IEEE CAMAD 2020 (held VIRTUALLY)

https://camad2020.ieee-camad.org/

Reduced Registration fees for IEEE COMSOC MEMBERS: USD 200

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The foundation of 5G and beyond mobile networks lies in the convergence
between networking and computing. The most appealing realization of such
convergence is the application of artificial intelligence (AI) and
machine learning (ML) to optimize network functions. The latter has
generated an increasing interest from academia and industry paving the
path for the transformation from the 5G paradigm “connected things” into
a “connected intelligence” vision for beyond 5G and 6G mobile networks.
To this end, the role of AI/ML is to support zero-touch configuration
and orchestration, thereby enabling self-configuration and
self-optimization of the mobile network. Mobile networks are indeed
becoming increasingly complex, heterogeneous, dynamic and dense, which
makes extremely hard to model correctly their behavior. Model-free
solutions that AI enable can overcome such challenge.

This Special Session seeks contributions from experts in areas such as
network programming, distributed systems, machine learning, data
science, data structures and algorithms, and optimization to discuss the
latest research ideas and results on the application of AI/ML to
networking. Specifically, this Special Session welcomes contributions in
the following major areas (indicative list, other related topics will
also be considered):

– Machine learning (ML) and big data analytics in networking
– Case studies showing (dis)advantages of AI/ML techniques for
networking over traditional ones
– Edge-driven data analytics and applications to smart cities
– AI/ML assisted network optimization
– Resource-efficient machine learning for mobile networks
– Measurements and analysis of network traffic for AI/ML systems
– Efficient ML data structures, algorithms and network protocols to
process network monitoring data
– Approaches for privacy-aware network traffic data collection
– Architectures for federated learning and its applications to
networking
– Energy-efficient federated learning
– Incentive mechanisms of federated learning
– In-network computation for next generation wireless networks

** IMPORTANT DATES **

Submission Deadline: June 28th (Extended)
Notification Acceptance: July 25th
Camera-Ready due: July 31st

** SUBMISSION INSTRUCTIONS **

Prospective authors are invited to submit a full paper of not more than
six (6) IEEE style pages including results, figures and references.
Papers should be submitted via EDAS. Papers submitted to the conference,
must describe unpublished work that has not been submitted for
publication elsewhere. All submitted papers will be reviewed by at least
three TPC members, while submission implies that at least one of the
authors will register and present the paper at the conference.
Electronic submission will be carried out through the EDAS web site at
the following link: https://edas.info/newPaper.php?c=27371&track=101982

All accepted papers will be included in the conference proceedings and
IEEE digital library (http://ieeexplore.ieee.org/).

**** COVID-19 Restrictions ****

As you may be aware, the World Health Organization officially declared
the novel coronavirus COVID-19 a pandemic. This global health crisis is
a unique challenge that has impacted many members of the IEEE family. We
would like to express our concern and support for all the members of the
IEEE community, our professional team, our families and all others
affected by this outbreak.

Governments around the world are now issuing restrictions on travel,
gatherings, and meetings in an effort to limit and slow the spread of
the virus. The health and safety of the IEEE community is our first
priority and IEEE is supporting these efforts.

Following the advice and guidelines from healthcare officials and local
authorities, the IEEE CAMAD 2020 will now be held virtually on 14-16
September.

IEEE publications continue to accept submissions and publish impactful
cutting-edge research. Our online publications remain available to
researchers and students around the world.

Accepted papers for the IEEE CAMAD 2020 will be submitted for inclusion
in IEEE Xplore Digital Library after they are presented at the virtual
conference. Information and instructions on how to prepare for a virtual
presentation will be sent separately.

Registration fees for the IEEE CAMAD 2020 have been adjusted. Authors
and non-authors who have registered at the original fees will be
refunded the price difference.

We extend our heartfelt thanks and appreciation to all of our technical
community for your understanding and community engagement. Although the
IEEE CAMAD 2020 cannot be held physically, the integrity and quality of
the research and content will remain and now be experienced in the
virtual environment. Thank you for your support of our shared mission to
advance technology for humanity.

** ORGANIZERS **
Claudio Fiandrino (IMDEA Networks Institute, Spain)
Andrea Capponi (University of Luxembourg)