[AISWorld] Special Issue on "Edge Intelligence for 6G Networks" - Elsevier Journal on Computer Communications - CfP

[Giovanni Schembra]

[apologies for cross-posting]

 

 

Dear All,

submission deadline to the special issue on “Edge Intelligence for 6G
Networks” – Elsevier Journal on Computer Communications

is approaching. 

 

More details are available on: 

 
<https://www.journals.elsevier.com/computer-communications/call-for-papers/s
pecial-issue-on-edge-intelligence-for-6g-networks>
https://www.journals.elsevier.com/computer-communications/call-for-papers/sp
ecial-issue-on-edge-intelligence-for-6g-networks

 

and also described below.

Submission deadline is 25th November 2021

We look forward to your submissions! 

 

Best regards,

Nabeel Akhtar, Akamai Technologies Inc, USA

Salvatore D’Oro, Northeastern University, USA

Christian Grasso, University of Catania, Italy

Giovanni Schembra, University of Catania

Michael Seufert, University of Würzburg, Germany

 

Guest Editors of the Journal on Computer Communications

Special Issue on “Edge Intelligence for 6G Networks”

 

 

---------------------- CUT HERE ----------------------

 

Journal on Computer Communications

Special Issue on “Edge Intelligence for 6G Networks”

 

(https://www.journals.elsevier.com/computer-communications/call-for-papers/s
pecial-issue-on-edge-intelligence-for-6g-networks)

 

In the last few years, due to the increasing evolution of the IoT, a lot of
new services and applications with heterogeneous characteristics in terms of
generated traffic, mobility and different Quality of Service (QoS)
requirements have been conceived. This will result in a huge amount of data
transmission on the next-generation communication network nodes. In this
scenario, a real time adaptation to network conditions changes to providing
quality user experience in ultra-dense and uncoordinated future networks
plays an important role. For these reasons, the use of solutions based on
data-driven machine learning and AI techniques is fundamental. Although the
capabilities offered by the remote cloud satisfy the current resource and
energy hungry requirements of AI due to the big data to be analyzed, with
the implementation of Edge Computing paradigm, the possibility to consider
the highly distributed AI solutions with small memory footprint is
fundamental. 

The combined use of AI and Edge Computing allows the birth of Edge
Intelligence, with the purpose of moving the intelligence from the central
cloud to the edge resources, enabling the Intelligent Internet of
Intelligent Things (IIoIT). The Edge Intelligence provides an efficient way
to manage various aspects of the edge computing approach, from resource
management to the organization of data produced by devices, along with the
instantiation of suitable software for computational and storage facilities
of the edge. 

This special issue will be devoted to both the theoretical and the practical
evaluations related to the design, analysis and implementation of AI
techniques applied at the Edge of the network. Topics of interest include,
but are not limited to:

 




*         Enabling technologies for Edge Intelligence: SDN, NFV, Edge
Computing, AI/ML techniques

*         Data-driven management of software defined networks in Edge
Computing context

*         Deep and Reinforcement learning for networking and communications
at the Edge of in 6G networks

*         Decision making mechanisms at the Edge

*         AI/ML for network management and orchestration at the Edge of
future networks

*         Intelligent energy-aware/green resource management at the Edge

*         AI/ML support for ultra-low latency applications at the Edge of
the network

*         Reliability, robustness and safety based on AI/ML techniques at
the Edge

*         AI/ML for IoIT and IIoIT

*         Open-source networking optimization tools for Edge Intelligence

*         Modeling and performance evaluation for Intelligent Internet of
Intelligence Things

*         AI/ML for optimization of network slicing extension toward the
Edge in future networks

*         Novel application scenarios for Edge Intelligence

*         AI/ML for service placement and dynamic Service Function Chaining
in the Edge Computing scenario

*         Self-learning and adaptive networking protocols and algorithms for
6G Edge nodes

*         Innovative architectures and infrastructures for Edge Intelligence




 




 


GUEST EDITORS

IMPORTANT DATES


Nabeel Akhtar, Akamai Technologies Inc, USA

Salvatore D’Oro, Northeastern University, USA

Christian Grasso, University of Catania, Italy

Giovanni Schembra, University of Catania

Michael Seufert, University of Würzburg, Germany

 

Submission Deadline: 25th November 2021

First Reviews Due: 30th December 2021

Revision Due: 10th February 2022

Acceptance Notification: 10th March 2022

Final Manuscript Due: 25th April 2022

Estimated Publication: As per the journal policy