Demo Data from VLDB 2026 / reviewers in the wild / expert
Jeffrey L. Freschl
dblp:10/5310
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2007
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 2
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 |
Distributed systems · 87% Performance modeling and evaluation · 13% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Distributed systems
grid computing |
0.0 | 1 | 2003 | A Performance Study of Monitoring and Information Services for Distributed Systems · HPDC 2003 |
Distributed systems › service-oriented architecture › service management
service monitoring |
0.0 | 1 | 2003 | A Performance Study of Monitoring and Information Services for Distributed Systems · HPDC 2003 |
Methods — techniques the papers use, named apart from their topics
benchmarking · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2007 | Scalability analysis of three monitoring and information systems: MDS2, R-GMA, and Hawkeye
Xuehai Zhang, Jeffrey L. Freschl, Jennifer M. Schopf |
J. Parallel Distributed Comput. | 2 |
| 2003 | A Performance Study of Monitoring and Information Services for Distributed SystemsabstractMonitoring and information services form a key component of a distributed system, or Grid. A quantitative study of such services can aid in understanding the performance limitations, advise in the deployment of the monitoring system, and help evaluate future development work. To this end, we study the performance of three monitoring and information services for distributed systems: the Globus Toolkit/spl reg/ Monitoring and Discovery Service (MDS2), the European Data Grid Relational Grid Monitoring Architecture (R-GMA) and Hawkeye, part of the Condor project. We perform experiments to test their scalability with respect to number of users, number of resources and amount of data collected. Our study shows that each approach has different behaviors, often due to their different design goals. In the four sets of experiments we conducted to evaluate the performance of the service components under different circumstances, we found a strong advantage to caching or pre-fetching the data, as well as the need to have primary components at well-connected sites because of the high load seen by all systems. Xuehai Zhang, Jeffrey L. Freschl, Jennifer M. Schopf |
HPDC | 2 |