CRII: NeTS: Characterizing, Quantifying and Modeling Network Complexity

复杂程度更高的网络通常需要更多的人工干预来管理，更难推理，更容易出现人为错误。尽管复杂性至关重要，但它仍然是网络中最不被理解的方面之一，而且还没有得到很好的特征描述或建模。人们普遍认为，对于同一目标网络，通常存在多种设计来满足相同的一组运营目标(例如，安全和恢复能力要求)，并且某些设计可能比其他设计更易于管理；然而，关于复杂性的决策通常是主观或定性的。本项目旨在对网络复杂性有一个全新的理解、衡量标准和模型。该项目通过一种新的白盒方法来研究网络的设计特征如何影响其管理的复杂性，该方法涉及从设备配置对网络设计进行逆向工程，识别不同于传统智慧的设计模式，以及与网络运营商进行迭代讨论以获取感知的复杂性。将开发一套自下而上的度量标准，以准确量化给定设计的复杂性。通过这些指标，可以对备选设计方案进行比较，并对设计变更可能如何影响管理复杂性进行“假设分析”。我们将开发一个自上而下的框架来模拟网络设计、运营目标和由此产生的管理复杂性之间的相互影响。该框架形式化地抽象了给定设计任务的目标，从而允许对设计基元的组合是否以及如何满足这些目标进行推理，将设计任务分解为其组成基元，并应用度量来量化单个基元的复杂性。如果该项目成功，该项目将在理解、量化和建模网络复杂性方面取得进展。通过在设计空间中引导搜索，建模框架实现了自顶向下的复杂性感知网络设计。从本项目中获得的见解可能会为未来网络架构、管理应用程序和配置语言的设计提供参考。该项目的PI将积极与研究社区、运营商社区和互联网工程任务组互动，以传播研究成果。该项目的成果将被纳入研究生级别的网络管理课程。由于佛罗里达国际大学是一所指定的拉美裔服务机构，该项目将作为一种工具，促进代表不足的少数族裔参与计算机科学研究。

Networks with higher degrees of complexity generally require more manual intervention to manage, are more difficult to reason about, and are more prone to human errors. Despite its critical importance, complexity remains one of the least understood aspects of a network, and has not been well characterized or modeled. There is a general perception that for the same target network multiple designs often exist to meet the same set of operational objectives (e.g., security and resiliency requirements), and that some designs could be significantly easier to manage than others; however the decisions on complexity are typically made subjectively or via qualitative terms. This project aims at developing a fundamentally new understanding of, and metrics and models for, network complexity. The project studies how a network's design characteristics impact the complexity in its management, through a novel white-box approach that involves reverse-engineering the network design from device configurations, identifying design patterns that differ from conventional wisdom, and iterative discussions with network operators to capture perceived complexity. A suite of bottom-up metrics will be developed to accurately quantify the complexity of a given design. These metrics enable comparisons of alternative design proposals and "what-if" analyses of how design changes might impact the management complexity. A top-down framework will be developed to model the interplay among network design, operational objectives, and the resulting management complexity. The framework formally abstracts the objectives of a given design task thus allowing reasoning about whether and how a combination of design primitives will meet those objectives, decomposes the design task into its constituent primitives, and applies the metrics to quantify the complexity of individual primitives.If successful this project will advance the state-of-the-art in understanding, quantifying, and modeling network complexity. The modeling framework enables complexity-aware top-down network design by guiding the search through the design space. The insights obtained from this project may inform the design of future network architectures, management applications, and configuration languages. The project's PI will actively interact with the research community, operator community, and Internet Engineering Task Force to disseminate the research findings. Results from the project will be incorporated into graduate-level network management classes. As Florida International University is a designated Hispanic-serving institution, this project will serve as a vehicle to advance the involvement of underrepresented minorities in computer science research.