Paper Info
Title
An Approximate Data Collection Algorithm in Space-Based Internet of Things.
Abstract
Space-based Internet of Things (S-IoT) is an important way to realize the real interconnection of all things because of its global coverage, infrastructure independence and strong resistance to destruction. In the S-IoT, a large amount of sensory data needs to be transmitted through a space-based information network with severely limited resources, which poses a great challenge to data collection. Therefore, this paper proposes an approximate data collection algorithm for the S-IoT, namely the sampling-reconstruction (SR) algorithm. The SR algorithm only collects the sensory data of some nodes, and then reconstructs the unacquired sensory data by leveraging the spatio-temporal correlation between sensory data, thereby reducing the amount of data that needs to be transmitted. We evaluated the performance of SR algorithm using real weather data set. The experimental results show that the SR algorithm can effectively reduce the amount of data collected under the condition of satisfying required data collection accuracy.
Year
DOI
Venue
2019
10.1007/978-3-030-24900-7_14
SpaCCS Workshops
Field
DocType
Citations 
Spectral clustering,Data collection,Computer science,Internet of Things,Algorithm,Weather data,Interconnection
Conference
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Changjiang Fei100.34
Baokang Zhao221.37
Wanrong Yu36719.19
Chunqing Wu431.27