Journal Name: Intelligent and Converged Networks - International specialized journal co-published by the International Telecommunication Union (ITU) and Tsinghua University Press (TUP)
- Series Call for Papers link: http://icn.tsinghuajournals.com/EN/column/item1649.shtml
- Journal web link: http://icn.tsinghuajournals.com/EN/0000-0000/home.shtml
Series on Data Driven Intelligence, Sustainability and Systems
Introduction of the series:
Networks and/or systems are expected to grow exponentially in the next decades. Networks may include but are not limited to communications, computing, social, vehicular, industrial, economic, and business networks, which may increase the complexities of relevant design, deployment, and management. The recent advances in artificial intelligence (AI) and data science technologies have provided promising approaches to deal with these complex problems, as well as in the applications of networks and/or systems. The trend towards highly integrated systems, with diverse underlying access technologies to support simultaneous, multiple, vertical industries also demands complex operations and support. This introduces further challenges related to design, analysis, and applications.
Additional global concerns are green and sustainability issues, related to information and communication technologies (ICTs). The ICT sector is accountable for significant carbon emissions and use of scarce natural resources. At the same time, ICTs play an enabling role in the transition and progress towards low carbon footprints, low resource consumptions, and sustainable environments as well as helping other vertical sectors to achieve sustainability goals without compromising the future of the next generations.
This series deals with the convergence of networks and/or systems, AI and data driven technologies, as well as green and sustainability issues. Topics of interest may include, but are 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 centres
- Internet of Things
- Security and privacy
- Relevant surveys
Important dates:(Submissions are always open every year)
Paper submission deadline for the first issue: June 30, 2020
Tentative time for the first issue publications: December 2020
Submission guidelines
Accepted papers will be published in the IEEE Xplore Digital Library 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
Please choose submission type as “Series on Data Driven Intelligence, Sustainability, and Systems” during submission processes.
Submission templates:
1. 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.
2. Submission templates for this journal in LaTeX and Word: http://icn.tsinghuajournals.com/EN/column/column8081.shtml
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, National Institute of Information and Communications Technology (NICT), Japan (lrd@nict.go.jp)
William Liu, Auckland University of Technology, New Zealand (william.liu@aut.ac.nz)
Chunguo Li, Southeast University, China (chunguoli@seu.edu.cn)