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Although the complete scope of the sixth generation of mobile technologies(6G) is still unclear, the prominence of the Internet of Things (IoT) andArtificial Intelligence (AI) / Machine Learning (ML) in the networking field isundeniable. In this regard, key technology enablers for the previousgeneration, 5G, such as software-defined networking and network functionvirtualization, fall short to accomplish the stringent requirements envisionedfor 6G verticals. This PhD thesis goes back to basics, by exploring missingfunctionality gaps in relation to these technologies, in order to provide the''glue'' for holistic and fully-fledged networking solutions for 6G, alignedwith standards and industry recommendations. Although ambitious, and in a veryearly stage, this PhD thesis illustrates an initial design for in-band controlin Software-Defined Networking (SDN) that could facilitate the interoperabilityamong constrained IoT devices. The current design demonstrates promisingresults in terms of resource-usage and robustness, which are pivotal featuresfor constrained networks. Next steps include the integration of the approachwith a real testbed comprised of constrained IoT devices and the implementationof a federated learning environment at the edge.

Enabling Technologies for Programmable and Software-Defined Networks: Bolstering the Path Towards 6G