  In this paper, we reveal the relationship between entropy rate and the
congestion in complex network and solve it analytically for special cases.
Finding maximizing entropy rate will lead to an improvement of traffic
efficiency, we propose a method to mitigate congestion by allocating limited
traffic capacity to the nodes in network rationally. Different from former
strategies, our method only requires local and observable information of
network, and is low-cost and widely applicable in practice. In the simulation
of the phase transition for various network models, our method performs well in
mitigating congestion both locally and globally. By comparison, we also uncover
the deficiency of former degree-biased approaches. Owing to the rapid
development of transportation networks, our method may be helpful for modern
society.
