Scope and Topics of the Workshop
To satisfy the diverse multi-dimension quality of service (QoS), such as enhanced broadband, ultra-reliable and low latency, and massive connections, a paradigm of fog computing-based radio access network (F-RAN) has been proposed as a promising evolution path for the future wireless network architecture. By integrating the fog computing resource into wireless networks, a part of service requirements can be handled locally, which provide great flexibility to satisfy QoS requirements of various application scenarios. Due to the great potential, F-RAN has become a research hotspot, and draws a lot of attention from both academia and industry.
As the permeation of artificial intelligence (AI) in wireless application, some data-driven and computing-intensive services are emerging, such as mobile high-definition AR/VR, and real-time fingertip interaction. To support the user experience of these services, the procedures of data transmission and service implementation should be coupled tightly. Therefore, it requires the fusion of AI and big data to enable the intelligent wireless networks. The target of network edge intelligence should be achieved to avoid feedback overloading and user privacy issues, which can be fully support by F-RANs. However, the existing works are mainly focus on the centralized AI paradigms, which are not applicable in network edge intelligence scenarios. Therefore, some new data-level distributed AI mechanisms, such as federated learning, are studied, and has become the future trends of intelligent wireless networks, especially with respect to the paradigm of F-RAN.
This workshop will focus on the state-of-art protocols, techniques and applications of network edge intelligence in F-RAN. The aim of this workshop is to share and discuss recent advances and future trends of network edge intelligence in F-RANs, and to bring academic researchers and industry developers together. The topics of interest include, but are not limited to the following:
- Edge intelligence-enabled network architecture and protocol design for F-RAN
- Edge computing-based AI paradigm and algorithm design in F-RAN
- Information-theoretic modeling and analysis of network intelligence in F-RAN
- Integration of computation, communication, and storage resources for edge intelligence in F-RAN
- Distributed multi-dimension resource management and cross-layer design in F-RAN
- Security and privacy issues for edge intelligence in F-RAN
- Prototype and test-bed for edge intelligence in F-RAN
The submitted papers should be original, not published or currently under review for publications in any other journal or conference. All submission must be formatted in standard IEEE camera-ready format and must be written in English and be at most six (6) printed papers in length, including figures. Papers should be submitted through EDAS System.
EDAS submission link: https://edas.info/newPaper.php?c=25822&track=96933
Workshop paper submission deadline: 15 May 2019
Workshop paper decision date: 25 June 2019
Zhongyuan Zhao, Beijing University of Posts and Telecommunications, China,
Zhiyong Chen, Shanghai Jiao Tong University, China
Yuanwei Liu, Queen Mary University of London, UK