设计标准是对不完整或不正确知识的扩展，分发和对帐。KP假定在多个问题域之间共享知识将增强每个域中的解决方案性能。为了激励体系结构设计并验证这一假设，研究最初着重于基于模型的硬故障诊断应用，然后将其扩展到发现安全故障的发现。 在麻省理工学院进行初步故障诊断工作后，PIS专注于ISI的DITER网络安全测试，作为用于诊断硬故障和安全性配置故障的测试环境。 DeTer提供了可控且受到限制的，以简化初始研究，同时足够大而复杂，可以激发商业互联网所需的许多KP机制。该项目的预期输出是（1）架构，包括原理，目标和初始设计，（2）这些特定的应用于硬故障和安全失败的单独但重叠的问题，以及（3）在研究的下一步中识别要解决的关键问题。 结果将通过纳入操作削弱测试床，论文和相关代码的发表以及PI参与Nets-Find社区的传播。