Title :
A Decentralized Quality Aware Adaptive Sampling Strategy in Wireless Sensor Networks
Author :
Masoum, A. ; Meratnia, N. ; Havinga, P.J.M.
Author_Institution :
Dept. of Comput. Sci., Univ. of Twente, Enschede, Netherlands
Abstract :
Since WSNs suffer from sever resource constraints, in terms of energy, memory and processing, temporal, spatial and spatio-temporal correlation among sensor data can be exploited by adaptive sampling approaches to find out an optimal sampling strategy, which reduces the number of sampling nodes and/or sampling rates while maintaining high data quality. In this paper, a quality aware decentralized adaptive sampling strategy is proposed which benefit from the data correlation for predicting future samples. In this algorithm, sensor nodes adjust their sampling rates, based on environmental conditions and user defined data range. Simulation results show that proposed approach provides 90 percentage event detection accuracy level while consumes lesser energy rather than existing adaptive sampling approach.
Keywords :
correlation methods; sampling methods; wireless sensor networks; WSN; data correlation; decentralized quality aware adaptive sampling strategy; energy correlation; environmental condition; event detection accuracy; memory correlation; processing correlation; resource constraint; sensor data quality; spatiotemporal correlation; wireless sensor network; Adaptation models; Correlation; Data models; Energy consumption; Predictive models; Quality of service; Resource management;
Conference_Titel :
Ubiquitous Intelligence & Computing and 9th International Conference on Autonomic & Trusted Computing (UIC/ATC), 2012 9th International Conference on
Conference_Location :
Fukuoka
Print_ISBN :
978-1-4673-3084-8
DOI :
10.1109/UIC-ATC.2012.156