Paper Info
Title
Energy-Efficient Data Collection Scheme for Environmental Quality Management in Buildings.
Abstract
How to efficiently collect sensory data for supporting energy-efficient operation of buildings has become a great challenge, especially for large-scale networks in buildings. In this paper, a spatio-temporal compression-based optimized clustering scheme is proposed for energy-efficient environmental data collection in buildings. In the scheme,first, according to the establishment of a cluster, an adaptive dynamic cluster head selection method for prolonging the lifetime of sensory nodes in buildings is developed. Meanwhile, to further reduce energy consumption, we construct the dynamic optimal quantity of the cluster heads solution method to achieve minimum energy consumption. Moreover, the spatio-temporal correlations of sensory data are explored in the data sampling and transmission processes, which can decrease the amount of data transmission and further extend the lifetime of the entire data collection network. The proposed scheme provides sensing data with high quality for environmental quality management in buildings and supports energy-efficient building operation. Finally, the simulation results show that the proposed scheme obtains obvious advantages in energy consumption compared with other related schemes, and the lifetime of the proposed scheme is also longer than others when it maintains high reconstruction precision.
Year
DOI
Venue
2018
10.1109/ACCESS.2018.2873789
IEEE ACCESS
Keywords
Field
DocType
Data collection,clustering,spatio-temporal compression,energy consumption,buildings
Data collection,Data transmission,Computer science,Efficient energy use,Real-time computing,Environmental data,Cluster analysis,Wireless sensor network,Energy consumption,Quality management,Distributed computing
Journal
Volume
ISSN
Citations 
6
2169-3536
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Siguang Chen16312.91
Jiasheng Zhou200.34
Xiaoyao Zheng371.83
Xiukai Ruan4171.66