Resumen
High Throughput Satellite (HTS) systems aim to push data rates to the order of Terabit/s, making use of Extremely High Frequencies (EHF) or free-space optical (FSO) in the feeder links. However, one challenge that needs to be addressed is that the use of such high frequencies makes the feeder links vulnerable to atmospheric conditions, which can effectively disable channels at times or temporarily increases the bit error rates. One way to cope with the problem is to introduce site diversity and to forward the data through the gateways not affected, or at least less constrained, by adverse conditions. In this paper, a virtual network function (VNF) introduced through reinforcement learning defines a smart routing service for an HTS system. Experiments were conducted on an emulated ground-satellite system in CloudLab, testing a VNF implementation of the approach with software-defined networking virtual switches, which indicate the expected performance of the proposed method.