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Transactions on Large-Scale Data- and Knowledge-Centered Systems XI [electronic resource] :Special Issue on Advanced Data Stream Management and Continuous Query Processing /

Contributor(s): Hameurlain, Abdelkader [editor.] | Küng, Josef [editor.] | Wagner, Roland [editor.] | Amann, Bernd [editor.] | Lamarre, Philippe [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Lecture Notes in Computer Science: 8290Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.Description: X, 127 p. 37 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642452697.Subject(s): Computer science | Database management | Data mining | Computer Science | Database Management | Data Mining and Knowledge DiscoveryOnline resources: Click here to access online
Contents:
ASSIST: Access Controlled Ship Identification Streams -- The HIT Model: Workflow-Aware Event Stream Monitoring -- P-Bench: Benchmarking in Data-Centric Pervasive Application Development -- Efficient Mining of Lag Patterns in Evolving Time Series -- On the Power of the Adversary to Solve the Node Sampling Problem.
In: Springer eBooksSummary: This, the 11th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains five selected papers focusing on Advanced Data Stream Management and Processing of Continuous Queries. The contributions cover different methods for avoiding unauthorized access to streaming data, modeling complex real-time behavior of stream processing applications, comparing different event-centric and data-centric platforms for the development of applications in pervasive environments, capturing localized repeated associative relationships from multiple time series, and obtaining uniform and fresh sampling strategies over input data streams generated by large open systems containing malicious participants.
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ASSIST: Access Controlled Ship Identification Streams -- The HIT Model: Workflow-Aware Event Stream Monitoring -- P-Bench: Benchmarking in Data-Centric Pervasive Application Development -- Efficient Mining of Lag Patterns in Evolving Time Series -- On the Power of the Adversary to Solve the Node Sampling Problem.

This, the 11th issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems, contains five selected papers focusing on Advanced Data Stream Management and Processing of Continuous Queries. The contributions cover different methods for avoiding unauthorized access to streaming data, modeling complex real-time behavior of stream processing applications, comparing different event-centric and data-centric platforms for the development of applications in pervasive environments, capturing localized repeated associative relationships from multiple time series, and obtaining uniform and fresh sampling strategies over input data streams generated by large open systems containing malicious participants.

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