通信学报2026，Vol.47Issue(2)：109-124,16.DOI:10.11959/j.issn.1000-436x.2026038
面向算力网络的端网协同RDMA拥塞控制
Congestion control for RDMA with end-network collaboration in computing power network
摘要
Abstract
To address the long control loop and hybrid traffic congestion issues caused by cross-domain interconnection scenarios of remote direct memory access(RDMA)technology,a congestion control method for computing power net-works,named WRCC(WAN RDMA congestion control),was proposed.A fair rate computing strategy based on input rate was employed,enabling switches to accurately calculate the port fair rate of congested queues.Combined with dual control loops on the near-source switch and in-band network telemetry technology,it achieved end-network collaboration rate control and rapidly responded to congestion.Simulation experiments demonstrate that compared with existing com-mercial methods,WRCC reduces the average and tail flow completion time by 8%～47%and 10%～70%.Prototype sys-tem tests indicate that compared with NVIDIA CX7,WRCC reduces the tail latency by 7%～49%in short-distance sce-narios.In long-distance scenarios of 640 kilometers,WRCC reduces the average and tail latency by 2%～7%and 45%～49%,while achieving the average throughput improvement of 26%～90%.关键词
拥塞控制/远程直接内存访问/算力网络/端网协同Key words
congestion control/remote direct memory access/computing power network/end-network collaboration分类
信息技术与安全科学引用本文复制引用
刘亚萍,严定宇,方滨兴,许名广,张硕,杨智凯..面向算力网络的端网协同RDMA拥塞控制[J].通信学报,2026,47(2):109-124,16.基金项目
新一代人工智能国家科技重大专项基金资助项目(No.2025ZD0122203) The New Generation Artificial Intelligence-National Science and Technology Major Project(No.2025ZD0122203) （No.2025ZD0122203）
