  Random linear network coding (RLNC) unicast protocol is analyzed over a
rapidly-changing network topology. We model the probability mass function (pmf)
of the dissemination time as a sequence of independent geometric random
variables whose success probability changes with every successful reception of
an innovative packet. We derive a tight approximation of the average networked
innovation probability conditioned on network dimension increase. We show
through simulations that our approximations for the average dissemination time
and its pmf are tight. We then propose to use a RLNC-based broadcast
dissemination protocol over a general dynamic topology where nodes are chosen
for transmission based on average innovative information that they can provided
to the rest of the network. Simulation results show that information
disseminates considerably faster as opposed to standard RLNC algorithm where
nodes are chosen uniformly at random.
