Arvind Dhaka: Associate Professor, Manipal University Jaipur, India
Gang Wu: University of Electronic Science and Technology of China, China
Weidang Lu: Zhejiang University of Technology, China
Imran Shafique Ansari: University of Glasgow, UK
Submission Status: Closed | Submission Deadline: Closed
This collection is no longer accepting submissions
EURASIP Journal on Wireless Communications and Networking is calling for submissions to our Collection Secure and Energy-Efficient Federated Learning over Wireless Networks: Cooperative Vehicle Infrastructure System.
The purpose of this call for papers is to solicit original research contributions on secure and energy-efficient federated learning over wireless networks. Federated learning, a rapidly growing field of study, is an approach to machine learning (ML) that allows data to remain on its original source while still being accessible for centralized training. Federated learning is becoming increasingly popular due to its ability to provide ML solutions without the need to collect, store and share data across multiple sites. Federated learning over wireless networks employs advanced encryption techniques to ensure secure transfer of data between the participants. The use of wireless communication networks ensures that the energy consumption of the distributed devices is minimized. Federated learning over wireless networks can easily scale up as the number of devices connected to the network increases. This ensures that the system is able to handle large amounts of data efficiently without any degradation in performance. Wireless networks are a popular choice for federated learning deployments, as they enable the sharing of data between multiple nodes and allow for dynamic reconfiguration. However, federated learning over wireless networks faces several security and energy efficiency challenges. On the security front, wireless networks are prone to attack, and network nodes must be secured to protect the data and ML models. On the energy efficiency front, the wireless network must be designed to reduce energy consumption while still providing a reliable and secure service.