Demo Data from EDBT 2026 / reviewers in the wild / expert
Wenkai Wan
dblp:213/7393
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 1
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
1 paper |
Transport protocols and congestion control · 54% Wireless networking · 23% Cellular and mobile networks · 23% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Cellular and mobile networks › mobile networks
mobile data networks |
0.4 | 1 | 2020 | Optimizing TCP Loss Recovery Performance Over Mobile Data Networks · IEEE Trans. Mob. Comput. 2020 |
Wireless networking
retransmission |
0.4 | 1 | 2020 | Optimizing TCP Loss Recovery Performance Over Mobile Data Networks · IEEE Trans. Mob. Comput. 2020 |
Transport protocols and congestion control › loss recovery
TCP loss recovery |
0.4 | 1 | 2020 | Optimizing TCP Loss Recovery Performance Over Mobile Data Networks · IEEE Trans. Mob. Comput. 2020 |
Transport protocols and congestion control
TCP performance |
0.4 | 1 | 2020 | Optimizing TCP Loss Recovery Performance Over Mobile Data Networks · IEEE Trans. Mob. Comput. 2020 |
Transport protocols and congestion control
flow control |
0.1 | 1 | 2020 | Optimizing TCP Loss Recovery Performance Over Mobile Data Networks · IEEE Trans. Mob. Comput. 2020 |
Methods — techniques the papers use, named apart from their topics
kernel implementation · 0.4emulation · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | Optimizing TCP Loss Recovery Performance Over Mobile Data NetworksabstractRecent advances in high-speed mobile networks have revealed new bottlenecks in ubiquitous TCP protocol deployed in the Internet. In addition to differentiating non-congestive loss from congestive loss, our experiments revealed two significant performance bottlenecks during the loss recovery phase: flow control bottleneck and application stall, resulting in degradation in QoS performance. To tackle these two problems, we first develop a novel opportunistic retransmission algorithm to eliminate the flow control bottleneck, which enables TCP sender to transmit new packets even if receiver's receiving window is exhausted. Second, application stall can be significantly alleviated by carefully monitoring and tuning the TCP sending buffer growth mechanism. We implemented and modularized the proposed algorithms in the Linux kernel thus they can plug-and-play with the existing TCP loss recovery algorithms easily. We evaluated our proposed algorithms over emulated and real experiments and showed that, compared to existing TCP loss recovery algorithms, the proposed optimization algorithms improve the bandwidth efficiency by up to 133 percent and completely mitigate RTT spikes, i.e., over 50 percent RTT reduction, over the loss recovery phase. Ke Liu 0004, Zhongbin Zha, Wenkai Wan, Vaneet Aggarwal, Binzhang Fu, Mingyu Chen 0001 |
IEEE Trans. Mob. Comput. | 3 |