Ubiquitous sensors and smart devices from factories and communities are generating
massive amounts of data, and ever-increasing computing power is driving the core of …

The Internet of Things (IoT) has created a ubiquitously connected world powered by a
multitude of wired and wireless sensors generating a variety of heterogeneous data over …

Driven by the emergence of new compute-intensive applications and the vision of the
Internet of Things (IoT), it is foreseen that the emerging 5G network will face an …

Federated learning (FL) offers distributed machine learning on edge devices. However, the
FL model raises privacy concerns. Various techniques, such as homomorphic encryption …

Infrastructure-assisted autonomous driving is an emerging paradigm that expects to
significantly improve the driving safety of autonomous vehicles. The key enabling …

Autonomous driving services depends on active sensing from modules such as camera,
LiDAR, radar, and communication units. Traditionally, these modules process the sensed …

With the development of smart devices, the computing capabilities of portable end devices
such as mobile phones have been greatly enhanced. Meanwhile, traditional cloud …

In recent years, Deep Neural Network (DNN) has been increasingly adopted by a wide
range of time-critical applications running on edge platforms with heterogeneous …

In recent years, deep learning algorithms are increasingly adopted by a wide range of data-
intensive and time-critical Internet of Things (IoT) applications. As a result, several new …

Many applications such as autonomous driving and augmented reality, require the
concurrent running of multiple deep neural networks (DNN) that poses different levels of real …