Demo Data from EDBT 2026 / reviewers in the wild / expert
Brian R. Crowley
dblp:92/2076
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2001
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 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 |
Network measurement and analytics · 67% Internet of things and sensor networks · 33% | |
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Distributed systems · 100% |
Topics — the 2 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Internet of things and sensor networks › wireless sensor network › network diagnosis
bottleneck detection |
0.0 | 1 | 2001 | Network Characterization Service (NCS) · HPDC 2001 |
Network measurement and analytics
network characterization |
0.0 | 1 | 2001 | Network Characterization Service (NCS) · HPDC 2001 |
Methods — techniques the papers use, named apart from their topics
cooperative information gathering · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2001 | Network Characterization Service (NCS)abstractDistributed applications require information to effectively utilize the network. Some of the information they require is the current and maximum bandwidth, current and minimum latency, bottlenecks, burst frequency and congestion extent. This type of information allows applications to determine parameters like the optimal TCP buffer size. In this paper, we present a cooperative information-gathering tool called the Network Characterization Service (NCS). NCS runs in the user space and is used to acquire network information. Its protocol is designed for scalable and distributed deployment, similar to DNS. Its algorithms provide efficient, speedy and accurate detection of bottlenecks, especially dynamic bottlenecks. On current and future networks, dynamic bottlenecks do and will affect network performance dramatically. Guojun Jin, George Yang, Brian R. Crowley, Deborah A. Agarwal |
HPDC | 3 |