Real-Time Measurement of End-to-End Available Bandwidth using Kalman Filtering

This paper presents a new method, BART (bandwidth available in real-time), for estimating the end-to-end available bandwidth over a network path. It estimates bandwidth quasi-continuously, in real-time. The method has also been implemented as a tool. It relies on self-induced congestion, and repeatedly samples the available bandwidth of the network path with sequences of probe packet pairs, sent at randomized rates. BART requires little computation in each iteration, is lightweight with respect to memory requirements, and adds only a small amount of probe traffic. The BART method uses Kalman filtering, which enables real-time estimation (a.k.a. tracking). It maintains a current estimate, which is incrementally improved with each new measurement of the inter-packet time separations in a sequence of probe packet pairs. The measurement model has a strong non-linearity, and would not at first sight be considered suitable for Kalman filtering, but we show how this non-linearity can be handled. BART may be tuned according to the specific needs of the measurement application, such as agility vs. stability of the estimate. We have tested an implementation of BART in a physical test network with carefully controlled cross traffic, with good accuracy and agreement. Test measurements have also been performed over the Internet. We compare the performance of BART with that of pathChirp, a state-of-the-art tool for measuring end-to-end available bandwidth in real-time