With the ever‐growing adoption of artificial intelligence (AI)‐based systems, the carbon
footprint of AI is no longer negligible. AI researchers and practitioners are therefore urged to …

Existing communication systems are mainly built based on Shannon's information theory,
which deliberately ignores the semantic aspects of communication. The recent iteration of …

Abstract The Cellular Internet of Things (CIoT) has seen significant growth in recent years.
With the deployment of 5G, it has become essential to reduce the power consumption of …

Federated learning methods offer secured monitor services and privacy-preserving
paradigms to end-users and organisations in the Internet of Things networks such as smart …

Federated learning (FL) enables collaborative model training among distributed devices
without data sharing, but existing FL suffers from poor scalability because of global model …

Real-time machine learning (ML) has recently attracted significant interest due to its
potential to support instantaneous learning, adaptation, and decision making in a wide …

Federated learning (FL) enables collaborative model training among distributed devices
without data sharing, but existing FL suffers from poor scalability because of global model …

Federated Learning (FL) mechanisms determine the implications of sensitive data for
constructing on-device Machine Learning (ML) to achieve personalisation in a smart …

Internet of Things (IoT) applications and services are becoming more prevalent in our
everyday life. However, such an interconnected network of intelligent physical entities needs …

Abstract Computing Power Network (CPN) is emerging as one of the important research
interests in beyond 5G (B5G) or 6G. This paper constructs a CPN based on Federated …