Real-time measurement of end-to-end available bandwidth using Kalman filtering

Ekelin, Svante and Nilsson, Martin and Hartikainen, Erik and Johnsson, Andreas and Mångs, Jan-Erik and Melander, Bob and Björkman, Mats (2006) Real-time measurement of end-to-end available bandwidth using Kalman filtering. In: 10th IEEE/IFIP Network Operations and Management Symposium (NOMS 2006), 3-7 April 2006, Vancouver, Canada.

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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 probes the network path with trains of probe packets, sent at randomized rates. BART requires little computation in each iteration, is light-weight with respect to memory requirements, and adds only a small amount of probe traffic. The BART method is based on Kalman filtering, which enables real-time estimation (a.k.a. tracking) with optimum performance under general conditions. It maintains a current estimate, which is incrementally improved with each new measurement of the inter-packet time separations in a probe packet train. 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, and the desired time-scale on which to track traffic fluctuations. We have tested 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.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:available bandwidth, measurement, probing, end-to-end, real-time, Kalman filter
ID Code:422
Deposited By:IAM Researcher
Deposited On:16 Apr 2008
Last Modified:18 Nov 2009 15:56

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