Adaptive data mining approach for flow redirection in multihomed mobile router

On multihomed mobile router with several interfaces toward Internet, it is important to provide an efficient flow redirection (FR) method that changes the served interface according to each network status or user movement. However, currently as the mobile devices roams, the interface is selected as only the physical signal strength, thus efficient resource use or quality of service (QoS) support is not guaranteed. In this paper, we propose an adaptive data mining approach that provides the selection of influential attributes for FR and the proper FR decision model as the interface type. We analyze assuming network protocols in order to heuristically extract the FR candidate attributes for estimating the required QoS. We abstract theoretically the FR influential attributes through decision-tree algorithm, and finally obtain the proper FR decision models per each interface. Our simulation results show that our FR approach provides improved performances in comparison with current handover.