Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Sven Schmidt

dblp:99/4895 · DBLP profile ↗
← Back
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

TopicWeightPapersLastEvidence papers
Data stream processing
continuous query processing
0.122005
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
0.112005
Robust Real-time Query Processing with QStream · VLDB 2005
Query processing and optimization › query optimization
robust query processing
0.112005
Robust Real-time Query Processing with QStream · VLDB 2005
YearPublicationVenuePosition
2005 Real-Time Scheduling for Data Stream Management Systems
abstract
Quality-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
ECRTS1
2005 Source-aware Join Strategies of Sensor Data Streams
Sven Schmidt, Marc Fiedler, Wolfgang Lehner
SSDBM1
2005 Robust Real-time Query Processing with QStream
Sven Schmidt, Thomas Legler, Sebastian Schär, Wolfgang Lehner
VLDB1
2004 QStream: Deterministic Querying of Data Streams
Sven Schmidt, Henrike Berthold, Wolfgang Lehner
VLDB1