Research On Application Of Kalman Filter In Bandwidth Measurement

Bandwidth measurement is very important in the field of network information. It plays a major role in the Qo S of network system management, congestion control and the routing access by measuring the largest amount of data of a link or a network path in the unit to transfer in the course of time. In 2006, Ekelin S and Nilsson M put forward the BART, which using Kalman filter method in the field of bandwidth measurement.While maintaining the high measuring accuracy, the BART improves the tracking performance of the changed environment. And it not only greatly reduces the computational power, but also expands the using conditions of the algorithm. In2008,the Probability-based Model ABEST, which uses the design of BART, extend the using of Kalman filter. However, the BART and ABEST just presents the method of Kalman filter in the context. It can’t be used in the other different link condition because of its parameter Settings ways.Now this paper presents a new adaptive filtering system according to the basis of the model, the theory, the experimental analysis of BART. It improves the measurement accuracy and tracking performance proved by the experiments. Then, this paper presents a new measurement “dynamic state equation” based on the probability-based model ABEST according to the standard state equation. By putting forward the double probe flow measurement strategy, It effectively improves the filtering performance. In the study of measuring the method based on the probability-based model IGI, the paper tries to combine the adaptive filtering and the dynamic state equation to make the Kalman Filter more stability and more practicability, so that it do not need the capacity C of bottleneck link while measuring more accuracy and faster.