Parallel Architectures For Priority Scheduling In Programmable Data Plane Switches

2026-10-03

AI Summary

This study addresses the challenge that exact priority scheduling in programmable data planes struggles to achieve line-rate processing, while approximate approaches suffer from correctness deficiencies. To overcome these limitations, this work proposes two parallel architectures, P3PO and PPQA. The core innovation lies in decomposing a global priority queue into multiple parallel smaller queues, introducing the first parallel priority queue design based on cascaded boundaries or occupancy distributions to transcend the performance bottleneck of conventional single large-capacity queues. Leveraging the NetBench simulator, the project implements dynamic multi-queue multiplexing and evaluates it under web search and data mining workloads. Results demonstrate that the proposed approach effectively balances scheduling accuracy with hardware scalability, significantly enhancing scheduling precision in high-throughput scenarios.

Abstract

Programmable Data Plane (PDP) switches enable flexible packet processing but remain limited in scheduling capabilities, particularly for priority-based policies that require strict ordering of packets according to user-defined ranks. An earlier work, called Push-in First-out (PIFO), proposed a priority queue that enables ordering enqueued packets based on their priority. It provided an ideal abstraction for programmable packet scheduling; however, its requirement for line-rate packet sorting makes it impractical at high network speeds (100 Gbps and beyond). Approximate schedulers such as SPPIFO, AIFO, and RIFO reduce complexity but introduce priority inversions, thus degrading latency, fairness, and Flow completion times (FCTs) since they rely on First-in First-out (FIFO) queues or use Active Queue Management (AQM) as a substitute for scheduling. To address the scalability limitations of accurate schedulers while avoiding the correctness issues of approximate schedulers, this work proposes two packet queuing architectures, Parallel Processing for Priority Ordering (P3PO) and Parallel PIFO Queuing Architecture (PPQA). Both architectures decompose a large global priority queue into multiple smaller bounded-capacity priority queues that operate in parallel. P3PO uses a cascading set of priority queues with priority-based bounds to ensure that packets are inserted into the earliest queue capable of maintaining ordering. PPQA distributes packets across multiple independent priority queues based on occupancy, using a demultiplexer for balanced queuing and a multiplexer for globally selecting the highest-priority packet at dequeue. The architectures are implemented in the NetBench packet-level simulator and evaluated using empirical datacenter workloads (Web-search and Data-mining).

Problem

• Programmable Data Plane
• Priority Scheduling
• PIFO
• Priority Inversion
• Scalability

Innovation

• Programmable Data Plane
• Priority Scheduling
• Parallel Queuing Architecture
• PIFO
• Scalability