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Inhaltsangabe: Data stream oriented applications are typically dealing with huge volumes of data. Storing data and performing off-line processing on this huge data set can be costly, time consuming and impractical. This work describes our research results while designing and implementing an efficient data management system for on-line and off-line processing of streaming data. We present major existing data stream processing engines, their internal architecture and how they compare to our platform, Global Sensor Network (GSN) middleware. In order to achieve high efficiency while processing large volumes of streaming data using window-based continuous queries, we present a set of optimization algorithms and techniques to intelligently group and process different types of continuous queries. Moreover we present an efficient query scheduling component which not only increases the performance at least by an order of magnitude but also, decreases the response time and memory requirements. Finally, we present techniques and algorithms to enable scalable delivery of streaming data for high data rate streams (e.g., Financial Ticks).

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Ali Salehi
Verlag: VDM Verlag 2010-04-28 (2010)
ISBN 10: 3639240758 ISBN 13: 9783639240757
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Buchbeschreibung VDM Verlag, 2010. Paperback. Buchzustand: Like New. Almost new condition. SKU:9783639240757-2-0-3. Buchnummer des Verkäufers 9783639240757-2-0-3

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Salehi, Ali
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Buchbeschreibung Buchzustand: New. Publisher/Verlag: VDM Verlag Dr. Müller | Systems Architecture, Algorithms and Implementation | Data stream oriented applications are typically dealing with huge volumes of data. Storing data and performing off-line processing on this huge data set can be costly, time consuming and impractical. This work describes our research results while designing and implementing an efficient data management system for on-line and off-line processing of streaming data. We present major existing data stream processing engines, their internal architecture and how they compare to our platform, Global Sensor Network (GSN) middleware. In order to achieve high efficiency while processing large volumes of streaming data using window-based continuous queries, we present a set of optimization algorithms and techniques to intelligently group and process different types of continuous queries. Moreover we present an efficient query scheduling component which not only increases the performance at least by an order of magnitude but also, decreases the response time and memory requirements. Finally, we present techniques and algorithms to enable scalable delivery of streaming data for high data rate streams (e.g., Financial Ticks). | Format: Paperback | Language/Sprache: english | 209 gr | 148 pp. Buchnummer des Verkäufers K9783639240757

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Buchbeschreibung VDM Verlag Apr 2010, 2010. Taschenbuch. Buchzustand: Neu. 219x150x18 mm. Neuware - Data stream oriented applications are typically dealing with huge volumes of data. Storing data and performing off-line processing on this huge data set can be costly, time consuming and impractical. This work describes our research results while designing and implementing an efficient data management system for on-line and off-line processing of streaming data. We present major existing data stream processing engines, their internal architecture and how they compare to our platform, Global Sensor Network (GSN) middleware. In order to achieve high efficiency while processing large volumes of streaming data using window-based continuous queries, we present a set of optimization algorithms and techniques to intelligently group and process different types of continuous queries. Moreover we present an efficient query scheduling component which not only increases the performance at least by an order of magnitude but also, decreases the response time and memory requirements. Finally, we present techniques and algorithms to enable scalable delivery of streaming data for high data rate streams (e.g., Financial Ticks). 148 pp. Englisch. Buchnummer des Verkäufers 9783639240757

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Buchbeschreibung VDM Verlag Apr 2010, 2010. Taschenbuch. Buchzustand: Neu. 219x150x18 mm. This item is printed on demand - Print on Demand Neuware - Data stream oriented applications are typically dealing with huge volumes of data. Storing data and performing off-line processing on this huge data set can be costly, time consuming and impractical. This work describes our research results while designing and implementing an efficient data management system for on-line and off-line processing of streaming data. We present major existing data stream processing engines, their internal architecture and how they compare to our platform, Global Sensor Network (GSN) middleware. In order to achieve high efficiency while processing large volumes of streaming data using window-based continuous queries, we present a set of optimization algorithms and techniques to intelligently group and process different types of continuous queries. Moreover we present an efficient query scheduling component which not only increases the performance at least by an order of magnitude but also, decreases the response time and memory requirements. Finally, we present techniques and algorithms to enable scalable delivery of streaming data for high data rate streams (e.g., Financial Ticks). 148 pp. Englisch. Buchnummer des Verkäufers 9783639240757

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Buchbeschreibung VDM Verlag Apr 2010, 2010. Taschenbuch. Buchzustand: Neu. 219x150x18 mm. Neuware - Data stream oriented applications are typically dealing with huge volumes of data. Storing data and performing off-line processing on this huge data set can be costly, time consuming and impractical. This work describes our research results while designing and implementing an efficient data management system for on-line and off-line processing of streaming data. We present major existing data stream processing engines, their internal architecture and how they compare to our platform, Global Sensor Network (GSN) middleware. In order to achieve high efficiency while processing large volumes of streaming data using window-based continuous queries, we present a set of optimization algorithms and techniques to intelligently group and process different types of continuous queries. Moreover we present an efficient query scheduling component which not only increases the performance at least by an order of magnitude but also, decreases the response time and memory requirements. Finally, we present techniques and algorithms to enable scalable delivery of streaming data for high data rate streams (e.g., Financial Ticks). 148 pp. Englisch. Buchnummer des Verkäufers 9783639240757

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Buchbeschreibung VDM Verlag, 2010. PAP. Buchzustand: New. New Book. Delivered from our UK warehouse in 3 to 5 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Buchnummer des Verkäufers LQ-9783639240757

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Salehi, Ali
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Buchbeschreibung VDM Verlag, 2016. Paperback. Buchzustand: New. PRINT ON DEMAND Book; New; Publication Year 2016; Not Signed; Fast Shipping from the UK. No. book. Buchnummer des Verkäufers ria9783639240757_lsuk

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Buchbeschreibung VDM Verlag, 2010. PAP. Buchzustand: New. New Book. Shipped from US within 10 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Buchnummer des Verkäufers I2-9783639240757

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Buchbeschreibung VDM Verlag Dr. Müller, 2010. Paperback. Buchzustand: New. book. Buchnummer des Verkäufers 3639240758

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