Aeronautical CNS systems rely on traditional network architectures involving numerous dedicated devices and proprietary implementations.
Network heterogeneity, lack of centralization and programmability makes network deployment, management and maintenance operations extremely complex.
In the future, datalink networks will progressively migrate to future IPv6 centric technologies over multilink which implies a centralized management of the network and the implementation of high-level security mechanisms.
More intelligence and automation will be additionally needed to efficiently manage and secure network operations while optimizing capacity and improving performance and mobility.

The Software Defined Networking (SDN) concept brings a framework allowing a logically centralized control, a global view of the network, a software-based traffic analysis, as well as a dynamic updating of traffic forwarding rules.
Additionally, Artificial Intelligence (AI) makes possible for machines to learn from experience, to adjust to new inputs and situations, and to automate a large panel of tasks.
Introducing AI in the SDN framework by applying machine learning (ML) techniques will allow sensible benefits in the way future datalink communications networks are operated.