5G services are expected to enable a broad range of new applications at significantly reduced cost per bit compared to current network services (e.g. IoT applications). Industry efforts to address the cost per bit challenges have been evolving to include not just virtualization of network functions, but life cycle automation and artificial intelligence approaches (e.g. machine learning) to manage the expected scale of operation for 5G services. Industry-lead open source initiatives are playing a leading role (e.g. the Linux Foundation’s ONAP and Deep Learning Projects). Theoretical approaches for cost optimizations, and implementation experience reports e.g. using open source and other implementation approaches are sought to enable a dialogue across these technologies.
Topics including the following are sought:
• AI/ Machine Learning in 5G
• AI/Machine Learning in ONAP
• 5G operations using ONAP
• Scaling AI/Machine Learning for 5G
• AI/Federated Learning at Scale
• AI/ Machine learning & Blockchain
• Deep learning/machine learning/AI algorithms
• Tools/Platforms for AI Architecture for AI computing Edge and cloud AI computing platforms
• Deep learning for Internet-of-Things
• 5G Emerging applications of AI
• 5G: Autonomous Vehicles
• Ethical issues in AI/ML for network automation • Security-Aware and Privacy-Preserving.
Full technical papers should have a maximum paper length of six (6) printed pages (10-point font), including figures, without incurring additional page charges (maximum 1 additional page with over length page charge of USD100 if accepted). Papers exceeding 7 pages will not be accepted at EDAS.
For information on submissions, please visit http://www.ieee-nfvsdn.org/ Workshop Paper Submission:July 26, 2019
Notification of Acceptance: August 30, 2019
Camera-ready Submission: September 20, 2019.
Ashutosh Dutta (JHAPL)
Steven Wright (AT&T)
Technical Program Committee:
Tim Culver (UTD)
Ramki Krishnan (VMWare)
Dimitrios Tzovaras (CERTH/ITI, Virtual and Augmented reality Lab)
Konstantinos Votis (CERTH/ITI, Visual Analytics Lab) (TPC Chair)