A new in-network data reduction mechanism to gather data for mining wireless sensor networks

Author(s):  
Azzedine Boukerche ◽  
Samer Samarah
2013 ◽  
Vol 347-350 ◽  
pp. 1068-1073
Author(s):  
Wei Min Qi ◽  
Jie Xiao

In order to provide efficient and suitable services for users in a ubiquitous computing environment, many kinds of context information technologies have been researched. Wireless sensor networks are among the most popular technologies providing such information. Therefore, it is very important to guarantee the reliability of sensor data gathered from wireless sensor networks. However there are several factors associated with faulty sensor readings which make sensor readings unreliable. The research put forward classifying faulty sensor readings into sensor faults and measurement errors, then propose a novel in-network data calibration algorithm which includes adaptive fault checking, measurement error elimination and data refinement. The proposed algorithm eliminates faulty readings as well as refines normal sensor readings and increase reliability. The simulation study shows that the in-network data calibration algorithm is highly reliable and its network overhead is very low compared to previous works.


Author(s):  
David James McCorrie ◽  
Elena Gaura ◽  
Keith Burnham ◽  
Nigel Poole ◽  
Roger Hazelden

2012 ◽  
Vol 4 ◽  
pp. 32-37
Author(s):  
Jin Song Chen

This paper introduces the basics of wireless sensor networks, focusing on the concept of sensor network data collection, data collection mechanisms, data collection in-network data aggregation, data collection and data collection applications Research. This paper presents the data collection in WSN node scheduling concept, analyzed the two data collection in WSN scheduling mechanism, which is based on data collection interval node scheduling mechanism and turn the data based on perceived probability of node sleep scheduling mechanism.


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