The integration of AI and networking technologies is driving the development of intelligent and autonomous systems that are capable of making decisions and performing tasks in real-time. These systems are critical for a wide range of applications, including 5G networks, IoT, and edge computing. However, designing, implementing, and deploying AI systems in networked environments presents a number of unique challenges. One of the main challenges is ensuring that AI systems can operate effectively in dynamic network environments with varying network conditions. Another requirement is balancing the trade-offs between the computational and communication requirements of AI systems in networked environments. Additionally, there is a need to develop new algorithms and protocols that can effectively utilize the resources of the network while ensuring robustness and security. Finally, networked AI systems will deal with the high-dimensionality and heterogeneity of the data generated by AI systems in networked environments, which requires novel data management and analytics techniques.

The goal of this workshop is to bring together researchers and practitioners working on the design, implementation, and deployment of AI systems in networked environments. The workshop aims to provide a forum for discussing the latest research and development in this field, as well as for sharing practical experiences and case studies. By bringing together experts from academia and industry, the workshop aims to foster collaboration and to promote the development of new ideas and research directions in this field. The workshop is co-located with ACM MobiSys 2024 as an in-person event in Tokyo, Japan. We invite submissions of original research papers,and papers describing practical experiences, case studies, and tutorials.

More specific topics of interest, include, but are not limited to:

- Distributed and collaborative AI algorithms and systems
- IoT, Cyber-Physical Systems (CPS), edge and fog computing for networked AI systems
- AI-enabled real time networking architectures and protocols for networked AI systems
- Enhanced intelligent networking techniques (e.g., slicing, placement, management, control, reconfiguration, virtualisation) for 5G and beyond
- Theoretical and/or experimental results addressing the predictability of networked AI systems
- Security and privacy for networked AI systems
- Data management, sharing, and sets for AI in networked AI systems
- Real-world deployment, diagnosis, evaluation and troubleshooting for networked AI systems
- Digital twin platforms enabled by networked AI systems
- On-device & multi-device AI
- Generative AI for networked AI systems
- Green network intelligence and sustainability for networked AI systems
- Real-world deployment and evaluation of AI in networked systems

[FULL PAPER SUBMISSIONS]
Solicited submissions include both full technical workshop papers and white position papers. The maximum length of such submissions is 6 pages (including references), and if accepted they will be published by ACM and appear in the ACM Digital Library.
Submission Deadline: April 5th, 2024 – 11:59 PM AOE
Author Notification: April 19th, 2024 – 11:59 PM AOE
For Submissions: https://netaisys24.hotcrp.com/

[WORK-IN-PROGRESS AND DEMO SUBMISSIONS]
Abstracts describing work-in-progress and demonstrations are also welcome and warmly encouraged. Submissions are limited to 2 pages (excluding references), and if accepted, included in the program as a short oral presentation – but will only be published on the workshop website (not on the ACM Digital Library). Deadlines for this informal track remain open even past the early registration deadline of MobiSys 2024; author notifications will be rolling (i.e., max. of 4 days after submission).

[Program Committee Chairs]
Roberto Morabito, EURECOM (FR)
SiYoung Jang, Nokia Bell Labs Cambridge (UK)
Ahmed M. A. Sayed, Queen Mary University of London (UK)

[Steering Committee]
Mallik Tatipamula (Ericsson)
Sasu Tarkoma (University of Helsinki)
Brahim Bensaou (Hong Kong University of Sci & Tech)
Fahim Kawsar (Nokia Bell Labs, University of Glasgow)

[Location]
Tokyo, Japan