[AISWorld] Network Intelligence 2019 AT Infocom 2019 - Final deadline extension

[Giovanni Schembra]

Please accept my apologies if you receive multiple copies of this CFP 

 

DEADLINE EXTENDED TO: January 24, 2019 (FIRM DEADLINE)

 

------------------------------------------   Call for Papers
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The 2nd International Workshop on Network Intelligence

NI 2019

“Machine Learning for Networking”

 

in conjunction with IEEE Infocom 2019

 

 <http://infocom2019.ieee-infocom.org/workshop-network-intelligence>
http://infocom2019.ieee-infocom.org/workshop-network-intelligence 

 <http://ni.committees.comsoc.org/ni-workshop-2019/>
http://ni.committees.comsoc.org/ni-workshop-2019/ 


29 April – 2 May 2019 – Paris, France

 

Technically Sponsored by IEEE Communications Society, Technical Committee on
Cognitive Networking, Technical Committee on Big Data, IEEE Network
Intelligence Emerging Technologies initiative

(IEEE NI ETI)

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Network Intelligence considers the embedding of Artificial Intelligence (AI)
in future networks to fasten service delivery and operations, leverage
Quality of Experience (QoE) and guarantee service availability, also
allowing better agility, resiliency, faster customization and security. This
concept inherits the solid background of autonomic networking, cognitive
management, and artificial intelligence. It is envisioned as mandatory to
manage, pilot and operate the forthcoming network built upon SDN, NFV and
cloud.

The main goal of the Network Intelligence Workshop is to present
state-of-the-art research results and experience reports in the area of
network intelligence, addressing topics such as artificial intelligence
techniques and models for network and service management; smart service
orchestration and delivery, dynamic Service Function Chaining, Intent and
policy based management, centralized vs. distributed control of SDN/NFV
based networks, analytics and big data approaches, knowledge creation and
decision making. This workshop offers a timely venue for researchers and
industry partners to present and discuss their latest results in Network
Intelligence. 

The main topic of this NI 2019 edition is “Machine Learning for Networking”
which puts the attention on the particular application of machine learning
tools to the optimization of next generation networks. Machine and deep
learning techniques become increasingly popular and achieve remarkable
success nowadays in many application domains, e.g., speech recognition,
bioinformatics and computer vision. Machine learning is capable to exploit
the hidden relationship from voluminous input data to complicated system
outputs, especially for some advanced techniques, like the deep learning.
Moreover, some other techniques, e.g., reinforcement learning, could further
adapt the learning results in the new environments to evolve automatically.
These features perfectly match the complex, dynamic and time-varying nature
of today’s networking systems. 

 

This workshop presents state-of-the-art research in machine learning for
networking. Both theoretical and system papers will be considered, to
present novel contributions in the field of machine learning,  deep learning
and, in general, network intelligent tools, including scalable analytic
techniques and frameworks capable of collecting and analyzing both online
and offline massive datasets, open issues related to the application of
machine learning into communications and networking problems and to share
new ideas and techniques for machine learning in communication systems and
networks. The topics of interest include (but not limited to):

 


•       Deep and Reinforcement learning for networking and communications in
networks

•       Data mining and big data analytics in networking

•       Protocol design and optimization using AI/ML 

•       Self-learning and adaptive networking protocols and algorithms 

•       Intent & Policy-based management for intelligent networks

•       Innovative architectures and infrastructures for intelligent
networks

•       AI/ML for network management and orchestration 

•       AI/ML for network slicing optimization in networking

•       AI/ML for service placement and dynamic Service Function Chaining 

•       AI/ML for C-RAN resource management and medium access control

•       Decision making mechanisms

•       Routing optimization based on flow prediction network systems

•       Bio-inspired learning for networking and communications

•       Protocol design and optimization using machine learning

•       Data analytics for network and wireless measurements mining

•       Big data analysis frameworks for network monitoring data 

•       Novel context-aware, emotion-aware networking services

•       Methodologies for network problem diagnosis, anomaly detection and
prediction 

•       Network Security based on AI/ML techniques

•       AI/ML for multimedia networking 

•       AI/ML support for ultra-low latency applications

•       AI/ML for IoT

•       Open-source networking optimization tools for AI/ML applications

•       Experiences and best-practices using machine learning in operational
networks

•       Machine learning for user behavior prediction

•       Modeling and performance evaluation for Intelligent Network

•       Intelligent energy-aware/green communications

•       Machine learning and data mining for networking

•       Transfer learning and reinforcement learning for networking system

•       Network anomaly diagnosis through big networking data and wireless

•       Machine learning and big data analytics for network management

•       Big data analytics and visualization for traffic analysis

•       Fault-tolerant network protocols using machine learning

•       Experiences and best-practices using machine learning in operational
networks

 

This workshop is supported by IEEE ComSoc Emerging Technical Initiative on
Network Intelligence, technically sponsored by IEEE Communications Society,
Technical Committee on Cognitive Networking, and Technical Committee on Big
Data.

 


Authors of the top-ranked papers accepted for publication in the NI 2019
workshop proceedings will be invited to submit an extended version of their
papers to the IEEE Transactions on Network and Service Management (TNSM)
journal.

 

 

SUBMISSION LINK

Papers must be submitted electronically as PDF files, formatted for
8.5x11-inch paper. The length of the paper must be no more than 6 pages in
the IEEE double-column format (10-pt font). Papers should neither have been
published elsewhere nor being currently under review by another conference
or journal. The reviews will be single blind. At least one of the authors of
every accepted paper must register and present the paper at the workshop.
Accepted papers will be published in the combined INFOCOM 2019 Workshop
proceedings and will be submitted to IEEE Xplore.

 

EDAS link for paper submission:  <http://edas.info/N25585>
http://edas.info/N25585 

 


Important dates

*	Paper submission deadline:             December 30, 2018  January
24, 2019 (FIRM DEADLINE)
*	Acceptance notification:                   February 18, 2019

·         Camera ready due:                              March 7, 2019

 


General Chairs:

·         Mérouane Debbah (CentraleSupélec, France)

·         Baochun Li (University of Toronto)

·         Giovanni Schembra (University of Catania, Italy)

·         Dapeng Oliver Wu (University of Florida)

              

Technical Program Committee Chairs:

·         Laura Galluccio (University of Catania, Italy)

·         Qiuyuan Huang (Microsoft Research, Redmond, USA)

·         Yunhuai Liu (Peking University, China)

·         Mohamed Faten Zhani (Universitè du Quebec, Canada)

NI Steering Committee Members:

·          <mailto:imen.gridabenyahia at orange.com?Subject=%5BNI%5D> Imen
Grida Ben Yahia (Orange Labs, France)

·          <mailto:laurent.ciavaglia at nokia-bell-labs.com?Subject=%5BNI%5D>
Laurent Ciavaglia (Nokia Bell Labs, France)

·          <mailto:wevertoncordeiro at gmail.com?Subject=%5BNI%5D> Weverton
Cordeiro (UFRGS, Brazil)

·         Mérouane Debbah (CentraleSupélec, France)

·         Laura Galluccio (University of Catania, Italy)

·         Baochun Li (University of Toronto)

·          <mailto:n2limam at uwaterloo.ca?Subject=%5BNI%5D> Noura Limam
(University of Waterloo, Canada)

·         Giovanni Schembra (University of Catania, Italy)

·         Dapeng Oliver Wu (University of Florida)

·          <mailto:mfzhani at etsmtl.ca?Subject=%5BNI%5D> Mohamed Faten Zhani
(École de Technologie Supérieure, Canada)