A dynamic bandwidth resource allocation based on neural networks in euroskyway multimedia satellite system

Advanced traffic management based on the Dynamic Resource Assignment allows a broadband satellite system such as EuroSkyWay (ESW) to dynamically assign the resources of connections. The mechanisms of the dynamic assignment exploit variations of Burstiness exhibited by real time and non real time Variable Bit Rate traffic sources to perform an optimised resource redistribution. The efficiency of the Dynamic Bandwidth Allocation Capability (DBAC) depends on the accuracy of the traffic source description; inaccurate assessment of the arrival process will cause an overhead and a degraded utilisation of system resources. In this paper a flexible traffic burstiness predictor for dynamic bandwidth resource allocation based on neural network is presented. The approach perform an online estimation of expected resource requests implementing traffic resource assignment by using a sub-symbolic adaptive representation of the traffic source. The achieved results prove that the flexible approach is more effective than the ones based on fixed schemes designed using analytical traffic source description when applied on the satellite terminal ESW system component. An accurate design of neural network architecture and the low-cost industrial availability of this novel technology lead to an optimal trade-off between customer satisfaction in terms of QoS and system resource optimization also in terms of network operator revenue.