DocumentCode
533291
Title
Source coding technique for energy efficient IEEE 802.15.4 wireless sensor networks
Author
Mohorko, Joze ; Pesovic, Uros ; Planinsic, Peter ; Cucej, Zarko
Author_Institution
Fac. of Electr. Eng., Comput. Sci. & Inf., Univ. of Maribor, Maribor, Slovenia
fYear
2010
fDate
23-25 Sept. 2010
Firstpage
71
Lastpage
75
Abstract
One of the main issues in wireless sensor networks is energy efficiency. Most of the energy is used for wireless transmission. To reduce an amount of data being sent, if a particular compression algorithm is used, than it can significantly reduce a power consumption and increase node´s operating lifetime. Presented in this paper is a research, in which the possibility of use of IEEE 802.15.4 wireless sensor networks in electrocardiogram (ECG) monitoring applications is analyzed. ECG signal, measured from a patient heart, is in the first step compressed that uses Autoregressive (AR) predictive coding and then again, using Huffman´s entropy coding. It has been studied, through the use of simulations, how reduction in data rate of compressed data will affect node´s average power consumption. The results obtained from data compression of ECG signal show that sufficient energy saving can be achieved.
Keywords
autoregressive processes; data compression; electrocardiography; personal area networks; source coding; wireless sensor networks; ECG signal; Huffman entropy coding; autoregressive predictive coding; data compression; electrocardiogram monitoring applications; energy efficient IEEE 802.15.4 wireless sensor networks; energy saving; power consumption; source coding technique; wireless transmission; Data compression; Data models; Electrocardiography; Encoding; Power demand; Wireless communication; Wireless sensor networks;
fLanguage
English
Publisher
ieee
Conference_Titel
Software, Telecommunications and Computer Networks (SoftCOM), 2010 International Conference on
Conference_Location
Split, Dubrovnik
Print_ISBN
978-1-4244-8663-2
Electronic_ISBN
978-953-290-004-0
Type
conf
Filename
5623648
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