Extracting Kernel Dataset from Big Sensory Data in Wireless Sensor Networks

The amount of sensory data manifests an explosive growth due to the increasing popularity of Wireless Sensor Networks (WSNs). The scale of sensory data in many applications has already exceeded several petabytes annually, which is beyond the computation and transmission capabilities of conventional...

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Veröffentlicht in:	IEEE transactions on knowledge and data engineering Jg. 29; H. 4; S. 813 - 827
Hauptverfasser:	Cheng, Siyao, Cai, Zhipeng, Li, Jianzhong, Gao, Hong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.04.2017 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithm design and analysis Algorithms Big sensory data Complexity Complexity theory Computer simulation Correlation Correlation coefficients Datasets Distributed algorithms Exploding wires Kernel kernel dataset Kernels Polynomials Redundancy Remote sensors Sensors Set theory Wireless sensor networks
ISSN:	1041-4347, 1558-2191
Online-Zugang:	Volltext
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