As the next generation communication systems beyond 5G, such as 6G, are expected to address a wider range of services and applications with a wider range of dynamic environmental and service-specific requirements, these systems evolve towards an architecture supported by enhanced capabilities to adapt to such flexible environments and connectivity needs. Envisioned 6G systems are expected to see a further increase of applications with stricter and heterogeneous requirements, be adaptive to connectivity requirements through dynamic topologies, and take autonomous decisions to reconfigure the networks for efficiency and resiliency purposes. Flexible and agile networking solutions are required to deal with uncertainties and dynamic parameters. As the number of QoS-demanding applications increases, the capability of end-to-end holistic network transformation is required triggered by the dynamicity and mobility of users and their service demands as well as the radio and resource topology. The complexity introduced by these flexible characteristics needs to be addressed with more adaptive network resource sharing mechanisms among users and applications. This includes the adaptation to individual QoE/QoS needs and the dynamics of the applications and services, starting from access networks to core networks.

Ability to process the big data generated by the network, derive necessary feedbacks from the network and AI-assisted cognitive network management are key enablers for elasticity and adaptiveness to network dynamics such as topology changes due to the mobility of the end users, base stations and rearrangement of network resources (either physical or virtual network functions). A distributed, self-*, AI-assisted and deeply programmable/reconfigurable end-to-end network architecture is required to address such network dynamics.

Topics of Interest:

All aspects of cognitive, flexible, dynamic, agile network architectures
Autonomous management of such networks, (real-time) zero-touch management
Autonomous network function allocation and placement
AI-assisted deeply-programmable networks, programmable data planes and nodes
Edge assistance and device-edge-cloud collaboration for elasticity, edge-AI networks
Distributed computing environments, hyper-distributed applications, integration of computing, connectivity, IoT, AI
Architectures for collaborative smart nodes with decentralised intelligence, federated machine learning in 6G
Microservice-based flexible architectures, network management, service orchestration
Open interfaces and open source solutions for smart networks
Virtual radio access technologies, programmable RAN, RANaaS
Energy-oriented network management, ultra-low-energy 6G networks
Multi-context awareness, dynamic multi-service and multi-tenancy and network slicing
Flexible backhauling/fronthauling, Integrated access/backhaul (IAB), multi-hop mesh backhauling
Runtime flexibility in services and applications, application-driven optimization
Drone-assisted agile networks, base stations on wheels or wings
Flexible and software-defined security, physical-layer security
Flexible and rapid deployment for automated and smart services
Private Beyond 5G Networks: Solutions to simplify the lifecycle, deployment, and operation

All in all, future networks must be flexible and elastic to easily introduce new services, applications and business models. Any topic related to this concept is welcome