This work is devoted to the issue of monitoring of distributed real-time systems. In particular, it focuses on formal aspects of model-based supervision and problems which are related to it. In its first part, we present the basic properties of two well-known formal models used to model distributed systems: networks of timed automata and time Petri nets. We show that the behavior of these models can be represented with so-called branching processes. We also introduce the key conceptual elements of the supervisory system. The second part of the work is dedicated to the issue of constrained unfoldings which enable us to track causal relationships between events in a distributed system. This type of structure can be used to reproduce processes of the system on the basis of a completely unordered set of previously observed events. Moreover, we show that time constraints imposed on a system and observations submitted to the supervisory system can significantly affect a course of events in the system. We also raise the issue of parameters in time constraints. The proposed methods are illustrated with case studies. The third part of the work deals with the issue of unobservable cyclical behaviors in distributed systems. This type of behaviors leads to an infinite number of events in constrained unfoldings. We explain how we can obtain a finite structure that stores information about all observed events in the system, even if this involves processes that are infinite due to such unobservable loops. The fourth and final part of the work is dedicated to implementation issues of the previously described methods.