The advent of the 6G era aims for ubiquitous connectivity, with the integration of non-
terrestrial networks (NTN) offering extensive coverage and enhanced capacity. As …

Multi-access edge computing (MEC) has recently been proposed to aid mobile end devices
in providing compute-and data-intensive services with low latency. Growing service …

In federated learning (FL), devices contribute to the global training by uploading their local
model updates via wireless channels. Due to limited computation and communication …

The metaverse is regarded as a new wave of technological transformation that provides a
virtual space for people to interact through digital avatars. To achieve immersive user …

Federated learning (FL) is a new technology that has been a hot research topic. It enables
the training of an algorithm across multiple decentralized edge devices or servers holding …

Recent medical applications are largely dominated by the application of Machine Learning
(ML) models to assist expert decisions, leading to disruptive innovations in radiology …

We consider the problem of massive matrix multiplication, which underlies many data
analytic applications, in a large-scale distributed system comprising a group of worker …

How can we optimally trade extra computing power to reduce the communication load in
distributed computing? We answer this question by characterizing a fundamental tradeoff …