  A striking discovery in the field of network science is that the majority of
real networked systems have some universal structural properties. In generally,
they are simultaneously sparse, scale-free, small-world, and loopy. In this
paper, we investigate the second-order consensus of dynamic networks with such
universal structures subject to white noise at vertices. We focus on the
network coherence $H_{\rm SO}$ characterized in terms of the
$\mathcal{H}_2$-norm of the vertex systems, which measures the mean deviation
of vertex states from their average value. We first study numerically the
coherence of some representative real-world networks. We find that their
coherence $H_{\rm SO}$ scales sublinearly with the vertex number $N$. We then
study analytically $H_{\rm SO}$ for a class of iteratively growing networks --
pseudofractal scale-free webs (PSFWs), and obtain an exact solution to $H_{\rm
SO}$, which also increases sublinearly in $N$, with an exponent much smaller
than 1. To explain the reasons for this sublinear behavior, we finally study
$H_{\rm SO}$ for Sierpin\'ski gaskets, for which $H_{\rm SO}$ grows
superlinearly in $N$, with a power exponent much larger than 1. Sierpin\'ski
gaskets have the same number of vertices and edges as the PSFWs, but do not
display the scale-free and small-world properties. We thus conclude that the
scale-free and small-world, and loopy topologies are jointly responsible for
the observed sublinear scaling of $H_{\rm SO}$.
