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Synopsis
Learning from Data Streams Provides the reader with an overview of stream data processing, including prototype implementations like the Nile system and the TinyOS operating system. Full description
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From the Back Cover
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.
"About this title" may belong to another edition of this title.
- PublisherSpringer
- Publication date2007
- ISBN 10 3540736786
- ISBN 13 9783540736783
- BindingHardcover
- LanguageEnglish
- Number of pages254
- EditorGama João, Gaber Mohamed Medhat
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Learning from Data Streams : Processing Techniques in Sensor Networks
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Springer Berlin / Heidelberg, 2007
ISBN 10: 3540736786
ISBN 13: 9783540736783
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Learning from Data Streams : Processing Techniques in Sensor Networks
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ISBN 10: 3540736786
ISBN 13: 9783540736783
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