Abstract
Loss tomography, as a key component of network tomography, aims to obtain the loss rate of each link in a network by end-to-end measurement. If knowing the loss model of a link, we, in fact, deal with a parametric estimate problem with incomplete data. Maximum likelihood estimates are often used in this situation to identify the unknown parameters in the loss model. The estimation methods either rely on iterative approximation to identify the parameters or solve some high order simultaneous equations. Both require a long execution time, and the former also needs to consider how to avoid trap into a local maximum. In this paper, we propose an estimate that is based on the correlation between a link and its sibling brothers to identify the loss rate of the link. It, instead of using an iterative approach to approximate the maximum, employs a bottom-up approach to identify the loss rates of the links of a network.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Cáceres, R., Duffield, N., Horowitz, J., Towsley, D.: Multicast-based inference of network-internal loss characteristics. IEEE Trans. on Information Theory 45 (1999)
Coates, M., Hero, A., Nowak, R., Yu, B.: Internet tomography. IEEE Signal Processing Magazine 19 (2002)
The network simulator 2. Technical report, http://www.isi.edu/nsnam/ns2
Felix: Independent monitoring for network survivality. Technical report, ftp://ftp.bellcore.com/pub/mwg/felix/index.html
Ipma: Internet performance measurement and analysis. Technical report, http://www.merit.edu/ipma
Mahdavi, J., Paxson, V., Adams, A., Mathis, M.: Creating a scalable architecture for internet measurement. In: INET 1998 (1998)
Surveyor. Technical report, http://io.advanced.org/surveyor
Cáceres, R., Duffield, N., Moon, S., Towsley, D.: Inference of Internal Loss Rates in the MBone. In: IEEE/ISOC Global Internet 1999 (1999)
Cáceres, R., Duffield, N., Moon, S., Towsley, D.: Inferring link-level performance from end-to-end multicast measurements. Technical report, University of Massachusetts (1999)
Bu, T., Duffield, N., Presti, F., Towsley, D.: Network tomography on General Topologies. In: SIGCOMM 2002 (2002)
Harfoush, K., Bestavros, A., Byers, J.: Robust identification of shared losses using end-to-end unicast probes. In: Technical Report BUCS-2000-013, Boston University (2000)
Coates, M., Nowak, R.: Unicast network tomography using EM algorthms. Technical Report TR-0004, Rice University (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zhu, W., Geng, Z. (2004). A Fast Method to Estimate Loss Rate. In: Kahng, HK., Goto, S. (eds) Information Networking. Networking Technologies for Broadband and Mobile Networks. ICOIN 2004. Lecture Notes in Computer Science, vol 3090. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25978-7_48
Download citation
DOI: https://doi.org/10.1007/978-3-540-25978-7_48
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23034-2
Online ISBN: 978-3-540-25978-7
eBook Packages: Springer Book Archive