ABM: Active buffer management in datacenters
Today's network devices share buffer across queues to avoid drops during transient
congestion and absorb bursts. As the buffer-per-bandwidth-unit in datacenter decreases, the …
congestion and absorb bursts. As the buffer-per-bandwidth-unit in datacenter decreases, the …
Flow scheduling with imprecise knowledge
Most existing data center network (DCN) flow scheduling solutions aim to minimize flow
completion times (FCT). However, these solutions either require precise flow information …
completion times (FCT). However, these solutions either require precise flow information …
Towards {Domain-Specific} Network Transport for Distributed {DNN} Training
The nature of machine learning (ML) applications exposes rich characteristics to underlying
network transport, yet little work has been done so far to systematically exploit these …
network transport, yet little work has been done so far to systematically exploit these …
Credence: Augmenting Datacenter Switch Buffer Sharing with {ML} Predictions
Packet buffers in datacenter switches are shared across all the switch ports in order to
improve the overall throughput. The trend of shrinking buffer sizes in datacenter switches …
improve the overall throughput. The trend of shrinking buffer sizes in datacenter switches …
Reverie: Low Pass {Filter-Based} Switch Buffer Sharing for Datacenters with {RDMA} and {TCP} Traffic
The switch buffers in datacenters today are shared by traffic classes with different loss
tolerance and reaction to congestion signals. In particular, while legacy applications use …
tolerance and reaction to congestion signals. In particular, while legacy applications use …
xnet: Improving expressiveness and granularity for network modeling with graph neural networks
Today's network is notorious for its complexity and uncertainty. Network operators often rely
on network models to achieve efficient network planning, operation, and optimization. The …
on network models to achieve efficient network planning, operation, and optimization. The …
Enabling load balancing for lossless datacenters
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 …
decade. Unfortunately, most of these solutions designed for lossy DCNs do not work well for …
PACC: Proactive and accurate congestion feedback for RDMA congestion control
The rapid upgrade of link speed and the prosperity of new applications in data center
networks (DCNs) lead to a rigorous demand for ultra-low latency and high throughput. To …
networks (DCNs) lead to a rigorous demand for ultra-low latency and high throughput. To …
Flow optimization strategies in data center networks: A survey
Y Liu, T Yu, Q Meng, Q Liu - Journal of Network and Computer Applications, 2024 - Elsevier
In the era of digitization, Data Center Networks (DCN) have emerged as a critical component
supporting infrastructure for cloud computing, big data analytics, online services, and more …
supporting infrastructure for cloud computing, big data analytics, online services, and more …
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 …
sensitive mice flows with strict deadline coexist. They compete with each other for limited …