RIFO: Pushing the Efficiency of Programmable Packet Schedulers

Packet scheduling is a fundamental networking task that recently received renewed attention in the context of programmable data planes. Programmable packet scheduling systems such as those based on Push-In First-Out (PIFO) abstraction enabled flexible scheduling policies, but are too resource-expensive for large-scale line rate operation. This prompted research into practical programmable schedulers (e.g., SP-PIFO, AIFO) approximating PIFO behavior on regular hardware. Yet, their scalability remains limited due to extensive number of memory operations. To address this, we design an effective yet resource-efficient packet scheduler, Range-In First-Out (RIFO), which uses only three mutable memory cells and one FIFO queue per PIFO queue. RIFO is based on multi-criteria decision-making principles and uses small guaranteed admission buffers. Our large-scale simulations in Netbench demonstrate that despite using fewer resources, RIFO generally achieves competitive flow completion times across all studied workloads, and is especially effective in workloads with a significant share of large flows, reducing flow completion time up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$4.91\times $ </tex-math></inline-formula> in datamining workload compared to state-of-the-art solutions. Our prototype implementation using P4 on Tofino switches requires only 600 lines of code, is scalable, and runs at line rate.

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Publication Details

Journal
IEEE Transactions on Networking
Published
2025-01-27
DOI
https://doi.org/10.1109/ton.2025.3531129
Citations
2
Primary Topic
Advanced Wireless Network Optimization
Type
article
Field-Weighted Citation Impact
1.46

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article

RIFO: Pushing the Efficiency of Programmable Packet Schedulers

Habib Mostafaei, Maciej Pacut, Stefan Schmid
2 citations
IEEE Transactions on Networking
Advanced Wireless Network Optimization
1.46
article

RIFO: Pushing the Efficiency of Programmable Packet Schedulers

Habib Mostafaei, Maciej Pacut, Stefan Schmid
article en
2 citations

Abstract

Packet scheduling is a fundamental networking task that recently received renewed attention in the context of programmable data planes. Programmable packet scheduling systems such as those based on Push-In First-Out (PIFO) abstraction enabled flexible scheduling policies, but are too resource-expensive for large-scale line rate operation. This prompted research into practical programmable schedulers (e.g., SP-PIFO, AIFO) approximating PIFO behavior on regular hardware. Yet, their scalability remains limited due to extensive number of memory operations. To address this, we design an effective yet resource-efficient packet scheduler, Range-In First-Out (RIFO), which uses only three mutable memory cells and one FIFO queue per PIFO queue. RIFO is based on multi-criteria decision-making principles and uses small guaranteed admission buffers. Our large-scale simulations in Netbench demonstrate that despite using fewer resources, RIFO generally achieves competitive flow completion times across all studied workloads, and is especially effective in workloads with a significant share of large flows, reducing flow completion time up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$4.91\times $ </tex-math></inline-formula> in datamining workload compared to state-of-the-art solutions. Our prototype implementation using P4 on Tofino switches requires only 600 lines of code, is scalable, and runs at line rate.

IEEE Transactions on NetworkingVol. 33(3)
Fraunhofer Institute for Secure Information Technology (DE), Technische Universität Berlin (DE), Eindhoven University of Technology (NL)
Deutsche Forschungsgemeinschaft
Affordable and clean energy
Openalex Percentile: Top 20%
Advanced Wireless Network Optimization
1.46
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RIFO: Pushing the Efficiency of Programmable Packet Schedulers — Habib Mostafaei, Maciej Pacut, et al. · IEEE Transactions on Networking (2025) | TGRS Research Map | TGRS