2026· IEEE Transactions on Network and Service Management· Vol 23, pp. 6927-6941· 0 citations· 55 references
Abstract
In data centers, large-scale many-to-one traffic can rapidly exhaust switch buffers and trigger priority-based flow control (PFC) pause, resulting in increased flow completion time (FCT) for uncongested flows. To address this issue, we propose an innovative switch-side fast and accurate flow control (FAFC) scheme. By differentially allocating pause time for each port during congestion, FAFC can minimize the performance loss for uncongested flows. Furthermore, FAFC is also coupled with an effective queue length prediction algorithm to enable proactive and reliable estimation of the congestion level. Extensive system-level simulations demonstrate that FAFC can flexibly allocate pause times across congested ports, which are not only compatible with existing PFC but also do not require per-flow states. We implemented FAFC in P4 programmable switches, showing it as lightweight flow control method that is portable for implementation in hardware. Remarkably, our large-scale simulations illustrate that compared to traditional PFC, FAFC improves the average FCT slowdown and 95% FCT slowdown by 10.6% and 23.3%, respectively, under Hadoop workload when performing HPCC congestion control.
Initial evaluations demonstrate that PFC-S can reduce the average flow completion time and effectively prevent congestion spreading, and experimental results show that PFC-S provides better protection for victim flows compared to standard PFC, BFC, and HPCC methods.
Weimin Gao, Jiawei Huang, Qile Wang et al.· Journal of High Speed Networ...· 0 citations
ProLet is a load balancing scheme that enables proactive probing and reroutes elephant flows at flowlet granularity in lossless RDMA networks and reduces average and tail flow completion time slowdowns by 69% and 79%, respectively, compared to state-of-the-art load balancing schemes.
Hong Wang, Jin-Hao Luo, J. Tan et al.· Asia-Pacific Workshop on Net...· 0 citations
Driven by the requirements of machine learning, cloud storage, and other network-intensive applications, remote direct memory access (RDMA) has been widely adopted in high-speed networks and is gradually being applied to geographically distributed datacenters. However, in cross-datacenter scenarios, long control loop latency and mixed traffic prevent existing RDMA congestion control schemes from perceiving and reacting to congestion in a timely and fair manner; this can lead to severe performance degradation and unfairness. To address these issues, we propose cdcPIM, a proactive congestion control scheme extended from datacenter parallel iterative matching (dcPIM) for cross-datacenter networks, which restructures the end-to-end control loop by introducing switch-coordinated control points, effectively transforming long-haul, RTT-bound feedback into localized control. Specifically, cdcPIM deploys a local control point by moving the token generation from the receiver to the sender side cross-datacenter switch, constraining the congestion control loop for inter-datacenter traffic within a single datacenter. Furthermore, cdcPIM introduces a remote control point to perform admission control for inter-datacenter traffic entering the receiver’s datacenter, thus avoiding intra-datacenter congestion caused by traffic bursts. Simulations demonstrate that when cdcPIM manages inter-datacenter traffic while cooperating with datacenter quantized congestion notification (DCQCN) for intra-datacenter traffic, long-haul congestion is effectively mitigated. Under mixed cross-datacenter workloads, DCQCN + cdcPIM reduces the overall average flow completion time (FCT) slowdown by up to 25.7% and the P99 FCT slowdown of intra-DC flows by up to 65.0% compared with the baseline scheme Themis.
Wenqiang Deng, Junyan Chen, Xuefeng Huang et al.· Journal of King Saud Univers...· 0 citations
ProFlow leverages distributed telemetry signals and offline-trained reinforcement learning to identify precursor congestion conditions and proactively reroute protected flows before throughput degradation occurs, demonstrating the effectiveness of anticipatory congestion management.
Sourya Saha, Md. Nurul Absur, Saptarshi Debroy· IEEE Conference on Local Com...· 0 citations
The proposed Multi-Path Multi-Level Feedback Queueing (MP-MLFQ) leverages the spatial diversity and regularity of DCNs to realize a scheduler with numerous logical priority levels while occupying as low as 2 physical priority queues within network switches.
Alessandro Cornacchia, Andrea Bianco, Paolo Giaccone et al.· 0 citations
: Multipath load balancing can effectively improve network throughput and reliability by aggregating the available bandwidth of multiple paths. However, existing load balancing schemes including Equal-Cost Multi-Path forwarding (ECMP), Weighted-Cost Multi-Path forwarding (WCMP) or LetFlow may lead to significant performance degradation due to hash conflicts and only target fixed symmetric topologies (e.g., Fattree). Flowlet switching has been proven to be a fine-grained load balancing technique, but remains elusive for widespread deployment. The emergence of network programmability including the control plane and data plane provides a new insight for the management of multipath load balancing. To achieve more effective load balancing and guarantee Quality of Service (QoS) on any network topology, we present ConFlet, a congestion-aware load balancing with Flowlet switching based on the cooperation of the data and control plane, where the control plane monitors the global network status to perform the optimized routing decision, and the data plane implements the flow splitting and path switching. Specifically, the centralized controller evaluates the reliability of nodes and links to perform multi-path routing calculations, ensuring that flows always travel along the most reliable multiple paths. The data plane can dynamically set the flowlet timeout to split flows into flowlets according to the path quality difference, and then implement path switching and congestion avoidance based on real-time congestion feedback. Experimental results show that compared to WCMP/LetFlow, ConFlet can significantly improve average service reliability and network throughput, and reduce average packet delay. Meanwhile, ConFlet can react quickly to congestion and maintain high resilience to network asymmetry
Unknown authors· Computers, Materials & C...· 0 citations
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