Call for Papers: Series on Data Driven Intelligence, Sustainability, and Systems

Introduction of the journal:

Intelligent and Converged Networks is an international journal co-published by the International Telecommunication Union (ITU) and Tsinghua University Press (TUP). It focuses on information and communication technologies (ICT) and reflects the trends in ICT areas and the needs of ITU as well. Considering ITU is the first international organization under United Nations (UN) to pay close attention to and advocates the artificial intelligence applications in the related areas, and that is the reason this journal is named as Intelligent and Converged Networks.

Accepted papers will be published in IEEE Digital Library (IEEE Xplore) as open access. No page charges will be requested for publications. No page limitations are set for paper submissions and publications.

Paper submission link: https://mc03.manuscriptcentral.com/icnjournal

It is allowed for authors to use IEEE transactions template (https://journals.ieeeauthorcenter.ieee.org/create-your-ieee-journal-article/authoring-tools-and-tem plates/ieee-article-templates/templates-for-transactions/) as Latex template for submissions.

Latex and Word template for submissions available on the section of Resources - Instructions & Forms at https://mc03.manuscriptcentral.com/icnjournal

Introduction of the series:

Networks and/or systems are expected to grow exponentially in the next decades. Networks may include but not limited to communications networks, computing networks, social networks, vehicular networks, industrial networks, economical networks, and business networks, which may increase the complexities of relevant designs, deployments, and managements. The recent advances in artificial intelligence (AI) and data science technologies have provided promising approaches to deal with complex problems faced in the designs, analyses, and applications of network and/or systems. The trend towards highly integrated and/or systems with diverse underlying access technologies to support simultaneous multiple vertical industries has also demanded complex operations and supports. These introduces great challenges in the relevant designs, analyses, and applications.

Another global concerns are green and sustainability issues, which are correlated to information and communications technologies (ICTs). On one side, information and communications technologies (ICTs) have high demands in reducing energy and material resources with sustainable ways. On the other hand, ICT may support the general green and sustainable objectives of the world, increasing quality of life for ever more people without compromising future generations to meet their needs.

This series may deal with AI and data driven technologies, green and sustainability issues, and convergences for networks and/or systems. Topics that may include, but not limited to:

- Data driven intelligence supported approaches and technologies
- Data driven intelligence supported applications and systems
- Green technologies
- Sustainability
- Artificial intelligence
- Communications and networking
- Convergence of communications, computing, and systems
- Relevant algorithms, approaches, analyses, and modelling
- Machine learning
- Data analytics
- Big data
- Big data meet green challenges
- Sustainability development goals
- Energy and energy efficiency issues
- Resource and resource efficiency issues
- Environmental concerns and protections
- AI meets ICTs
- Green ICTs
- Cloud computing and data centers
- Internet of Things
- Security and privacy
- Relevant surveys

Important dates:

DDISS series was established in June 2020.
Submissions always open with deadlines: Every May 15 and November 15.

Series Editors:

Jinsong Wu, University of Chile, Chile, wujs@ieee.org
Chuan Heng Foh, University of Surrey, UK, c.foh@surrey.ac.uk
Periklis Chatzimisios, International Hellenic University, Greece, pchatzimisios@ieee.org
Celimuge Wu, The University of Electro- Communications, Japan, celimuge@uec.ac.jp
Muhammad Imran, University of Glasgow, UK, Muhammad.Imran@glasgow.ac.uk
Ruidong Li, Kanazawa University,Japan, liruidong@ieee.org
William Liu, Auckland University of Technology, New Zealand, william.liu@aut.ac.nz
Chunguo Li, Southeast University, China, chunguoli@seu.edu.cn