-------- Forwarded Message -------- Subject: [AISWorld] Special Issue on "Edge Intelligence for 6G Networks" - Elsevier Journal on Computer Communications - CfP Date: Sun, 21 Nov 2021 17:04:34 +0100 From: Giovanni Schembra giovanni.schembra@unict.it To: aisworld@lists.aisnet.org
[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
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