Demo Data from EDBT 2026 / reviewers in the wild / expert
Chun-Yun Chang
dblp:62/10609
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 2011
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 1 · 1 first-author
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 |
Content delivery and video streaming · 87% Network performance modeling · 13% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Content delivery and video streaming › peer-to-peer streaming
chunk scheduling |
0.1 | 1 | 2011 | Striking the balance between content diversity and content importance in swarm-based P2P streaming · ICNP 2011 |
Content delivery and video streaming
peer-to-peer streaming |
0.1 | 1 | 2011 | Striking the balance between content diversity and content importance in swarm-based P2P streaming · ICNP 2011 |
Methods — techniques the papers use, named apart from their topics
simulation · 0.1dynamic strategy-switching · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2011 | Striking the balance between content diversity and content importance in swarm-based P2P streamingabstractDuring recent years, the success of live swarm-based P2P streaming system has been witnessed. Nevertheless, how to design an effective mechanism for mitigating video quality degradation in a lossy network environment is still not thoroughly resolved yet. Unlike conventional client-server paradigm, there is data availability problem in swarm-based P2P streaming system. If we directly conduct the importance-first scheduling strategy in swarm-based P2P streaming system, the serious content bottleneck for low priority chunks occurs, particularly when the population size is large. In this work, we propose a dynamic strategy-switching approach that combines the advantages of random scheduling and importance first scheduling to deal with the problem. Simulation results indicate that our approach not only provides better scheduling efficiency, but also is scalable even if population size is large. Chun-Yun Chang, Cheng-Fu Chou, Ming-Hung Chen |
ICNP | 1 |