AI summaryⓘ
The authors developed a new user-space version of a network traffic control tool called DualPI2, which helps manage internet delays and congestion, for the Mahimahi network emulator. They compared this version to the existing Linux kernel implementation and found that identical settings don't always produce the same results across different environments. Their study shows that how this tool behaves depends on the network conditions and platform used, especially under varying traffic loads. The authors also found settings that make the two versions work more similarly in low-delay situations, but some differences remain under heavier traffic. This work offers a useful tool and important insights for researchers studying network delay control outside the kernel.
L4SDualPI2Active Queue ManagementLatency ControlCongestion ControlMahimahiNetwork EmulationBandwidth-Delay ProductLinux KernelUser-space Implementation
Authors
Nawel Alioua, Linghe Zhang, Aneesh Garg, Francis Y. Yan, Elizabeth Belding
Abstract
Low Latency, Low Loss, and Scalable Throughput (L4S) is an emerging paradigm for latency control based on DualPI2 active queue management and scalable congestion control. While a Linux kernel implementation of DualPI2 is available, controlled and reproducible experimentation on L4S mechanisms can be facilitated by a modular, user-space alternative. In this paper, we present a DualPI2 module for the Mahimahi network emulator, designed to support extensible, component-level experimentation without kernel modification. We conduct a statistical behavioral characterization of the Mahimahi implementation by examining key metrics across diverse traffic patterns and network conditions, using the Linux kernel implementation as a reference baseline. Our analysis shows that behavioral alignment across execution environments is not automatic: identical DualPI2 parameterization does not guarantee identical dynamics. Instead, key control parameters exhibit environment-dependent sensitivity, leading to regime-dependent discrepancies across bandwidth-delay product (BDP) conditions. Through targeted parameter exploration, we identify configurations that improve cross-platform alignment in low BDP regimes, while revealing structural differences that persist under higher load. This work provides both a practical tool for experimental L4S research and empirical insight into cross-platform behavioral differences, highlighting the importance of systematic characterization and environment-aware parameter selection in emulation-based AQM studies.