Network Virtualization and Edge/Fog Computing

This section aims at offering a state-of-the-art publication venue for researchers and a fresh up-to-date overview for beginners (with both surveys/reviews and in-depth original technical papers) about vast fields of research, including network virtualization, virtualized networked resources, edge/fog-oriented cloud continuum, and network orchestration in future generation networks, which will continue to become more focused on virtualization techniques. Nowadays network virtualization and distributed cloud computing (i.e., cloud continuum) have made tremendous advancements, with several mechanisms, supports, and technologies emerging within the field, including software-defined networking (SDN), network function virtualization (NFV), virtualized network containerization, DevOps for container-oriented virtual network resources, supports and applications as microservice compositions in the cloud continuum, cloud continuum for distributed artificial intelligence (AI), AI-based optimization of virtual networking, and distributed and federated machine learning, to mention a few. Our section aims to become an international, recognized, and visible home for the above research topics and any related advancements in the field of network virtualization and edge/fog cloud computing.

To this purpose, our section solicits conceptual, theoretical, and experimental contributions discussing and solving technical challenges, reviewing the state-of-the-art, and presenting innovative approaches/solutions to a set of currently unresolved key questions including, but not limited to, the following themes related to network virtualization and the cloud continuum: edge/fog-enhanced cloud continuum architecture; B5G and 6G infrastructure and architectural models; communication, networking, and coordination paradigms for virtualized networking resources in the cloud continuum; communication, networking, and coordination protocols for the cloud continuum; simulation-based performance analysis; in-the-field experimental and performance results, with a special focus on scalability; interoperability and security of virtualized network resources in the cloud continuum; distributed middleware exploiting network virtualization for emerging wide-scale applications, such as IoT big data analytics and distributed machine learning; etc. It aims to provide a forum for research from both academia and the industry and to be the section of our journal Future Internet in which you can disseminate your results to a global community of experienced technical managers and junior researchers in the field.

Subject Areas

• Reference architectures and frameworks for virtualized next-generation network infrastructure (NGNI)
• Open networking approaches and toolkits for NGNI
• End-to-end network function disaggregation and composition (beyond Open RAN, NFV, etc.)
• Network abstractions and open APIs for virtualized NGNI
• Virtualized networking as part of applications vs. multi-purpose networks (network slicing)
• Virtualization technologies and infrastructures in the cloud continuum
• QoS/QoE management and orchestration in open virtualized NGNI
• End-to-end network programming
• Novel software paradigms for integrated control and management of virtualized networks
• Quality control and low-latency middleware for control loops based on virtualized cloud continuum resources
• Private campus and enterprise (e.g., industrial IoT) networks
• Interworking, interoperability, and interdomain networking of virtualized networked resources
• Life cycle management and innovative deployment models for virtualized NGNI (CD/CI, DevOps, etc.)
• AI/ML for network automation and optimization (NGNI MLOps)
• Virtualized networking and cloud continuum for distributed AI/ML
• Scalability and wide-scale performance evaluation of virtualized network infrastructures and applications
• Lessons learned from real deployment environments and in-the-field optimization experiences
• Security and identity management in NGNI
• Resilience and sustainability of NGNI
• Energy-efficient cloud continuum for networking and massive distributed applications
• Best practices, open testbeds, and living labs