To alleviate the congestion of traditional data center network, the flow scheduling cost based congestion control routing algorithm on Software Defined Network (SDN) architecture was proposed. Firstly, the maximum flows and minimum flows on congestion links were differentiated. Secondly, the cost of each equivalent route for maximum flows was calculated, and the routes with minimum cost were selected as available scheduling routes for maximum flows. Then, the flow scheduling cost of each available scheduling route was defined by considering the cost change of rerouting operation and the occupancy ratio of bandwidth together. Finally, the maximum flows with minimum scheduling cost were scheduled to related available scheduling routes. The experimental results show that, the proposed algorithm is qualified to reduce the load of congestion links when network congestion occurs. Moreover, compared with the previous congestion control algorithm which taking into account the flow route selection only, the proposed algorithm improves the link utilization and reduces the transmission time of flow, which make the network link resources to be better used.

A distributed strategy based on Stackelberg game was proposed to allocate cooperative power for cooperative networks. A Stackelberg game model was built at first, and the source node decided the price according to the cooperative power. Considering the relay's available resources, channel state, location and the price determined by source node, the relay node allocated the cooperative power to construct a user utility function. Then, the utility function was demonstrated to satisfy the conditions of concave function to ensure the existence of equilibrium. Subsequently, each node maximized its utility by finding the Stackelberg Equilibrium (SE) of optimum power and price. Finally, the simulation results proved the existence of equilibrium point, and the node's price, cooperative power and each node's utility were analyzed when the source node was in a different position. In the experiments, the cooperative power and price of the closer user respectively were 1.29 times and 1.37 times of the farther user. The experimental results show that the proposed strategy is effective, and it can be used in cooperative network and some other distributed networks.