Abstract

In the field of network monitoring and measurement, the efficiency and accuracy of the adopted tools is strongly dependent on (i) structural and dynamic characteristics of the network scenario under measurement and (ii) on manual fine tuning of the involved parameters. This is, for example, the case of the end-to-end available bandwidth estimation, in which the constraints of the measurement stage vary according to the use of the final results. In this work, we present UANM (unified architecture for network measurement), a novel measurement infrastructure for the automatic management of measurement stages, tailored to the end-to-end available bandwidth estimation tools. We describe in detail its architecture, illustrating the features we introduced to mitigate the problems affecting available bandwidth estimation in heterogeneous scenarios. To provide evidences of UANM benefits, we present an experimental validation in three selected scenarios deployed over a real network testbed to (i) quantify the overhead introduced by the use of UANM, (ii) show how UANM is able to alleviate the interferences among concurrent measurements, and (iii) illustrate how UANM is capable to provide more accurate results thanks to the knowledge of the network environment. Finally, for the first time in literature, we provide a “fair comparison” of eight available bandwidth estimations tools in terms of accuracy, probing time, and intrusiveness.

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