NDLI: A methodology to optimize query in wireless sensor networks using historical data

Content Provider	Springer Nature Link
Author	Malik, Haroon Malik, Ahsan Samad Roy, Chanchal K.
Copyright Year	2011
Abstract	In wireless sensor networks (WSN), a query is commonly used for collecting periodical data from the objects under monitoring. Amount of sensory data drawn across WSNs by a query can significantly impact WSN’s power consumption and its lifetime, since WSNs are battery operated. We present a novel methodology to construct an optimal query containing fewer sensory attributes as compared to a standard query, thereby reducing the sensory traffic in WSN. Our methodology employees a statistical technique, principal component analysis on historical traces of sensory data to automatically identify important attributes among the correlated ones. The optimal query containing reduced set of sensory attributes, guarantees at least 25% reduction in energy consumption of WSN with respect to a standard query. Furthermore, from reduced set of data reported by optimal query, the methodology synthesizes complete set of sensory data at a base station (reporting unit with surplus power supply). We validated the effectiveness of our methodology with real world sensor data. The result shows that our methodology can synthesize complete set of sensory data analogues to standard query with 93% accuracy.
Starting Page	227
Ending Page	238
Page Count	12
File Format	PDF
ISSN	18685137
Journal	Journal of Ambient Intelligence and Humanized Computing
Volume Number	2
Issue Number	3
e-ISSN	18685145
Language	English
Publisher	Springer-Verlag
Publisher Date	2011-06-11
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Wireless sensor network Data reduction Principal component analysis Artificial Intelligence (incl. Robotics) Robotics and Automation User Interfaces and Human Computer Interaction Computational Intelligence
Content Type	Text
Resource Type	Article
Subject	Computer Science

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