A Flow Redirection Decision Mechanism using Data Mining on NEMO Environments

As constructing ubiquitous environment, the various researches for the integration of heterogeneous networks are now under way. Multihoming is one of important issues in these researches to provide effective mobility. In order to support high quality service and seamless connectivity, it is necessary to provide an efficient FR (Flow Redirection) for the integrated network. Especially, mobile router with multiple interfaces should decide FR based on network condition for the efficient use of resources. In this paper, we propose a FR decision mechanism on mobile network (NEMO) via combined data mining technologies with multiple attributes presenting network condition. We assume that the mobile router has WLAN and WiBro interface toward Internet. At first, in order to heuristically choose candidate attributes, we analyze the WLAN/WiBro specification documents [5][6] and the considered QoS parameters in these networks. Then, we apply various data obtaining from QualNet [12] in various cases to decision tree algorithm, in order to theoretically select the influential attributes in FR decision. Finally, we acquire a FR decision model through the neural network with data for chosen attributes. Our simulation results show that our FR can provide the improved performances in comparison with current handover using only signal strength.