A smart VPN bonding technique based on rtt analisys and neural network prediction

Internet mobile networks are not designed to support the real-time data traffic due to many factors as resource sharing, traffic congestion, radio link, coverage, etc., which affect the Quality of Experience (QoE). A possible solution to improve the QoS in mobility scenarios, is given by the “Smart VPN Bonding” technique, which is based on aggregation of two or more internet mobile accesses and is able to provide a higher end-to-end available bandwidth due to an adaptive load balancing algorithm. In this paper, in order to dynamically establish the correct load balancing weights of the smart VPN bonder, a neural network approach to predict the main Key Performance Indicators (KPIs) values in a determinate geographical point is proposed. More specifically, the paper investigates the relation between the Round Trip Time (RTT) and the end-to-end available bandwidth (upload and download) in order to simplify and speed up the estimation bandwidth process.