Demo Data from EDBT 2026 / reviewers in the wild / expert
Kurt Kremer
dblp:52/3492
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 1994
—ORCID · unresolved
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 architecture, parallel and distributed computing, and storage systems
1 paper |
Cloud and datacenter computing · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Cloud and datacenter computing
bin packing |
0.0 | 1 | 1994 | Scheduling a Metacomputer by an Implicit Voting System · HPDC 1994 |
Cloud and datacenter computing
resource management |
0.0 | 1 | 1994 | Scheduling a Metacomputer by an Implicit Voting System · HPDC 1994 |
Methods — techniques the papers use, named apart from their topics
simulation · 0.0bin packing · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1994 | Scheduling a Metacomputer by an Implicit Voting SystemabstractWe address the problem of scheduling hardware requests to a metacomputer environment. The environment may consist of a heterogeneous set of computing resources. A high level abstraction of the metacomputer is assumed to take care of the heterogeneity. The scheduling problem is considered in two parts. Some requests are extracted from the waiting room at first and scheduled afterwards by using bin packing to allocate the hardware resources. The bin packing algorithm is dynamically turned by the current mixture of the requests to tradeoff utilization versus response time. The extraction algorithm ensures prioritizing without starving lower priority jobs. The Implicit Voting System is compared to a well known bin packing algorithm by simulation. IVS improves the system utilization by 30% and simultaneously the average waiting time by 9%. Its behavior is also validated by integration into the Computing Center Software, CCS. Currently, this software package serves a pool of different transputer based MPP-systems to a large user community.> Friedhelm Ramme, Kurt Kremer |
HPDC | 2 |