SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Large-Sample and Deterministic Confidence Intervals for Online Aggregation
SSDBM '97 Proceedings of the Ninth International Conference on Scientific and Statistical Database Management
On the Quantitative Specification of Jitter Constrained Periodic Streams
MASCOTS '97 Proceedings of the 5th International Workshop on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems
Real Time Distributed Control Systems Using RTAI
ISORC '03 Proceedings of the Sixth IEEE International Symposium on Object-Oriented Real-Time Distributed Computing
Aurora: a new model and architecture for data stream management
The VLDB Journal — The International Journal on Very Large Data Bases
Monitoring streams: a new class of data management applications
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Load shedding in a data stream manager
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Operator scheduling in a data stream manager
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
QStream: deterministic querying of data streams
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Robust real-time query processing with QStream
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Time-bounded distributed QoS-aware service configuration in heterogeneous cooperative environments
Journal of Parallel and Distributed Computing
Quality-driven resource-adaptive data stream mining?
ACM SIGKDD Explorations Newsletter
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Data stream systems have to deal with massive data volumes. To perform several queries in parallel or to perform even a single query, resources must be planned carefully and the resulting quality-of-service (QoS) is lower than the best one. Typical QoS measures are the output delay and the amount of data in the stream used for the processing. In this paper, we introduce a model which allows to describe stream operators and the streams between the operators of an operator graph belonging to a stream query. The model allows us to calculate the resources consumed by a query graph given a certain result quality. Furthermore, it can be used to determine in advance if the quality-of-service requirement of a given query can be met with the actual available system resources. This model is the basis for building QoS-guaranteeing systems.