Article

Change detection and estimation for network-measurement applications

Authors:

Erik Hartikainen,

Johan M. KarlssonAuthors Info & Claims

PM2HW2N '07: Proceedings of the 2nd ACM workshop on Performance monitoring and measurement of heterogeneous wireless and wired networks

Pages 1 - 10

https://doi.org/10.1145/1298275.1298277

Published: 22 October 2007 Publication History

Abstract

This paper presents a method for improving filter-based network-state estimation by adding detection and estimation of sudden changes in the system state. This can be of benefit in various contexts, e.g. in network management and adaptive streaming applications. In particular, it is shown that the performance of available-bandwidth estimation can be significantly enhanced by employing change detection in conjunction with a filter-based estimator. The use of filtering makes it feasible to track the communication network state and to estimate selected properties in real-time. In addition, filter-based methods may be combined with change detection in order to overcome the trade-off regarding stable estimation versus speed of adaptation to change. We discuss filtering and change detection in general, and present the novel approach of combining the filter-based available-bandwidth estimator BART with the Generalized Likelihood Ratio (GLR) change-detection test, which estimates both the time and magnitude of changes.

References

[1]

S. Ekelin, M. Nilsson, E. Hartikainen, A. Johnsson, J.-E. Mångs, B. Melander, and M. Björkman. Real-time measurement of end-to-end available bandwidth using Kalman filtering. In Proceedings of the 10th IEEE/IFIP Network Operations and Management Symposium, 2006.

[2]

V. Ribeiro, R. Riedi, G. Baraniuk, J. Navratil, and L. Cottrell. pathChirp: efficient available bandwidth estimation for network paths. In Proceedings of the Passive and Active Measurement Workshop, 2003.

[3]

M. Jain and C. Dovrolis. Pathload: a measurement tool for end-to-end available bandwidth. In Proceedings of the Passive and Active Measurement Workshop, 2002.

[4]

J. Navratil and R.L. Cottrell. Abwe: a practical approach to available bandwidth estimation. In Proceedings of the Passive and Active Measurement Workshop, 2003.

[5]

R. Carter and M. Crovella. Measuring Bottleneck Link Speed in Packet-Switched Networks. Technical Report 96-006, Boston University, 1996.

Digital Library

[6]

N. Hu and P. Steenkiste. Evaluation and characterization of available bandwidth probing techniques. IEEE JSAC Internet and WWW Measurement, Mapping, and Modeling, 2003.

Digital Library

[7]

G. Jin, G. Yang, B.R. Crowley, and D. A. Agarwal. Network Characterization Service (NCS). Lawrence Berkely National Lab Report 47892, 2001.

[8]

J. Strauss, D. Katabi, and F. Kaashoek. A measurement study of available bandwidth estimation tools. In Proceedings of the ACM SIGCOMM Internet Measurement Conference, 2003.

Digital Library

[9]

B. Melander, M. Björkman, and P. Gunningberg. A new end-to-end probing and analysis method for estimating bandwidth bottlenecks. In Proceedings of the IEEE Global Telecommunications Conference, 2000.

[10]

E. S. Page. Continuous inspection schemes. Biometrika, vol. 41, 1954.

[11]

U. Appel and A. V. Brandt. Adaptive sequential segmentation of piecewise stationary time series. Information Sciences, vol. 29, 1983.

[12]

M. Basseville and A. Benveniste. Design and comparative study of some sequential jump detection algorithms for digital signals. IEEE Transactions on Acoustics, Speech and Signal Processing, vol. 31, 1983.

[13]

A. S. Willsky and H. L. Jones. A generalized likelihood ratio approach to the detection and estimation of jumps in linear systems. IEEE Transactions on Automatic Control, vol. 21, 1976.

[14]

F. Gustafsson. The marginalized likelihood ratio test for detecting abrupt changes. IEEE Transactions on Automatic Control, vol. 1, 1996.

[15]

F. Gustafsson. A comparative study on change detection for some automotive applications. In Proceedings of the European Control Conference, 1997.

[16]

E. Hartikainen and S. Ekelin. Enhanced network-state estimation using change detection. In Proceedings of the 31st IEEE Conference on Local Computer Networks, 2006.

[17]

G. Bishop and G. Welch. An introduction to the Kalman filter. SIGGRAPH, Course 8, 2001.

[18]

F. Gustafsson. Adaptive Filtering and Change Detection. John Wiley & Sons, Ltd, 2000.

[19]

E. Hartikainen and S. Ekelin. Tuning the temporal characteristics of a Kalman-filter method for end-to-end bandwidth estimation. In Proceedings of the 4th IEEE/IFIP Workshop on End-to-End Monitoring Techniques and Services, 2006.

Cited By

Casolari SColajanni MPresti F(2009)Runtime state change detector of computer system resources under non stationary conditions2009 IEEE International Symposium on Modeling, Analysis & Simulation of Computer and Telecommunication Systems10.1109/MASCOT.2009.5366607(1-10)Online publication date: Sep-2009
https://doi.org/10.1109/MASCOT.2009.5366607
Bergfeldt EEkelin SKarlsson J(2009)Real-time available-bandwidth estimation using filtering and change detectionComputer Networks: The International Journal of Computer and Telecommunications Networking10.1016/j.comnet.2009.05.01153:15(2617-2645)Online publication date: 1-Oct-2009
https://dl.acm.org/doi/10.1016/j.comnet.2009.05.011

Index Terms

Change detection and estimation for network-measurement applications
1. Networks
  1. Network services
    1. Network monitoring

Recommendations

Real-time available-bandwidth estimation using filtering and change detection

This paper presents a filter-based method BART (Bandwidth Available in Real-Time) for real-time estimation of end-to-end available bandwidth in packet-switched communication networks. BART relies on self-induced congestion, and repeatedly samples the ...
A new FIR filter for state estimation and its application

This paper proposes a new FIR (finite impulse response) filter under a least squares criterion using a forgetting factor. The proposed FIR filter does not require information of the noise covariances as well as the initial state, and has some inherent ...
Kalman Estimation of Single-Tone Parameters and Performance Comparison With MAP Estimator

By incorporating a priori knowledge via the a priori probability density function of the frequency and phase, the Kalman estimator for linear, minimum mean-square error estimation of these single-tone parameters in additive, white, Gaussian noise is ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

PM2HW2N '07: Proceedings of the 2nd ACM workshop on Performance monitoring and measurement of heterogeneous wireless and wired networks

October 2007

144 pages

ISBN:9781595938053

DOI:10.1145/1298275

Co-chair:
Richard Werner Nelem Pazzi
University of Ottawa, Ottawa, Canada
,
General Chair:
Mohamed Ould-Khaoua
University of Glasgow, UK
,
Program Chair:
Blanca Caminero
University of Castilla-La Mancha, Spain

Copyright © 2007 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 October 2007

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Article

Conference

MSWiM07

Sponsor:

MSWiM07: 10th International Symposium on Modeling, Analysis and Simulation of Wireless and Mobile Systems

October 22, 2007

Crete Island, Chania, Greece

Acceptance Rates

Overall Acceptance Rate 74 of 226 submissions, 33%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

2
Total Citations
View Citations
230
Total Downloads

Downloads (Last 12 months)2
Downloads (Last 6 weeks)0

Reflects downloads up to 16 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

Casolari SColajanni MPresti F(2009)Runtime state change detector of computer system resources under non stationary conditions2009 IEEE International Symposium on Modeling, Analysis & Simulation of Computer and Telecommunication Systems10.1109/MASCOT.2009.5366607(1-10)Online publication date: Sep-2009
https://doi.org/10.1109/MASCOT.2009.5366607
Bergfeldt EEkelin SKarlsson J(2009)Real-time available-bandwidth estimation using filtering and change detectionComputer Networks: The International Journal of Computer and Telecommunications Networking10.1016/j.comnet.2009.05.01153:15(2617-2645)Online publication date: 1-Oct-2009
https://dl.acm.org/doi/10.1016/j.comnet.2009.05.011

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Table of Conten