EDBT 2026 Demo / reviewers in the wild / expert
Jork Wolter
dblp:49/46
· 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
Applied, interdisciplinary, general and emerging computing · 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 |
Embedded and real-time systems · 88% Performance modeling and evaluation · 12% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Embedded and real-time systems › real-time scheduling
admission control |
0.0 | 1 | 2001 | Quality-Assuring Scheduling-Using Stochastic Behavior to Improve Resource Utilization · RTSS 2001 |
Embedded and real-time systems
real-time scheduling |
0.0 | 1 | 2001 | Quality-Assuring Scheduling-Using Stochastic Behavior to Improve Resource Utilization · RTSS 2001 |
Embedded and real-time systems
execution time distribution |
0.0 | 1 | 2001 | Quality-Assuring Scheduling-Using Stochastic Behavior to Improve Resource Utilization · RTSS 2001 |
Performance modeling and evaluation
workload characterization |
0.0 | 1 | 2001 | Quality-Assuring Scheduling-Using Stochastic Behavior to Improve Resource Utilization · RTSS 2001 |
Methods — techniques the papers use, named apart from their topics
stochastic modeling · 0.0resource reservation · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2001 | Quality-Assuring Scheduling-Using Stochastic Behavior to Improve Resource UtilizationabstractWe present a unified model for admission and scheduling, applicable for various active resources such as CPU or disk to assure a requested quality in situations of temporary overload. The model allows us to predict and control the behavior of applications based on given quality requirements. It uses the variations in the execution time, i.e., the time any active resource is needed We split resource requirements into a mandatory part which must be available and an optional part which should be available as often as possible but at least with a certain percentage. In combination with a given distribution for the execution time we can move away from worst-case reservations and drastically reduce the amount of reserved resources for applications which can tolerate occasional deadline misses. This increases the number of admittable applications. For example, with negligible loss of quality our system can admit more than two times the disk bandwidth than a system based on the worst-case. Finally, we validated the predictions of our model by measurements using a prototype real-time system and observed a high accuracy between predicted and measured values. Claude-Joachim Hamann, Lars Reuther, Jork Wolter, Hermann Härtig, Jork Löser, Sebastian Schönberg |
RTSS | 3 |