End-to-end network performance estimation using signal complexity

This paper proposes to analyze end-to-end network performance as a signal. Traditionally, network performance is measured by specially designed active probes, which can be singular packets, packet pairs, or longer packet trains, where packet pairs and trains are the default methods for useful performance metrics like available bandwidth, bottleneck capacity, jitter, etc. Probing results are notoriously noisy. This paper shows that if probing data are treated as a signal and processed as such, precision can be improved. Real network experiments and analysis are conducted specifically for available bandwidth, but the fundamental approach can be applied to any performance metric.