Call for Papers

Artificial Intelligence (AI) and Machine Learning (ML) approaches have emerged in the networking domain with great promise. They can be clustered into AI/ML techniques for network engineering and management, network design for AI/ML applications, and system aspects. AI/ML techniques for network management, operations and automation improve the way we address networking today. They support efficient, rapid, and trustworthy management operations. The current interest in softwarization and network programmability fuels the need for improved network automation in agile infrastructures, including edge and fog environments. Network design and optimization for AI/ML applications address the complementary topic of supporting AI/ML-based systems through novel networking techniques, including new architectures and performance models. A third topic area is system implementation and open-source software development.

This special issue will focus on networking aspects (mostly, network layer and above). Work with primary contribution to physical layer concepts or wireless access should be submitted to other venues. Prospective authors are invited to submit high-quality, original manuscripts on topics including, but not limited to:

Fundamental Frameworks

• Network theory inspired by machine learning
• Transfer learning and reinforcement learning for networking
• Big data analytic frameworks for networking data

Network analytics

• Machine learning, data mining and big data analytics for networking
• Representation learning on operational data
• Data mining, statistical modeling, and machine learning for network management
• User experience-driven network planning
• Learning algorithms and tools for network diagnostics and root cause analysis

Network decision making and optimization

• Protocol design and optimization using machine learning
• Network architecture and optimization for AI/ML applications at scale
• Resource allocation for shared/virtualized networks using machine learning
• Energy-efficient network operations based on AI/ML algorithms
• AI/ML Algorithms for network security
• Network Reliability, robustness and safety based on AI/ML concepts
• Security for networks optimized and operated based on AI/ML concepts

Network automation

• Self-driving networks
• Self-Learning and adaptive networking protocols and algorithms
• Deep learning and reinforcement learning in network control & management
• Predictive or self-aware networking maintenance
• Open-source AI software for networking or networked applications

Submission Guidelines

All submissions must follow the Information for Authors as published on the Journal website. All papers need to be submitted via EDAS.

Important Dates

Manuscript Due: 1 October 2019
First Notification: 15 December 2019
Acceptance Notification: 1 March 2020
Final Manuscript Due: 15 March 2020
Expected Publication of the Special Issue: Second Quarter 2020

Guest Editors

Rolf Stadler (Lead Guest Editor)
KTH Royal Institute of Technology, Sweden

Prosper Chemouil
Orange Labs (retired), France

Pan Hui
University of Helsinki, Finland & Hong Kong University of Science and Technology, Hong Kong

Noura Limam
University of Waterloo, Canada

Wolfgang Kellerer
Technical University of Munich, Germany

Yonggang Wen
Nanyang Technological University, Singapore