Recent years have witnessed the widespread popularity of Internet of things (IoT). By
providing sufficient data for model training and inference, IoT has promoted the development …

The explosive growth of the Internet of Things (IoT) applications has imposed a dramatic
increase of network data and placed a high computation complexity across various …

As a new paradigm, fog computing (FC) has several characteristics that set it apart from the
cloud computing (CC) environment. Fog nodes and edge computing (EC) hosts have limited …

Facial expression recognition (FER) is embedded in many real-world human-computer
interaction tasks, such as online learning, depression recognition and remote diagnosis …

With the gradual opening of the electricity sales market, distributed energy trading is
becoming an important research topic. However, it is not easy to design practical energy …

Distributed edge intelligence is a disruptive research area that enables the execution of
machine learning and deep learning (ML/DL) algorithms close to where data are generated …

Privacy leakage is one of the most critical issues in machine learning and has attracted
growing interest for tasks such as demonstrating potential threats in model attacks and …

Intrusion detection systems are widely implemented to protect computer networks from
threats. To identify unknown attacks, many machine learning algorithms like neural networks …

Edge of Things (EoT) enables the seamless transfer of services, storage, and data
processing from the cloud layer to edge devices in a large-scale distributed Internet of …

Abstract Edge-of-Things (EoT) is a new evolving computing model driven by the Internet of
Things (IoT). It enables data processing, storage, and service to be shifted from the Cloud to …