Performance Analysis of a DEKF for Available Bandwidth Measurement

The paper presents a characterisation analysis of a measurement algorithm based on a Discrete-time Extended Kalman Filter (DEKF), which has recently been proposed for the estimation and tracking of end-to-end available bandwidth. The analysis is carried out by means of simulations for different rates of variations of the available bandwidth and permits assessing the performance of the measurement algorithm for different values of the filter parameters, that is, the covariance matrixes of the measurement and process noise.

[1]  Daniel M. Batista,et al.  Performance Analysis of Available Bandwidth Estimation Tools for Grid Networks , 2009, CAMAD.

[2]  M. Y. Sanadidi,et al.  The probe gap model can underestimate the available bandwidth of multihop paths , 2006, CCRV.

[3]  Du Ling.  End-to-end available bandwidth measurement methodology , 2011 .

[4]  Koichi Asatani,et al.  A new estimation method using RTT for available bandwidth of a bottleneck link , 2013, The International Conference on Information Networking 2013 (ICOIN).

[5]  kc claffy,et al.  Bandwidth estimation: metrics, measurement techniques, and tools , 2003, IEEE Netw..

[6]  Andrea Bondavalli,et al.  Differential analysis of Operating System indicators for anomaly detection in dependable systems: An experimental study , 2016 .

[7]  Carey Williamson,et al.  Comparing Wired-side and Wireless-side WLAN Monitoring Techniques: A Case Study , 2007 .

[8]  Andrea Bondavalli,et al.  Resilient estimation of synchronisation uncertainty through software clocks , 2013, Int. J. Crit. Comput. Based Syst..

[9]  Manish Jain,et al.  End-to-end available bandwidth: measurement methodology, dynamics, and relation with TCP throughput , 2003, IEEE/ACM Trans. Netw..

[10]  Greg Welch,et al.  Welch & Bishop , An Introduction to the Kalman Filter 2 1 The Discrete Kalman Filter In 1960 , 1994 .

[11]  Manish Jain,et al.  End-to-end available bandwidth: measurement methodology, dynamics, and relation with TCP throughput , 2003, TNET.

[12]  Peter Steenkiste,et al.  Evaluation and characterization of available bandwidth probing techniques , 2003, IEEE J. Sel. Areas Commun..

[13]  M. Frans Kaashoek,et al.  A measurement study of available bandwidth estimation tools , 2003, IMC '03.

[14]  Michele Vadursi,et al.  A Kalman filtering based method for available bandwidth measurement , 2015, 2015 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) Proceedings.

[15]  Richard G. Baraniuk,et al.  Multifractal Cross-Traffic Estimation , 2000 .

[16]  Carey L. Williamson,et al.  Comparing Wired-side and Wireless-side WLAN Monitoring Techniques: A Case Study , 2007, 32nd IEEE Conference on Local Computer Networks (LCN 2007).

[17]  Nelson Luis Saldanha da Fonseca,et al.  Refining the estimation of the available bandwidth in inter-cloud links for task scheduling , 2014, 2014 IEEE Global Communications Conference.

[18]  Mohinder S. Grewal,et al.  Kalman Filtering: Theory and Practice , 1993 .

[19]  Jason Lee,et al.  The devil and packet trace anonymization , 2006, CCRV.

[20]  S. Suthaharan,et al.  Measuring Available Bandwidth: pathChirp's Chirp Train Structure Remodeled , 2008, 2008 Australasian Telecommunication Networks and Applications Conference.

[21]  Carey L. Williamson,et al.  A comparative analysis of web and peer-to-peer traffic , 2008, WWW.