AINet 2021: IEEE International Workshop on Artificial Intelligence for Intelligent Network Management (IEEE AINet - 2021) New York, USA, NY, United States, October 1-3, 2021 |
Conference website | https://sites.google.com/view/ieeeainet |
Submission link | https://easychair.org/conferences/?conf=ainet2021 |
Submission deadline | June 15, 2021 |
IEEE International Workshop on Artificial Intelligence for Intelligent Network Management (IEEE AINet - 2021)
in conjunction with
The 19th IEEE International Symposium on Parallel and Distributed Processing with Applications ()IEEE ISPA 2021
October 1-3, New York, USA
Artificial intelligence (AI) enables the simulation of human intelligence in computing machines that can be programmed to behave like humans and imitates their actions. The term can be associated with any machine that shows human traits such as learning new patterns and problem-solving. The main characteristic of artificial intelligence is its power to think rationally and take appropriate action to achieve a specific goal. Machine learning, which is a subset of artificial intelligence, refers to a computing paradigm that can automatically learn from a set of data with minimal human intervention. After that, it can take any input and classify or predict the outcomes.
Network technologies such as Software Defined Networking (SDN), Network Function Virtualization (NFV), and 5G / 6G, are continuously evolving to support the exponential growth of connected devices and unique performance expectations such as reliability, dependability, and scalability. The downside of those technologies is that they are changing faster than we can manage them. To address this problem, cognitive network (CN) is increasingly used, which refers to a network as a cognitive process that can take input as real-time network conditions, process them using artificial intelligence and act on those network conditions.
Therefore, research is required to understand and improve the potential and suitability of artificial intelligence in the context of network management. This will provide a deeper understanding and better decision-making based on largely collected and available network data. It will also present opportunities for improving artificial intelligence algorithms on aspects such as reliability, dependability, and scalability and demonstrate the benefits of these methods in management and control systems. This workshop aims at gathering the recent advances in AI for Intelligent network management. We hope this workshop will inspire new thoughts and contributions to this specific topic.
List of Topics
Topics include but are not limited to the following:
-
Deep and Reinforcement learning for networking and communications in 5G networks
-
Data mining and big data analytics in 5G networking
-
Protocol design and optimization using AI/ML in 5G
-
Self-learning and adaptive networking protocols and algorithms for 5G
-
Intent & Policy-based management for intelligent networks
-
Innovative architectures and infrastructures for intelligent networks
-
AI/ML for network management and orchestration in 5G systems
-
AI/ML for network slicing optimization in 5G systems
-
AI/ML for service placement and dynamic Service Function Chaining in 5G systems
-
AI/ML for C-RAN resource management and medium access control
-
Decision making mechanisms
-
Routing optimization based on flow prediction in 5G systems
-
Data-driven management of software defined networks for 5G networks
-
Methodologies for network problem diagnosis, anomaly detection and prediction
-
Reliability, robustness and safety based on AI/ML techniques
-
Network Security based on AI/ML techniques in 5G
-
AI/ML for IoT
-
Open-source networking optimization tools for AI/ML applications
-
Experiences and best-practices using machine learning in operational networks
-
Novel context-aware, emotion-aware networking services
-
Machine learning for user behavior prediction
-
Modeling and performance evaluation for Intelligent Network
-
Intelligent energy-aware/green communications
Submission Guidelines
Papers submitted to the workshop should be written in English conforming to the IEEE Conference Proceedings Format (8.5" x 11", Two-Column). The paper should be submitted through the symposium EasyChair submission system. Prospective authors are invited to submit full papers up to 6 pages in length and authors are allowed to purchase up to 2 extra pages.
Accepted and presented papers will be included into the IEEE Conference Proceedings published by IEEE CS CPS and submitted to IEEE Xplore. Authors of accepted papers, or at least one of them, are requested to register and present their work at the conference, otherwise their papers will be removed from the digital libraries of IEEE CS after the conference.
Submitting a paper to the workshop means that, if the paper is accepted, at least one author should attend the workshop and present the paper.
-
The Submission website link is: Submission Link
-
The Manuscript Templates for the conference proceedings can be found in here: Templates
Committe
Program Committee
-
Arif Ahmed, Ericsson Research, Sweden
-
Meriam Gay Bautista, Lawrence Berkeley National Laboratory, USA
Publicity Chair
-
Ananya Choudhury, Maastricht University, Netherlands
Technical Program Committe
-
Nikumani Choudhury, BITS Pilani, India
-
Biswapratap Singh Sahoo, Samsung R&D, India
-
Sambit Kumar Mishra, SRM University, India
-
Prabha Sundaravadivel, University of Texas at Tyler, USA
-
Ashish Nanda, Deakin University, Australia
-
Mukesh Prasad, University of Technology Sydney, Australia
-
Chi Yang, Huazhong University of Science and Technology, China
-
Xuyun Zhang, Macquarie University, Australia
-
Prasanth Yanambaka, Central Michigan University, USA
-
Ayan Mondal, University Rennes 1, Inria, IRISA, CNRS, France
-
Kumar Yelamarthi, Central Michigan University, USA
Publication
AINet 2021 proceedings will be published in The 19th IEEE International Symposium on Parallel and Distributed Processing with Applications (IEEE ISPA 2021)
by IEEE Computer Society
Venue
The conference will be held in New York, USA
Contact
All questions about submissions should be emailed to arif.ahme@ericsson.com, mgbautista@lbl.gov