*Guest Editors*
*Liang Zhao*, Shenyang Aerospace University, China, lzhao@sau.edu.cn
*Jia Hu*, University of Exeter, UK, j.hu@exeter.ac.uk
*Ahmed Al-Dubai*, Edinburgh Napier University, UK, al-dubai@napier.ac.uk
*Celimuge Wu*, University of Electro-Communications, Japan,
celimuge@uec.ac.jp
*Qi Wang*, Institute of Computing Technology, Chinese Academy of Sciences,
China, wangqi08@ict.ac.cn
*Ammar Hawbani*, University of Science and Technology of China, China,
anmande@ustc.edu.cn
*Overview*
Over the past decades, the technologies of artificial intelligence (AI) and
machine learning (ML) have undergone a series of evolutionary innovation
where these technologies have been promoting the quality of human life
significantly. Learning the patterns and creating actions from the proper
data could provide better and right decisions for many applications. By
applying such techniques, the performance of networks could be refined to
ensure scenarios including broad coverage, high capacity, high resource
availability, extensive connectivity and key metrics including bandwidth,
jitter, throughput, transmission delay and availability. This special issue
is designed to foster the application and innovation of AI and ML
technologies for mobile networking within 5G, MANETs, VANETs, wireless
sensor networks and as well as other forms of networks. This is to explore
a way of seamless and intelligence-driven communications for enabling
evolution of the current networks and beyond, and thus, to support the
sustainable smart cities.
*Topics*
Topics of interest include, but are not limited to, the following scopes:
· Intelligent 5G networks
· Industrial wireless networks
· Smart network planning and optimisation
· Data-based analysis of users (user group/user behaviour/user track
etc.)
· Data-based analysis of network quality & performance & telecom value
area
· Intelligence-driven mobile computing and wireless communications
· Intelligent mobile network protocols
· Data-based network Trust, security, and privacy
· Software defined networks
· Machine learning for mobile networking
· Network-based models and optimisation algorithms
· Data-driven social network analysis
· Internet of Things (IoT) and big data
· Intelligent vehicular networks
· Intelligent wireless sensor networks
· Smart Cloud, Fog and Edge
· Next-generation Internet
· Intelligent load balancing and traffic control
*Tentative Schedule *
Manuscript submission deadline: February 15, 2020
Notification of acceptance: June 15, 2020
Submission of final revised paper: September 15, 2020
Publication of special issue (tentative): 4th Quarter, 2021
*Major Guidelines*
We invite the submission of original and high-quality manuscripts
describing topics related to intelligence-driven mobile networks.
Submissions of "extended versions" of already published works (e.g.,
conference/workshop papers) should be significantly extended with a
relevant part of novel contribution (50%). A "Summary of Differences"
between the submitted paper to this special issue and the former one must
be included.
*Submission Guidelines*
All submitted manuscripts must be formatted according to Computing's
instructions for authors which are available at https://www.springer.com/607.
We will accept both LaTeX manuscripts (which must use Springer templates at
https://www/springer.com/607) and word manuscripts (for which no templates
are available).
*Manuscript length*
Please note that the page limit for Special Issue submissions differs from
that of regular Computing submissions. Manuscripts submitted to the Special
Issue should not exceed 20 pages. Submission that do not comply with this
requirement are likely to be desk rejected without being reviewed.
*Submission instruction*
Manuscripts should be submitted using the online submission system at (
http://www.springer.com/607).
When submitting a manuscript for this special issue, authors should take
care to select 'Intelligence-driven Mobile Networks for Smart Cities'.
*A copy of the manuscript should also be emailed to the Guest Editor at the
following email address: lzhao@sau.edu.cn <lzhao@sau.edu.cn>*
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