IEEE ICCC 2023 Workshop on
Edge Intelligence for 6G Networks
Dalian, China|10-12 August 2023
Scope: The six generation (6G) networks are expected to accommodate a huge number of mobile devices, and provision low latency and context-aware intelligent applications to mobile users in a flexible and efficient manner. To support intelligent applications, such as autonomous driving, smart city surveillance, and VR/AR, cloud services are expected to be pushed to the proximity of mobile devices for service quality assurance. For instance, to facilitate safe autonomous driving, the service delay of most vehicular applications is required to be within milliseconds. Edge intelligence aims to process data/computing intensive tasks at the network edge, where a set of mobile devices can work cooperatively for data collection and processing, task offloading, model training/inference, data analytics via edge caching and training, etc. However, edge intelligence systems have to deal with potential challenges. The systems should support various intelligent applications with distinct QoS requirements in terms of latency, reliability, and accuracy. In addition, the service demands exhibit spatial and temporary dynamics due to traffic burstiness and user mobility. It is of importance to manage the communication, computing, and memory/storage resources which jointly affect the perceived user performance.
Topics:
- Performance analysis of edge intelligence systems
- Joint optimization of heterogeneous resources
- Digital twin-assisted edge intelligence
- Edge intelligence for industrial IoT
- SDN/NFV-assisted edge intelligence
- Network slicing for edge intelligence
- Task offloading for intelligent applications
- End-edge-cloud interplay
- Green edge intelligence systems
- Architecture for edge intelligence systems
- Protocols for edge intelligence systems
- Security and privacy in edge intelligence systems
- Distributed learning in edge intelligence systems
- Data analytics assisted edge intelligence systems
Organizing Committee
General Co-Chairs:
- Qiang Ye, Memorial University, Canada
- Ning Zhang, University of Windsor, Canada
- Jun Cai, Concordia University, Canada
- Ning Lu, Queens University, Canada
- Octavia A. Dobre, Memorial University, Canada
Technical Program Co-Chairs:
- Wen Wu, Peng Cheng Laboratory, China
- Peng Yang, HUST, China
- Qihao Li, Jilin University, China
- Haixia Peng, Xi’an Jiaotong University, China
- Shaohua Wu, Harbin Institute of Technology (Shenzhen), China
- Dong Yang, Beijing Jiaotong University, China
Keynote Speakers:
- Prof. Yan Zhang, University of Oslo, Norway
- Prof. Ping Wang, York University, Canada
- Prof. Yu Cheng, Illinois Institute of Technology, USA
Submission Procedure:
Authors are invited to submit original papers of no more than 6 pages (standard IEEE proceedings, two-column, 10 pt font, etc.), including figures, tables, and references, in PDF format. EDAS submission Link: https://ieeeiccc2023workshops.edas.info/
