BeeQoS: A Cloud-Native QoS System for Adaptive and Scalable Multi-Priority Bandwidth Guarantees

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Authors: Jinyao Liu, Si Wu, Haoyuan Ma, Chaoqun Li, Hongjing Yu, Dingyi Jia, Feng Li, Pengfei Hu
Cited by: 1
References: 13

Abstract

Modern cloud applications, from interative web services to mobile and WoT workloads, generate highly dynamic multi-tenant network demands. Guaranteeing priority-aware bandwidth remains challenging: legacy shapers like Linux Traffic Control Hierarchical Token Bucket are static and unscalable, while cloud-native solutions such as Cilium offer only coarse-grained rate limiting. We present BeeQoS, a cloud-native QoS system that delivers low-latency, adaptive, and scalable multi-priority bandwidth guarantees. BeeQoS consists of an eBPF-powered data plane for high-performance, fine-grained per-packet shaping, a demand-aware control plane that senses real-time flow requirements and adaptively reallocates bandwidth, and seamless Kubernetes integration for expressive policy specification and cluster-wide scalable deployment. Evaluation shows that BeeQoS scales to 1K+ flows with stable performance, boosts high-/medium-priority throughput by 14.6%/36.4%, cuts median latency by 72.4%, reduces deployment overhead, and improves video QoE by 27.3% over state-of-practice baselines.

Fields of Study & Subjects

Network Traffic and Congestion Control Software-Defined Networks and 5G Cloud Computing and Remote Desktop Technologies

Publication details

Journal / source
Proceedings of the ACM Web Conference 2026
Publisher
ACM
Pages
5515–5524
Publication date
12 April 2026