The project FRADIS aims to create a new FRAmework for performance-aware Differentiated Innovative Services in 5G and beyond networks. FRADIS integrates a set of new algorithms and protocols to perform dynamic performance, energy consumption and quality trade-off according to specific service requirements when supporting differentiated services. FRADIS employs an innovative machine learning solution when selecting the best approach for service-specific optimisation between an infrastructure-dependent approach and a protocol-based solution.

The goal of FRADIS is to support differentiated delivery of services with heterogeneous requirements at high quality across a complex heterogeneous network environment such as that of a 5G and beyond network. Examples of such services include smart city monitoring data, e-health information, emergency messages, infotainment, rich media targeted advertisement, diverse IoT and sensor data, road traffic navigation data, agriculture monitoring information, touristic virtual reality data, etc.