Alec Woo and David Culler

EECS Department
University of California, Berkeley
Technical Report No. UCB/CSD-03-1270
2003

http://www2.eecs.berkeley.edu/Pubs/TechRpts/2003/CSD-03-1270.pdf

Real-time wireless link reliability estimation is a fundamental building block for self-organization of multihop sensor networks. Observed connectivity at low-power is more chaotic and unpredictable than in wireless LANs, and available resources are severely constrained. We seek estimators that react quickly to large changes, yet are stable, have a small memory footprint and are simple to compute. We create a simple model that generates link loss characteristics similar to empirical traces collected under different contexts. With this model, we simulate a variety of estimators, and uses the simple exponentially weighted moving average (EWMA) estimator, as a basis for comparison. We find that recently propose flip-flop estimators are not superior. However, our cascaded EWMA on windowed averaging is very effective.

BibTeX citation:

@techreport{Woo:CSD-03-1270,
    Author = {Woo, Alec and Culler, David},
    Title = {Evaluation of Efficient Link Reliability Estimators for Low-Power Wireless Networks},
    Institution = {EECS Department, University of California, Berkeley},
    Year = {2003},
    URL = {http://www2.eecs.berkeley.edu/Pubs/TechRpts/2003/6239.html},
    Number = {UCB/CSD-03-1270},
    Abstract = {Real-time wireless link reliability estimation is a fundamental building block for self-organization of multihop sensor networks. Observed connectivity at low-power is more chaotic and unpredictable than in wireless LANs, and available resources are severely constrained. We seek estimators that react quickly to large changes, yet are stable, have a small memory footprint and are simple to compute. We create a simple model that generates link loss characteristics similar to empirical traces collected under different contexts. With this model, we simulate a variety of estimators, and uses the simple exponentially weighted moving average (EWMA) estimator, as a basis for comparison. We find that recently propose flip-flop estimators are not superior. However, our cascaded EWMA on windowed averaging is very effective.}
}

EndNote citation:

%0 Report
%A Woo, Alec
%A Culler, David
%T Evaluation of Efficient Link Reliability Estimators for Low-Power Wireless Networks
%I EECS Department, University of California, Berkeley
%D 2003
%@ UCB/CSD-03-1270
%U http://www2.eecs.berkeley.edu/Pubs/TechRpts/2003/6239.html
%F Woo:CSD-03-1270