Demo Data from SIGIR 2026 / reviewers in the wild / expert
Haixuan Tong
dblp:374/9930
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0008-6102-0132ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 1 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 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
1 paper |
Transport protocols and congestion control · 87% Network measurement and analytics · 13% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Transport protocols and congestion control › TCP
TCP slow-start |
0.8 | 1 | 2024 | Cold Start or Hot Start? Robust Slow Start in Congestion Control with A Priori Knowledge for Mobile Web Services · WWW 2024 |
Network measurement and analytics › web performance measurement
mobile web performance |
0.2 | 1 | 2024 | Cold Start or Hot Start? Robust Slow Start in Congestion Control with A Priori Knowledge for Mobile Web Services · WWW 2024 |
Methods — techniques the papers use, named apart from their topics
adaptive probing · 0.8a priori knowledge · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Cold Start or Hot Start? Robust Slow Start in Congestion Control with A Priori Knowledge for Mobile Web ServicesabstractMobile web services value a quick loading of contents in the first page, which is quantified by the above-the-fold time of the first page (first AFT) and is likely to fall into the slow start phase in congestion control. However, the widely deployed slow start mechanism is "cold start", which manually hardcodes the parameters and is not suitable for the first AFT of heterogeneous mobile web services. We revisit the slow start mechanism and find that it could be optimized with a priori knowledge. However, blindly relying on a priori knowledge is not robust enough to handle the fluctuating mobile networks and unpredictable application traffic. In this paper, we propose WiseStart, a "hot-start-based" slow start mechanism. WiseStart utilizes the priori knowledge to set the initial parameters, continuously probes the new connection to handle the fluctuating network conditions, and carefully adapts to the application-limit scenarios. We implement WiseStart in a popular mobile web service online in production. Comprehensive experiments demonstrate that WiseStart reduces the First AFT by 25.43% and the average RCT at connection establishment by 16.15% compared to the default slow start mechanism and other state-of-the-art baselines. Jia Zhang 0010, Haixuan Tong, Enhuan Dong, Mingwei Xu 0001, Zili Meng |
WWW | 2 |