In current IP-based networks, the application of window-based end-to-end flow control, including TCP, to ensure reliable flows is an essential factor. However, since such a flow control is provided by the end hosts, end-to-end control cannot be applied to decision-making in a time-scale shorter than the round-trip delay. We have previously proposed a diffusion-type flow control mechanism to realize the extremely time sensitive flow control that is required for high-speed networks. In this mechanism, each network node manages its own traffic only on the basis of the local information directly available to it, by using predetermined rules. The implementation of decision-making at each node can lead to optimal performance for the whole network. Our previous studies showed that the mechanism works well, by itself, in high-speed networks. However, to apply this mechanism to actual networks, it needs to be able to coexist with other existing protocols. In this paper, we investigate the performance of diffusion-type flow control coexisting with TCP. We show that diffusion-type flow control can coexist with TCP and the two can be complementary. Then, we show that a combination of both controls achieves higher network performance than TCP alone in high-speed networks.

We have previously proposed a diffusion-type flow control mechanism as a solution for severely time-sensitive flow control required for high-speed networks. In this mechanism, each node in a network manages its local traffic flow using the basis of only the local information directly available to it, by using predetermined rules. In addition, the implementation of decision-making at each node can lead to optimal performance for the whole network. Our previous studies show that our flow control mechanism with certain parameter settings works well in high-speed networks. However, to apply this mechanism to actual networks, it is necessary to clarify how to design a parameter in our control mechanism. In this paper, we investigate the range of the parameter and derive its optimal value enabling the diffusion-type flow control to work effectively.