Inference and labeling of metric-induced network topologies

The development and deployment of distributed network-aware applications and services require the ability to compile and maintain a model of the underlying network resources with respect to one or more characteristic properties of interest. To be manageable, such models must be compact; and to be ge...

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Bibliographic Details
Published in:IEEE transactions on parallel and distributed systems 2005-11, Vol.16 (11), p.1053-1065
Main Authors: Bestavros, A., Byers, J.W., Harfoush, K.A.
Format: Article
Language:English
Subjects:
Bandwidth
Bayesian probing
End-to-end measurement
Internet
Internet tomography
Jitter
Joining processes
Labeling
Loss measurement
Network servers
Network topology
packet-pair probing
performance evaluation
Resource management
Web server
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Summary:The development and deployment of distributed network-aware applications and services require the ability to compile and maintain a model of the underlying network resources with respect to one or more characteristic properties of interest. To be manageable, such models must be compact; and to be general-purpose, should enable a representation of properties along temporal, spatial, and measurement resolution dimensions. In this paper, we propose MINT - a general framework for the construction of such metric-induced models using end-to-end measurements. We present the basic theoretical underpinnings of MINT for a broad class of performance metrics, and describe PERISCOPE, a Linux embodiment of MINT constructions. We instantiate MINT and PERISCOPE for a specific metric of interest - namely, packet loss rates - and present results of simulations and Internet measurements that confirm the effectiveness and robustness of our constructions over a wide range of network conditions.
ISSN:1045-9219
1558-2183
DOI:10.1109/TPDS.2005.138