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 ...
This paper describes our ongoing work developing the Stanford Stream Data Manager (STREAM), a system...
Deploying an infrastructure to execute queries on distributed data streams sources requires to ident...
Distributed Data Stream Management Systems (DSMS) are increasingly used for the processing of high-r...
Data stream systems have to deal with massive data volumes. To perform several queries in parallel o...
Data stream processing in the industrial as well as in the academic field has gained more and more i...
Quality-aware management of data streams is gaining more and more importance with the amount of data...
Data streams in the form of potentially unbounded sequences of tuples arise naturally in a large var...
Scalable stream processing systems have to continuously manage changing resources efficiently, which...
In this paper, we identify issues and present solutions developed – both theoretical and experimenta...
It is challenging for large-scale stream management systems to return always perfect results when pr...
Data streams processing is an emerging research area that is driven by the growing need for monitori...
The last decade witnessed a vast number of Big Data applications in the science and industry fields ...
Data stream processing systems (DSPSs) compute real-time queries over continuously changing streams ...
Processing data streams with Quality-of-Service (QoS) guarantees is an emerging area in existing str...
Resource management in Distributed Stream Processing Systems (DSPS) defines the way queries are depl...
This paper describes our ongoing work developing the Stanford Stream Data Manager (STREAM), a system...
Deploying an infrastructure to execute queries on distributed data streams sources requires to ident...
Distributed Data Stream Management Systems (DSMS) are increasingly used for the processing of high-r...
Data stream systems have to deal with massive data volumes. To perform several queries in parallel o...
Data stream processing in the industrial as well as in the academic field has gained more and more i...
Quality-aware management of data streams is gaining more and more importance with the amount of data...
Data streams in the form of potentially unbounded sequences of tuples arise naturally in a large var...
Scalable stream processing systems have to continuously manage changing resources efficiently, which...
In this paper, we identify issues and present solutions developed – both theoretical and experimenta...
It is challenging for large-scale stream management systems to return always perfect results when pr...
Data streams processing is an emerging research area that is driven by the growing need for monitori...
The last decade witnessed a vast number of Big Data applications in the science and industry fields ...
Data stream processing systems (DSPSs) compute real-time queries over continuously changing streams ...
Processing data streams with Quality-of-Service (QoS) guarantees is an emerging area in existing str...
Resource management in Distributed Stream Processing Systems (DSPS) defines the way queries are depl...
This paper describes our ongoing work developing the Stanford Stream Data Manager (STREAM), a system...
Deploying an infrastructure to execute queries on distributed data streams sources requires to ident...
Distributed Data Stream Management Systems (DSMS) are increasingly used for the processing of high-r...