A control theoretic strategy for intelligent interface selection in heterogeneous network environments

With the diversity of wireless network accesses, new opportunities are offered to leverage network overload by wisely distributing traffic over the less congested networks. Following this observation, a number of studies have addressed the issue of the optimal interface selection to maximize the network performance. In order to address this problem, we propose, in this paper, a general model describing the interface selection process in heterogeneous network environments. The model is, then, used to derive a scalable controller, which can assist in steering dynamically the traffic to the most appropriate network access while blocking the residual traffic in a way to avoid the network congestion. In contrast with existing mechanisms, which generally rely on heuristic approaches, the proposed mechanism allows to compute network access probabilities based on linear optimal control theory. It also presents the advantage of a seamless integration with the Access Network Discovery and Selection Function (ANDSF). Simulation results sort out that the proposed scheme prevents the network congestion and demonstrates the effectiveness of the controller design, which can maximize the network resources' allocation by converging the network workload to the targeted network occupancy.