Demo Data from EDBT 2026 / reviewers in the wild / expert
Bodong Yan
dblp:387/3818
· DBLP profile ↗
3ranked-venue papers
1as first author
3since 2021 · last 2026
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 3 · 1 first-author · 3 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer networks
2 papers |
Datacenter networks · 60% Transport protocols and congestion control · 21% Network measurement and analytics · 18% | |
| Computer architecture, parallel and distributed computing, and storage systems
2 papers |
High-performance computing · 54% Performance modeling and evaluation · 46% |
Topics — the 6 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Datacenter networks
RDMA |
1.9 | 2 | 2026 | Scalable, Low-Latency, and Hi-Precision Congestion Control in RDMA Datacenter Networks · IEEE Trans. Netw. 2026 Towards Lightweight Traffic Forecasting in RDMA Networks: Design and Application · INFOCOM 2025 |
Transport protocols and congestion control › low-latency transport
low-latency congestion control |
1.0 | 1 | 2026 | Scalable, Low-Latency, and Hi-Precision Congestion Control in RDMA Datacenter Networks · IEEE Trans. Netw. 2026 |
Datacenter networks › RDMA
RDMA congestion control |
1.0 | 1 | 2026 | Scalable, Low-Latency, and Hi-Precision Congestion Control in RDMA Datacenter Networks · IEEE Trans. Netw. 2026 |
Network measurement and analytics
traffic prediction |
0.9 | 1 | 2025 | Towards Lightweight Traffic Forecasting in RDMA Networks: Design and Application · INFOCOM 2025 |
High-performance computing
low-latency networking |
0.3 | 1 | 2026 | Scalable, Low-Latency, and Hi-Precision Congestion Control in RDMA Datacenter Networks · IEEE Trans. Netw. 2026 |
Performance modeling and evaluation
workload characterization |
0.3 | 1 | 2025 | Towards Lightweight Traffic Forecasting in RDMA Networks: Design and Application · INFOCOM 2025 |
Methods — techniques the papers use, named apart from their topics
congestion control · 2.0machine learning · 1.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | Scalable, Low-Latency, and Hi-Precision Congestion Control in RDMA Datacenter Networks
Sun Xu, Bodong Yan, Yangming Zhao, Jianchun Liu, Hongli Xu 0001 |
IEEE Trans. Netw. | 2 |
| 2025 | Towards Lightweight Traffic Forecasting in RDMA Networks: Design and Application
Bodong Yan, Sun Xu, Bingyi Liu, Jianchun Liu |
INFOCOM | 3 |
| 2024 | LHCC: Low-Latency and Hi-Precision Congestion Control in RDMA Datacenter NetworksabstractCongestion Control (CC) plays a vital role in deploying lossless datacenter networks based on Remote Direct Memory Access (RDMA). A high-performance CC scheme should provide low-latency and precise feedback to congestion events. However, no existing CC schemes achieved both features simultaneously. In this paper, we propose LHCC, a Low-latency and Hi-precision Congestion Control scheme for RDMA datacenter networks. LHCC uses out-band signaling to notify the network status and hence a packet sender can detect congestion events within an RTT. In addition, LHCC adjusts packet sending rate by taking into consideration all queues along the entire path that a packet has gone through. Accordingly, it provides a more precise CC compared with existing schemes especially when there are multiple bottlenecks in the networks. We build the LHCC prototype on a real testbed carrying NVIDIA BlueField-3 NICs and AGM39D FPGAs. Both testbed experiments and extensive simulations show that LHCC can reduce the Flow Completion Time (FCT) slow down and reduce the buffer usage (i.e., reduce the queue lengths) by up to 62.5% and 58%, respectively, compared with the state-of-the-art high-precision CC scheme, HPCC. Bodong Yan, Yangming Zhao, Sun Xu, Jianchun Liu, Hongli Xu 0001 |
IWQoS | 1 |