By Topic

Dynamic power management of wireless sensor networks based on grey model

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Wei Hailong ; School of Mechatronics Engineering University of Electronic Science and Technology of China, Chendu, Sichuan, China ; Shen Yan ; Wei Tuming

The energy constraint of sensor nodes is the key factor that restrict the life of wireless sensor networks. So an effective method of dynamic power management (DPM) that based on grey model is proposed to make economical use of energy. Historical data collected of sensor node is used to predict the future value in this method, while the parameters are adjusted automatically in the process of prediction to realize the adaptive prediction. Compared with the algorithm of wavelet and AR, the accuracy of prediction is improved. The basic idea is to decide the working pattern of the entire sensor networks by the node of Sink, and in the next period sensor nodes do not send back data if their observed values are not out of threshold. To reduce energy consumption of the entire sensor networks by shortening the working hours and reducing transmitted messages between the nodes. Theory analysis and experiment result show that the method of this paper is effective not only in the predictive accuracy but also in the energy efficiency.

Published in:

2010 3rd International Conference on Advanced Computer Theory and Engineering(ICACTE)  (Volume:1 )

Date of Conference:

20-22 Aug. 2010