Formal Methods for Network Performance Analysis


Mina Tahmasbi Arashloo, University of Waterloo; Ryan Beckett, Microsoft Research; Rachit Agarwal, Cornell University


Accurate and thorough analysis of network performance is challenging. Network simulations and emulations can only cover a subset of the continuously evolving set of workloads networks can experience, leaving room for unexplored corner cases and bugs that can cause sub-optimal performance on live traffic. Techniques from queuing theory and network calculus can provide rigorous bounds on performance metrics, but typically require the behavior of network components and the arrival pattern of traffic to be approximated with concise and well-behaved mathematical functions. As such, they are not immediately applicable to emerging workloads and the new algorithms and protocols developed for handling them.

We explore a different approach: using formal methods to analyze network performance. We show that it is possible to accurately model network components and their queues in logic, and use techniques from program synthesis to automatically generate concise interpretable workloads as answers to queries about performance metrics. Our approach offers a new point in the space of existing tools for analyzing network performance: it is more exhaustive than simulation and emulation, and can be readily applied to algorithms and protocols that are expressible in first-order logic. We demonstrate the effectiveness of our approach by analyzing packet scheduling algorithms and a small leaf-spine network and generating concise workloads that can cause throughput, fairness, starvation, and latency problems.

NSDI '23 Open Access Sponsored by
King Abdullah University of Science and Technology (KAUST)

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This content is available to:

@inproceedings {285179,
author = {Mina Tahmasbi Arashloo and Ryan Beckett and Rachit Agarwal},
title = {Formal Methods for Network Performance Analysis},
booktitle = {20th USENIX Symposium on Networked Systems Design and Implementation (NSDI 23)},
year = {2023},
isbn = {978-1-939133-33-5},
address = {Boston, MA},
pages = {645--661},
url = {},
publisher = {USENIX Association},
month = apr,
Tahmasbi Paper (Prepublication) PDF

Presentation Video