  Results for estimating the convergence rate of non-stationary distributed
consensus algorithms are provided, on the basis of qualitative (mainly
topological) as well as basic quantitative information (lower-bounds on the
matrix entries). The results appear to be tight in a number of instances and
are illustrated through simple as well as more sophisticated examples. The main
idea is to follow propagation of information along certain spanning trees which
arise in the communication graph.
