[hpc-announce] [CFP] Deadline Extended: June 10th - IEEE CAMAD'20 - SS on Emerging Data-driven Approches for Network Optimization

[Claudio Fiandrino]

*[Our apologies if you receive multiple copies of this announcement]*

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SS on Emerging Data-driven Approches for Network Optimization

IEEE CAMAD 2020 (VIRTUAL with reduced fees)

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

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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 10th (Extended)
Notification Acceptance: July 5th
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.

-- 
Claudio Fiandrino, PhD
Post-Doc Researcher

IMDEA NETWORKS Institute
Web: http://people.networks.imdea.org/~claudio_fiandrino/
Phone: (+34) 91 481 6932