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Learning from Data Streams -

Learning from Data Streams

Processing Techniques in Sensor Networks
Buch | Softcover
X, 244 Seiten
2010 | 1. Softcover reprint of hardcover 1st ed. 2007
Springer Berlin (Verlag)
978-3-642-09285-5 (ISBN)
CHF 149,75 inkl. MwSt
Processing data streams has raised new research challenges over the last few years. This book provides the reader with a comprehensive overview of stream data processing, including famous prototype implementations like the Nile system and the TinyOS operating system. Applications in security, the natural sciences, and education are presented. The huge bibliography offers an excellent starting point for further reading and future research.

Sensor networks consist of distributed autonomous devices that cooperatively monitor an environment. Sensors are equipped with capacities to store information in memory, process this information and communicate with their neighbors. Processing data streams generated from wireless sensor networks has raised new research challenges over the last few years due to the huge numbers of data streams to be managed continuously and at a very high rate.

The book provides the reader with a comprehensive overview of stream data processing, including famous prototype implementations like the Nile system and the TinyOS operating system. The set of chapters covers the state-of-art in data stream mining approaches using clustering, predictive learning, and tensor analysis techniques, and applying them to applications in security, the natural sciences, and education.

This research monograph delivers to researchers and graduate students the state of the art in data stream processing in sensor networks. The huge bibliography offers an excellent starting point for further reading and future research.

Processing data streams generated from wireless sensor networks has raised new research challenges over the last few years due to the huge numbers of data streams to be managed continuously and at a very high rate. This book provides the reader with a comprehensive overview of stream data processing, including famous prototype implementations like the Nile system and the TinyOS operating system. The set of chapters covers the state-of-the-art in data stream mining approaches using clustering, predictive learning, and tensor analysis techniques, and applying them to applications in security, the natural sciences, and education. This research monograph delivers to researchers and graduate students the state-of-the-art in data stream processing in sensor networks. The huge bibliography offers an excellent starting point for further reading and future research.

Overview.- Sensor Networks: An Overview.- Data Stream Processing.- Data Stream Processing in Sensor Networks.- Data Stream Management Techniques in Sensor Networks.- Data Stream Management Systems and Architectures.- Querying of Sensor Data.- Aggregation and Summarization in Sensor Networks.- Sensory Data Monitoring.- Mining Sensor Network Data Streams.- Clustering Techniques in Sensor Networks.- Predictive Learning in Sensor Networks.- Tensor Analysis on Multi-aspect Streams.- Applications.- Knowledge Discovery from Sensor Data for Security Applications.- Knowledge Discovery from Sensor Data For Scientific Applications.- TinyOS Education with LEGO MINDSTORMS NXT.

Erscheint lt. Verlag 19.10.2010
Zusatzinfo X, 244 p. 73 illus.
Verlagsort Berlin
Sprache englisch
Maße 155 x 235 mm
Gewicht 400 g
Themenwelt Mathematik / Informatik Informatik Datenbanken
Schlagworte Architectures • Clustering • Data Stream Processing • Information • Knowledge Discovery • learning • LEGO MINDSTORMS • Memory • Mindstorms • Monitor • Predictive Learning • Sensor Data • sensor networks • Tensor Analysis • TinyOS • wireless sensor network • wireless sensor networks
ISBN-10 3-642-09285-3 / 3642092853
ISBN-13 978-3-642-09285-5 / 9783642092855
Zustand Neuware
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