  This paper presents distributed algorithmic solutions that employ
opportunistic inter-agent communication to achieve dynamic average consensus.
In our solutions each agent is endowed with a local criterion that enables it
to determine whether to broadcast its state to its neighbors. Our starting
point is a continuous-time distributed coordination strategy that, under
continuous-time communication, achieves practical asymptotic tracking of the
dynamic average of the time-varying agents' reference inputs. Then, for this
algorithm, depending on the directed or undirected nature of the time-varying
interactions and under suitable connectivity conditions, we propose two
different distributed event-triggered communication laws that prescribe agent
communications at discrete time instants in an opportunistic fashion. In both
cases, we establish positive lower bounds on the inter-event times of each
agent and characterize their dependence on the algorithm design parameters.
This analysis allows us to rule out the presence of Zeno behavior and
characterize the asymptotic correctness of the resulting implementations.
Several simulations illustrate the results.
