11–13 Dec 2025
Asia/Tokyo timezone

Locality-Aware, Self-Adjusting Data Structures: A Case Study in Linux Firewalls

Not scheduled
20m
Networking Track Networking Track

Speaker

Jonas Köppeler (TU Berlin)

Description

The Move-Recursively-Forward algorithm [1] has shown impressive results in speeding up packet classification for firewall rule sets. Its performance gains are generated by reordering firewall rules based on access patterns: frequently matched rules are promoted forward in the list, leveraging locality in network traffic to speed up classification without changing the intended firewall behavior. We applied this idea to the Linux nftables firewall and explored how well it scales across multiple CPU cores. Our initial prototype shows that this approach is feasible: under ideal conditions, testbed evaluations demonstrate improvements in throughput up to 5x greater than the default nftables implementation. Further, even under sub-optimal conditions, our prototype achieves similar performance to the static-list lookup.

In this talk, we will share our results, discuss key implementation details, and invite feedback from the community on potential pathways toward upstream integration.

[1]: V. Addanki, M. Pacut, A. Pourdamghani, G. Rétvári, S. Schmid and J. Vanerio, "Self-Adjusting Partially Ordered Lists," IEEE INFOCOM 2023 - IEEE Conference on Computer Communications, New York City, NY, USA, 2023, pp. 1-10, doi: 10.1109/INFOCOM53939.2023.10228937.

Primary author

Jonas Köppeler (TU Berlin)

Co-authors

Dr Gábor Rétvári (Budapest University of Technology and Economics) Dr Maciej Pacut (TU Berlin) Prof. Stefan Schmid (TU Berlin) Mr Tamás Lévai (Budapest University of Technology and Economics) Dr Vamsi Addanki (Purdue University)

Presentation materials

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