Demo Data from VLDB 2026 / reviewers in the wild / expert
Michael Sczittnick
dblp:81/5901
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1990
—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 |
Network performance modeling · 91% Routing and switching · 9% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Network performance modeling
markov chain model |
0.0 | 1 | 1990 | Modeling and Analysis of Communication Systems Based on Computational Methods for Markov Chains · IEEE J. Sel. Areas Commun. 1990 |
Network performance modeling › queueing analysis
markovian queueing model |
0.0 | 1 | 1990 | Modeling and Analysis of Communication Systems Based on Computational Methods for Markov Chains · IEEE J. Sel. Areas Commun. 1990 |
Network performance modeling
queueing analysis |
0.0 | 1 | 1990 | Modeling and Analysis of Communication Systems Based on Computational Methods for Markov Chains · IEEE J. Sel. Areas Commun. 1990 |
Routing and switching
adaptive routing |
0.0 | 1 | 1990 | Modeling and Analysis of Communication Systems Based on Computational Methods for Markov Chains · IEEE J. Sel. Areas Commun. 1990 |
Methods — techniques the papers use, named apart from their topics
markov chain · 0.0direct and iterative numerical methods · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1990 | Modeling and Analysis of Communication Systems Based on Computational Methods for Markov ChainsabstractThe authors describe a computational approach for modeling and analyzing modern communication systems based on numerical methods for Markov chains. Advanced direct and iterative procedures for the calculation of the stationary distribution of a homogeneous discrete- or continuous-time Markov chain with finite state space are presented. They are implemented in a convenient software tool called MACOM for interactive modeling and performance evaluation of communication systems. MACOM provides the user with a predefined markovian model world describing modern telecommunication networks with adaptive routing schemes and advanced congestion-control mechanisms. The versatility of these algorithms is illustrated by their application to Markovian queuing models derived from telecommunications networks.> Udo R. Krieger, Bruno Müller-Clostermann, Michael Sczittnick |
IEEE J. Sel. Areas Commun. | 3 |