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Learning from Data Streams

Processing Techniques in Sensor Networks

João Gama editor Mohamed Medhat Gaber editor

Format:Paperback

Publisher:Springer-Verlag Berlin and Heidelberg GmbH & Co. KG

Published:19th Oct '10

Should be back in stock very soon

Learning from Data Streams 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.

ISBN: 9783642092855

Dimensions: unknown

Weight: unknown

244 pages

Softcover reprint of hardcover 1st ed. 2007