IEEE JSAC Special issue on Advances in Artificial Intelligence and Machine Learning for Networking

1 October 2019 all-day

Call for Papers – IEEE JSAC Special issue on Advances in Artificial Intelligence and Machine Learning for Networking


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 program-
mability fuels the need for improved network automation in agile infra-
structures, including edge and fog environments. Network design and optimi-
zation 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 mplemen-
tation 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 the following
topics, 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

* User experience-driven network planning
* Learning algorithms and tools for network diagnostics and root cause

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 Guide for Authors as published on the
Journal website at

  • Manuscript Due: October 1, 2019
  • Acceptance notification: March 1, 2020
  • Final manuscript due: March 15, 2020
  • Expected Publication of the Special Issue: Second quarter 2020

Guest Editors

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