Today's networks are becoming increasingly complex and the ability to effectively and efficiently operate and manage them is ever more challenging. Ways to provide end-to-end Quality of Service have to cope with the increasing heterogeneity of these networks, which is due to the several actors of current network scenarios, from access networks to end-user devices, from protocols to applications and operating systems. Exploiting such heterogeneity, in this paper we present an approach to the identification of each element composing an end-to-end path. Such identification is useful in several situations. For instance, it can improve the performance of adaptive and network-aware applications, it can help intelligent routing approaches, and it can be used in network and service overlay scenarios. Our approach, based on Bayesian classifiers, utilizes the measurements and off-line processing of three QoS parameters, that are delay, jitter, and packet loss. To illustrate the capabilitie...