A dynamic QoS management system with flow classification platform for software-defined networks

In the last decades, along with the continuously evolving of the Internet Protocol-based network, numerous Internet programs that have played critical roles in the current technological era are being developed inclusive of interactive applications. Nevertheless, the transmission performance and user experience of these instant services that require high bandwidth or low latency may suffer when serious traffic congestion occurs. In this paper, a QoS management system with a dynamic routing algorithm, based on a software-defined networking architecture, is implemented. The purpose of the system is to generate an optimal route with minimum cost based on real-time monitored statistics and the cost model. The system is also integrated with a flow classification engine based on machine learning algorithms to enable the application identification thus providing a bandwidth management mechanism that can enforce rate-limit policies for each application with different priorities under traffic congestion. Experimental results show that the proposed algorithm can provide excellent QoS with little overhead, where the rate-limit policies can be implemented in one to several seconds for different applications through the bandwidth management mechanism.