Evaluation of Efficient Link Reliability Estimators for Low-Power Wireless Networks

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.