Since the popularisation of the Internet in the 1990s, the cyberspace has kept evolving. We
have created various computer-mediated virtual environments, including social networks …

Deep learning is currently widely used in a variety of applications, including computer vision
and natural language processing. End devices, such as smartphones and Internet-of-Things …

Sixth generation (6G) enabled edge intelligence opens up a new era of Internet of
everything and makes it possible to interconnect people-devices-cloud anytime, anywhere …

Abstract With the Internet of Things (IoT) becoming part of our daily life and our environment,
we expect rapid growth in the number of connected devices. IoT is expected to connect …

Most existing Augmented Reality (AR) and Mixed Reality (MR) systems are able to
understand the 3D geometry of the surroundings but lack the ability to detect and classify …

We are living in a world where massive end devices perform computing everywhere and
everyday. However, these devices are constrained by the battery and computational …

With the development of recent innovative applications (eg, augment reality, self-driving, and
various cognitive applications), more and more computation-intensive and data-intensive …

Due to the limited computing resource and battery capability at the mobile devices, the
computation-intensive tasks generated by mobile devices can be offloaded to edge servers …

The ultra-low latency requirements of 5G/6G applications and privacy constraints call for
distributed machine learning systems to be deployed at the edge. With its simple yet …

Operating data-intensive applications on edge systems is challenging, due to the extreme
workload and device heterogeneity, as well as the geographic dispersion of compute and …