  Most of the real world networks are complex as well as evolving. Therefore,
it is important to study the effect of network topology on the dynamics of
traffic and congestion in the network. To account this problem, we have
designed a time-varying network model where a new node will join a node in the
existing network with probability proportional to its degree and
disassortativity with its neighbors. Betweenness centrality (BC) plays an
important role to find the influential node and user's shortest route in the
network. As shortest route comprised of hub nodes and chances of congestion is
more on these nodes. Hence, BC-BC correlation is used to find user's route. A
connection between two hub nodes reduces the data forwarding capacity of
connecting link with higher probability. If a node shows disassortativity with
its neighbors then it may forward more packets and may be chosen for routing.
Furthermore, user's optimal data sending rate as well as critical packet
generation rate of the proposed model is calculated and shown improved results
in comparison than the classical scale-free network model.
