Workshop on Integrating Edge Intelligence and Large Model in Next Generation Networks (IEILM) - Call for Papers

Scope and topics:

Edge Intelligence and Large Model in next generation networks are closely related to the increasing convergence of networking, artificial intelligence, and cloud-edge technologies. As cloud-edge computing gains momentum, the demand for intelligent, context-aware, and efficient networking solutions is rising. The integration of edge intelligence and large models enables networks to become more adaptive, self-optimizing, and responsive to user and application needs.

The Workshop on "Integrating Edge Intelligence and Large Models in Next Generation Networks" provides a forum that brings together industry and academia, engineers, and researchers to discuss up-to-date developments in integrating edge intelligence and large models in Large AI models. The workshop invites submissions of unpublished works on (but not limited to) the following topics:

• End-to-end semantic communication systems
• Microdata cells/centers for integrating edge intelligent and semantic communications
• Large AI models for multi-task intelligent mobile edge computing
• Distributed learning architectures for semantic communications
• Generative AI for next generation networks
• Architectures and protocols for integrating semantic and large models
• Designs and optimizations for integrating semantic and large models
• Energy-efficient hardware, software, networks and services with edge intelligence
• Integrating edge intelligence and large models in future networks
• Cache-enabled networks with semantic communications
• Large models for multimedia services
• Network functions virtualization (NFV) for cloud-edge networks
• Efficient reasoning of large models by Edge Intelligence
• Deploying large models for cloud-edge networking
• Distributed and power-efficient training of large models in wireless networks
• The role of semantic communications/large models in emerging 6G applications
• Edge intelligent systems for semantic communication Networks
• Signal processing for integrating semantic communications
• Information-centric and content-centric networks with large models
• Interdisciplinary research for integrating edge intelligence/large models
• Information theory for integrating semantic communications, and large models
• Personalization of FL with large models in cloud-edge networks
• Overcoming data interoperability challenges using large models in cloud-edge networks
• System architectures for inference and training in cloud-edge networks
• Training on cloud/heterogeneous infrastructure with large models

Paper submission

Submitted papers must represent original material which is not currently under review in any other conference or journal and has not been previously published. Paper length should not exceed six-page standard IEEE conference two-column format (including all text, figures, and references). Please see the Author Information page for submission guidelines in the IEEE INFOCOM 2024. All submitted papers will go through a peer review process. All accepted and presented papers will be included in the IEEE INFOCOM 2024 proceedings and IEEE Xplore. IEEE reserves the right to exclude an accepted and registered but not presented paper from the IEEE digital library. Please follow the submission link on https://edas.info/N31772 to submit your paper.