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Inference and labeling of metric-induced network topologies

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3 Author(s)
Bestavros, A. ; Dept. of Comput. Sci., Boston Univ., MA, USA ; Byers, J.W. ; Harfoush, K.A.

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.

Published in:

Parallel and Distributed Systems, IEEE Transactions on  (Volume:16 ,  Issue: 11 )

Date of Publication:

Nov. 2005

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