NDLI: Impact of linear regression on time synchronization accuracy and energy consumption for Wireless Sensor Networks

Content Provider	IEEE Xplore Digital Library
Author	Liangping Ma Hua Zhu Nallamothu, G. Bo Ryu Zhensheng Zhang
Copyright Year	2008
Description	Author affiliation: Network Syst., Argon ST, Inc., San Diego, CA (Liangping Ma; Hua Zhu; Nallamothu, G.; Bo Ryu; Zhensheng Zhang)
Abstract	Linear regression is used in a number of time synchronization protocols to establish a linear relationship between clocks at different sensor nodes to achieve energy-efficient time synchronization. These protocols are predictive in the sense that a node predicts a target clock based on collected time stamp data. However, the use of linear regression for sensor network time synchronization has not been thoroughly studied in the literature. This paper attempts to close the gap by analyzing the impacts of two parameters on the precision of linear regression based time synchronization protocols: (1) the frequency at which the time stamp data are collected; (2) the window size, i.e., the number of time stamps used for linear regression. Through theoretical analysis, experiments and simulations, we show a counter-intuitive result: given the prediction interval, if the clock relationship varies slowly over time, more frequent synchronization results in worse synchronization precision. This result suggests that a linear regression based time synchronization protocol can achieve both high precision and good energy efficiency when operating at a low synchronization frequency. We also show that increasing the window size improves the synchronization performance but the synchronization uncertainty is bounded away from zero.
Starting Page	1
Ending Page	7
File Size	387626
Page Count	7
File Format	PDF
ISBN	9781424426768
DOI	10.1109/MILCOM.2008.4753563
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-11-16
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Linear regression Energy consumption Wireless sensor networks Frequency synchronization Protocols Clocks Energy efficiency Analytical models Predictive models Uncertainty
Content Type	Text
Resource Type	Article

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