ConnSched: Selective Connection Offloading Framework for Accelerating Stateful NFs with DPU
Songlin Chen, Fuliang Li, Qin Chen, Chengxi Gao, Man Hou, Jiaxing Shen
Abstract
The escalating volume of network traffic drives the offloading of stateful Network Functions (NFs) to Data Processing Units (DPUs) for enhanced performance and host CPU relief. However, current DPU offloading approaches, while often boosting forwarding throughput, frequently suffer from poor concurrency performance. Effectively addressing this requires overcoming challenges inherent to DPU architectures, such as the Arm subsystem’s limitations in rapid connection setup and the intricate management of hardware flow table resources, which can otherwise cap connection processing rates (e.g., below 100k connections per second (CPS) with conventional methods). To address these limitations, we present ConnSched, a high-performance software framework for efficient and robust offloading of connection processing in stateful NFs to DPUs. ConnSched incorporates two key mechanisms: ConnSched-Filter adaptively identifies and filters out short-lived connections by monitoring their lifecycle and current DPU load, thereby reserving hardware resources for long-lived connections and enhancing robustness against concurrent traffic bursts. Complementing this, ConnSched-QoS implements a prioritized offloading mechanism, managing DPU hardware flow table entries by giving precedence to critical flows, especially when resources are constrained. Experimental results demonstrate that ConnSched achieves a 6.4× higher new connection creation rate compared to standard DPU offloading methods and 38.7% higher throughput than CPU-based approaches. ConnSched simultaneously improves concurrent connection handling capability while maintaining high packet forwarding performance.
Ask about this paper
Ask your agent about it.
Lune has read the top-tier papers around this one, so every answer names the papers it rests on.
Your agent calls
Lunesearch_papers
Free to start. No credit card required.
Terminal
Install the CLIlune papers get ab408064-a8b7-4ff7-9a3a-e2a6f3e8e482Related papers
- Dyssect: Dynamic Scaling of Stateful Network FunctionsFabrício B. Carvalho, Ronaldo A. Ferreira, Ítalo Cunha, Marcos A. M. Vieira et al.INFOCOM 2022 · 10 citations
- Accelerating Sketch-based End-Host Traffic Measurement with Automatic DPU OffloadingXiang Chen, Xi Sun, Wenbin Zhang, Xin Yao et al.INFOCOM 2024 · 5 citations
- dpKernels: Harvesting DPU Compute Resources for Data-path Efficiency in Cloud Data ProcessingJiasheng Hu, Kaiwen Zheng, Anna Li, Sidharth Sankhe et al.VLDB 2026
- DDS: DPU-optimized Disaggregated StorageQizhen Zhang, Philip A. Bernstein, Badrish Chandramouli, Jason Hu et al.VLDB 2024 · 12 citations
- Transparent Multicore Scaling of Single-Threaded Network FunctionsLei Yan, Yueyang Pan, Diyu Zhou, George Candea et al.EuroSys 2024 · 5 citations
