A Software Toolkit for Visualizing Enterprise Routing Design



Routing design is widely considered as one of the most challenging parts of enterprise network design. The challenges come from the typical large scale of such networks, the diverse objectives to meet through design, and a wide variety of protocols and mechanisms to choose from. As a result network operators often find it difficult to understand and troubleshoot the routing design of their networks. Furthermore, today common practice of focusing on one router or one protocol at a time makes it a onerous task to reason about the network-wide routing behavior.

We believe that to mitigate the problem, there is a need forsoftware tools to produce effective visualization of enterprise routing designs. In this paper we report on our experience building such a toolkit. We begin by abstracting various routing mechanisms into a small number of design primitives. The abstraction allows for a more concise representation of routing design without losing important design information, which is critical for making the tool scalable. Guided by the abstraction, we then develop a set of algorithms and heuristics, which take router configuration files as input and output a graphical representation of the routing design. The layout and components of the graph are highly customized to optimize its readability and power to infer the network-wide design pattern.

We also present a case study using the toolkit to analyze the routing design of two large campus networks, and report on our findings. Our experience confirms the effectiveness of our toolkit in revealing key design characteristics of the networks, and in illustrating the network-wide routing behavior.

Please look at here for instructions on how to install and use the toolkit.

If you want to cite this tool, please cite the following paper instead:
Xin Sun, Jinliang Wei, Sanjay Rao and Geoffrey G. Xie, "A Software Toolkit for Visualizing Enterprise Routing Design", Symposium on Configuration Analytics and Automation (SafeConfig), 2011

This work was supported by NSF grants Career-0953622, and Cisco.

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