Simplifying Prioritization and Scheduling with P2CS

Abstract

Modern datacenter networks host diverse services and workloads with varying quality-of-service (QoS) requirements, yet are constrained by hardware limitations. Most notably, the small number of physical priority queues available in commodity switches. Existing scheduling mechanisms, whether end-host or in-network based, struggle to scale under these constraints due to their reliance on global priority information or complex queue management. This paper presents P2CS (Priority-based Probabilistic Congestion Signaling), a lightweight and scalable approach that enables fine-grained traffic prioritization using only a single FIFO queue. P2CS combines priority-aware probabilistic congestion signaling, priority-aware packet dropping, and simple switch-side arbitration to enforce prioritization across flows. P2CS supports a range of scheduling objectives, and requires minimal software changes making it readily deployable in today's datacenter infrastructure. Evaluation on representative workloads, including multi-tenant ML training, HPC, and mixed spray/ECMP traffic, demonstrates that P2CS achieves performance comparable to in-network mechanisms while significantly reducing complexity and cost.