Monitoring systems today often involve continuous queries over streaming data, in a distributed collaborative system. The distribution of query operators over a network of processors, and their processing sequence, form a query configuration with inherent constraints on the throughput it can support. In this paper we propose to optimize stream queries with respect to a version of throughput measure, the profiled input throughput. This measure is focused on matching the expected behavior of the input streams. To prune the search space we used hill-climbing techniques that proved to be efficient and effective.

Maximizing the sustained throughput of distributed continuous queries

Palpanas, Themistoklis;
2006-01-01

Abstract

Monitoring systems today often involve continuous queries over streaming data, in a distributed collaborative system. The distribution of query operators over a network of processors, and their processing sequence, form a query configuration with inherent constraints on the throughput it can support. In this paper we propose to optimize stream queries with respect to a version of throughput measure, the profiled input throughput. This measure is focused on matching the expected behavior of the input streams. To prune the search space we used hill-climbing techniques that proved to be efficient and effective.
2006
Proceedings of the 2006 ACM CIKM International Conference on Information and Knowledge Management, Arlington, Virginia, USA, November 6-11, 2006. ACM 2006,
New York, N.Y.
ACM
1595934332
I., Stanoi; G., Mihaila; Palpanas, Themistoklis; C., Lang
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/77885
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