DocumentCode :
2623297
Title :
Dynamic power management of WSN based on data stream grey forecasting
Author :
Feng, Youbing ; Wang, Xinfang
Author_Institution :
Sch. of Electron. & Inf., Jiangsu Univ. of Sci. & Technol., Zhenjiang, China
fYear :
2011
fDate :
27-29 June 2011
Firstpage :
3209
Lastpage :
3212
Abstract :
Due to the characteristics of limited computing capabilities and small storage of WSN node, a dynamic power management (DPM) method that can realize data stream forecasting based on the grey theory was proposed. Two working modes were established in terms of the different data receiving/sending cycle status of the node, combining the features that grey forecasting has strong adaptive ability and needs few samples and computation work, the model for forecasting the data stream between node and converged node was established to realize the dynamic switch of working modes and reduce the energy consumption on the communication between the WSN nodes. The grey forecasting of data stream on the basis of only 4 sample data is able to obtain the forecasting result of MSE=1.21%. The simulation analysis of nodes´ energy consumption indicates that this DPM method can save 67.9% of energy.
Keywords :
data handling; energy consumption; forecasting theory; grey systems; wireless sensor networks; WSN; data receiving-sending cycle; data stream grey forecasting; dynamic power management method; energy consumption; grey theory; wireless sensor networks; Computational modeling; Computers; Energy consumption; Forecasting; Predictive models; Wireless communication; Wireless sensor networks; data stream; dynamic power management; grey forecast; wireless sensor networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Science and Service System (CSSS), 2011 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-9762-1
Type :
conf
DOI :
10.1109/CSSS.2011.5974830
Filename :
5974830
Link To Document :
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