Demo Data from EDBT 2026 / reviewers in the wild / expert
Sven Schmidt
dblp:99/4895
· DBLP profile ↗
4ranked-venue papers
4as first author
0since 2021 · last 2005
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 3 · 3 first-author
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.
| Databases, data mining, and information retrieval
2 papers |
Query processing and optimization · 52% Data stream processing · 48% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Data stream processing
continuous query processing |
0.1 | 2 | 2005 | Robust Real-time Query Processing with QStream · VLDB 2005 QStream: Deterministic Querying of Data Streams · VLDB 2004 |
Query processing and optimization › online query processing
real-time query processing |
0.1 | 1 | 2005 | Robust Real-time Query Processing with QStream · VLDB 2005 |
Query processing and optimization › query optimization
robust query processing |
0.1 | 1 | 2005 | Robust Real-time Query Processing with QStream · VLDB 2005 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2005 | Real-Time Scheduling for Data Stream Management SystemsabstractQuality-aware management of data streams is gaining more and more importance with the amount of data produced by streams growing continuously. The resources required for data stream processing depend on different factors and are limited by the environment of the data stream management system (DSMS). Thus, with a potentially unbounded amount of stream data and limited processing resources, some of the data stream processing tasks (originating from different users) may not be satisfyingly answered, and therefore, users should be enabled to negotiate a certain quality for the execution of their stream processing tasks. After the negotiation process, it is the responsibility of the Data Stream Management System to meet the quality constraints by using adequate resource reservation and scheduling techniques. Within this paper, we consider different aspects of real-time scheduling for operations within a DSMS. We propose a scheduling concept which enables us to meet certain time-dependent quality of service requirements for user-given processing tasks. Furthermore, we describe the implementation of our scheduling concept within a real-time capable data stream management system, and we give experimental results on that. Sven Schmidt, Thomas Legler, Daniel Schaller, Wolfgang Lehner |
ECRTS | 1 |
| 2005 | Source-aware Join Strategies of Sensor Data Streams
Sven Schmidt, Marc Fiedler, Wolfgang Lehner |
SSDBM | 1 |
| 2005 | Robust Real-time Query Processing with QStream
Sven Schmidt, Thomas Legler, Sebastian Schär, Wolfgang Lehner |
VLDB | 1 |
| 2004 | QStream: Deterministic Querying of Data Streams
Sven Schmidt, Henrike Berthold, Wolfgang Lehner |
VLDB | 1 |