Federated Learning (FL) is an emerging Artificial Intelligence (AI) paradigm enabling
multiple parties to train a model collaboratively without sharing their data. With the upcoming …

Crowdsensing has received widespread attention in recent years. It is extensively employed
in smart cities and intelligent transportation systems. This paper comprehensively surveys …

Federated learning (FL) is widely regarded as highly promising because it enables the
collaborative training of high-performance machine learning models among a large number …

The Passive Optical Network (PON) has been evolving continuously in terms of architecture
and capacity to keep up with the demand for high-speed Internet access in the access …

With the advent of 6G technology, the proliferation of interconnected devices necessitates a
robust, fully connected intelligence network. Federated Learning (FL) stands as a key …

Large Language Models (LLMs) have revolutionized natural language processing tasks.
However, their deployment in wireless networks still face challenges, ie, a lack of privacy …

The 5 G networks are effectively deployed worldwide, and academia and industries have
begun looking at 6 G network communication technology for consumer electronics …

This paper proposes a novel three tier architecture for federated learning to optimize edge
computing environments. The proposed architecture addresses the challenges associated …

The advent of pervasive computing and ambient intelligence has opened up new
possibilities for the development of intelligent systems that can adapt to the needs of their …

As a novel form of infrastructure, 6G is poised to become an indispensable component of the
future digital economy and serves as a solid guarantee for the development of human …