Leveraging deep reinforcement learning for traffic engineering: A survey

Y **ao, J Liu, J Wu, N Ansari - IEEE Communications Surveys & …, 2021 - ieeexplore.ieee.org
After decades of unprecedented development, modern networks have evolved far beyond
expectations in terms of scale and complexity. In many cases, traditional traffic engineering …

SketchINT: Empowering INT with TowerSketch for per-flow per-switch measurement

K Yang, S Long, Q Shi, Y Li, Z Liu, Y Wu… - … on Parallel and …, 2023 - ieeexplore.ieee.org
Network measurement is indispensable to network operations. INT solutions that can
provide fine-grained per-switch per-packet information serve as promising solutions for per …

One more config is enough: Saving (DC) TCP for high-speed extremely shallow-buffered datacenters

W Bai, S Hu, K Chen, K Tan… - IEEE/ACM Transactions …, 2020 - ieeexplore.ieee.org
The link speed in production datacenters is growing fast, from 1 Gbps to 40 Gbps or even
100 Gbps. However, the buffer size of commodity switches increases slowly, eg, from 4 MB …

Flow scheduling with imprecise knowledge

W Li, X He, Y Liu, K Li, K Chen, Z Ge, Z Guan… - … USENIX Symposium on …, 2024 - usenix.org
Most existing data center network (DCN) flow scheduling solutions aim to minimize flow
completion times (FCT). However, these solutions either require precise flow information …

Enabling load balancing for lossless datacenters

J Hu, C Zeng, Z Wang, J Zhang, K Guo… - 2023 IEEE 31st …, 2023 - ieeexplore.ieee.org
Various datacenter network (DCN) load balancing schemes have been proposed in the past
decade. Unfortunately, most of these solutions designed for lossy DCNs do not work well for …

A receiver-driven transport protocol with high link utilization using anti-ECN marking in data center networks

J Hu, J Huang, Z Li, J Wang, T He - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Existing reactive or proactive congestion control protocols are hard to simultaneously
achieve ultra-low latency and high link utilization across all workloads ranging from delay …

DRL-PLink: Deep reinforcement learning with private link approach for mix-flow scheduling in software-defined data-center networks

WX Liu, J Lu, J Cai, Y Zhu, S Ling… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
In datacenter networks, bandwidth-demanding elephant flows without deadline and delay-
sensitive mice flows with strict deadline coexist. They compete with each other for limited …

Efficient data-plane memory scheduling for in-network aggregation

H Wang, Y Qin, CL Lao, Y Le, W Wu, K Chen - arxiv preprint arxiv …, 2022 - arxiv.org
As the scale of distributed training grows, communication becomes a bottleneck. To
accelerate the communication, recent works introduce In-Network Aggregation (INA), which …

Flash: Joint Flow Scheduling and Congestion Control in Data Center Networks

C Gao, S Chu, H Xu, M Xu, K Ye… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Flow scheduling and congestion control are two important techniques to reduce flow
completion time in data center networks. While existing works largely treat them …

Towards fine-grained load balancing with dynamical flowlet timeout in datacenter networks

J Hu, R Li, Y Liu, J Wang - Computer Networks, 2024 - Elsevier
In modern datacenter networks (DCNs), load balancing mechanisms are widely deployed to
enhance link utilization and alleviate congestion. Recently, a large number of load …