IEEE Consumer Communications & Networking Conference
8–11 January 2023 // Las Vegas, NV // USA

Call for Papers

The SONATAI workshop aims to be a forum for researchers and engineers from academia and industry to present and discuss novel ideas, solutions and results aiming to support the requirements of emerging and challenging applications on future generation network architectures.

We invite authors to submit unpublished papers with novel research contributions, addressing mixed reality applications and critical services in edge and cloud continuum, optimised and secured through federated AI mechanisms. Topics include and are not limited to:

Edge and cloud continuum

  • Dynamic migration of network functions between edge and cloud
  • Optimized resource allocation for network functions at the edge and cloud
  • Architectures for edge and cloud continuum
  • Software defined infrastructures for edge and cloud continuum
  • Optimization and implementation of edge and cloud continuum
  • Security mechanisms for edge and cloud continuum (Intrusion detection and prevention)
  • Authentication and Accounting mechanisms for edge and cloud continuum
  • Network softwarization for edge and cloud continuum

Service function chaining

  • Service Function Chaining modelling and representation for IoT and mission critical services
  • Network softwarization and virtualization for mixed reality applications
  • Dynamic migration of network functions in the xNF paradigm
  • Efficient network and service monitoring of Network Functions
  • Resilience, QoS/QoE management of network functions
  • Secure architectures and protocols for Service Function Chaining
  • Optimization and implementation of Service Function Chaining
  • Algorithms for Service Function Chaining

Federated AI

  • Data privacy with federated learning
  • Platforms for federated AI
  • Federated AI models for mixed reality applications and services
  • Federated AI models for efficient and secure service/applications orchestration and distribution
  • Federated AI models for efficient data collection and resource monitoring
  • Federated AI for Service Function Chaining

Patrons