  The interest in dynamic processes on networks is steadily rising in recent
years. In this paper, we consider the $(\alpha,\beta)$-Thresholded Network
Dynamics ($(\alpha,\beta)$-Dynamics), where $\alpha\leq \beta$, in which only
structural dynamics (dynamics of the network) are allowed, guided by local
thresholding rules executed in each node. In particular, in each discrete round
$t$, each pair of nodes $u$ and $v$ that are allowed to communicate by the
scheduler, computes a value $\mathcal{E}(u,v)$ (the potential of the pair) as a
function of the local structure of the network at round $t$ around the two
nodes. If $\mathcal{E}(u,v) < \alpha$ then the link (if it exists) between $u$
and $v$ is removed; if $\alpha \leq \mathcal{E}(u,v) < \beta$ then an existing
link among $u$ and $v$ is maintained; if $\beta \leq \mathcal{E}(u,v)$ then a
link between $u$ and $v$ is established if not already present.
  The microscopic structure of $(\alpha,\beta)$-Dynamics appears to be simple,
so that we are able to rigorously argue about it, but still flexible, so that
we are able to design meaningful microscopic local rules that give rise to
interesting macroscopic behaviors. Our goals are the following: a) to
investigate the properties of the $(\alpha,\beta)$-Thresholded Network Dynamics
and b) to show that $(\alpha,\beta)$-Dynamics is expressive enough to solve
complex problems on networks.
  Our contribution in these directions is twofold. We rigorously exhibit the
claim about the expressiveness of $(\alpha,\beta)$-Dynamics, both by designing
a simple protocol that provably computes the $k$-core of the network as well as
by showing that $(\alpha,\beta)$-Dynamics is in fact Turing-Complete. Second
and most important, we construct general tools for proving stabilization that
work for a subclass of $(\alpha,\beta)$-Dynamics and prove speed of convergence
in a restricted setting.
