IEEE Network Magazine – Special Issue on Big Data Intelligent Networking
Jul 1 all-day

Publication Date: July 2020

Manuscript Submission Deadline: 1 July 2019

Special Issue

Call for Papers

A vast amount of big data is opening the era of the data-driven solutions which will shape communication networks. Current networks are often designed based on the static end-to-end design principle, and their complexity has dramatically increased over the past several decades, which hinders the efficient and intelligent provision of big data. Both networking for big data and big data analytics in networking applications pose great challenges for industry and academic researchers.

Small devices are continuously generating data, which are processed, cached, analyzed, and finally stored on in-network storages (e.g., routers), edge servers, or Clouds. From them, users efficiently and securely discover and fetch big data for diverse purposes. Intelligent networking technologies should be designed to effectively support such big data distribution, processing, and sharing.

On the other hand, critical applications, such as industrial Internet of Things, connected vehicles, network monitoring/security/management, require fast mechanisms for real-time analysis of a huge number of events, as well as off-line analysis of massive historical data. These applications show strong demands to enable the networking decisions (e.g. routing, caching, security, and slicing) to be intelligent and automatic. Furthermore, big data analytic techniques to extract features and analyze the vast amount of data lead to a heavy burden on the networking, and therefore smart and scalable approaches must be conceived to enable them to be practical.

The aim of this special issue is to answer some of the questions related to intelligent networking for big data and big data analytics for networking. The potential topics include, but are not limited to:

  • Networking architecture for big data
  • Machine learning, data mining and big data analytics in networking
  • Information-centric networking for big data
  • Software-defined network and network function virtualization for big data
  • Edge, fog, and mobile edge computing for big data
  • Security, trust, and privacy for big data networking
  • 5G and future mobile networks for big data sharing
  • Blockchain with big data networking
  • Data-center network for big data processing
  • Data analytics for networking big data
  • Distributed monitoring architectures for networking big data
  • Machine learning for network anomaly detection and security
  • In-network computation for intelligent networking
  • Big data analytics for network management
  • Distributed artificial intelligence for networking
  • Efficient networking for distributed artificial intelligence
  • Big data analytics and visualization for network traffic
  • Big data analytics for intelligent routing and caching
  • Big data networking in healthcare, smart cities, industry and other applications

Submission Guidelines

Manuscripts should conform to the standard format as indicated in the Information for Authors section of the Paper Submission Guidelines.

All manuscripts to be considered for publication must be submitted by the deadline through Manuscript Central. Select the “July 2020: Big Data Intelligent Networking” topic from the drop-down menu of Topic/Series titles.

Important Dates

Manuscript Submissions Deadline: 1 July 2019
Initial Decision Notification: 1 November 2019
Final Decision Notification: 1 March 2020
Final Manuscript Deadline: 1 April 2020
Publication Date: July 2020

Guest Editors

Ruidong Li
National Institute of Information and Communications Technology, Japan

Houbing Song
Embry-Riddle Aeronautical University, USA

Jiannong Cao
Hong Kong Polytechnic University, Hong Kong

Payam Barnaghi
University of Surrey, UK

Jie Li
Shanghai Jiaotong University, China

Constandinos X. Mavromoustakis
University of Nicosia, Cyprus

IEEE JSAC Special issue on Advances in Artificial Intelligence and Machine Learning for Networking
Oct 1 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,