Demo Data from EDBT 2026 / reviewers in the wild / expert
J. Greyling
dblp:29/5570
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1984
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1Software engineering, systems software and programming languages · 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 architecture, parallel and distributed computing, and storage systems
1 paper |
Performance modeling and evaluation · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Performance modeling and evaluation › queueing models
mean value analysis |
0.0 | 1 | 1984 | Improved Lineariser Methods for Queueing Networks with Queue Dependent Centres · SIGMETRICS 1984 |
Performance modeling and evaluation › queueing models
queueing network model |
0.0 | 1 | 1984 | Improved Lineariser Methods for Queueing Networks with Queue Dependent Centres · SIGMETRICS 1984 |
Methods — techniques the papers use, named apart from their topics
mean value analysis · 0.0lineariser approximation · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1984 | Improved Lineariser Methods for Queueing Networks with Queue Dependent CentresabstractThe Lineariser is an MVA-based technique developed for the approximate solution of large multiclass product form queueing networks. The Lineariser is capable of computing accurate solutions for networks of fixed rate centres. However, problems arise when the Lineariser is applied to networks containing centres with queue dependent service rates. Thus networks exist which seem well suited (a large number of lightly loaded centres, large numbers of customers in each closed chain) for Lineariser solution but whose queue dependent centres cannot be solved accurately by the Lineariser method. Examples have also been found where the Lineariser computes accurate values for the queue lengths, waiting times and throughputs though the values computed for the queue length distributions are totally in error. Anthony E. Krzesinski, J. Greyling |
SIGMETRICS | 2 |