The softwarization of infrastructure and the virtualization of communication networks (and network functions) is a strategic direction for meeting the various technical and socio-economic requirements imposed by emerging systems. It's a direction that interests both the research community and industrial players grouped together in international working groups (ETSI, notably in Europe, and W3C). Current technological solutions are moving in the direction of convergence between the world of information processing, which has seen the advent of "cloud computing" and "service computing" technology for over a decade, and the world of telecommunications, which in recent years has been promoting the softwarization and virtualization of network services and functions (SDN/NFV).

Our work focuses on solving the challenges posed by the adoption of emerging and (so-called) next-generation networks for service provisioning and hosting. These include fifth-generation mobile technologies (5G/MEC), network function virtualization infrastructures (NFV/VNFI), content distribution networks (CDN) and the Internet of Things (IoT). The integration and operation of such networks within the service computing model poses various challenges that need to be addressed, such as flexibility to meet the demands of many users, scalability to ensure that the information and communication technology (ICT) infrastructure supports the required functionalities and technologies, and the necessary efficiency in managing large-scale services and heterogeneous infrastructures.

Advanced network virtualization and softwarization are the keys to realizing a next-generation ICT infrastructure. Our work aims to:

• Set up the basic architectures and services to enable the distributed, multi-domain orchestration of network services needed to implement dynamic network (re)configuration to meet the wide variety of end-user demands in real time
• Support efficient resource management for a heterogeneous, distributed (multi-domain) environment
• Achieve scalability and elasticity according to service volume, and ensure sustainability to involve new functionalities and technologies
• Adapt and integrate automation as far as possible into infrastructure component and lifecycle management (DevOps and Site Reliability Engineering). This requires, among other things, the adaptation and integration of machine learning models into the service provisioning process