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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 measure 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 an automatic management of measurement stages, tailored to the end-to-end available bandwidth estimation tools. We describe in details its architecture, illustrating the features we introduced to mitigate the problems affecting available bandwidth estimation in heterogeneous scenarios. Moreover, to provide evidences of UANM benefits, we present an experimental validation in three selected scenarios deployed over a real network testbed: (i) we show how UANM is able to alleviate the interferences among concurrent measures; (ii) we quantify the overhead introduced by the use of UANM; (iii) we illustrate how UANM is capable to provide more accurate results thanks to the knowledge of the network environment.