Edge computing applications leverage advances in edge computing along with the latest
trends of convolutional neural networks in order to achieve ultra-low latency, high-speed …

With the continuous growth of the Internet of Things applications, increasingly sophisticated
and malicious network security attacks have been posing new security requirements. One of …

Network resources and traffic priorities can be utilized to distribute requested tasks across
edge nodes at the edge layer. However, due to the variety of tasks, the edge nodes have an …

It is now very important to adopt and continue to improve on the technologies that support
the ideas of smart management of energy and integration of renewable energy into the …

With the advancement of Internet of Things (IoT) technology, IoT smart devices (ISDs) are
often frequently constrained by their battery capability and computing ability. In mobile edge …

This article introduces a novel distributed model for handling in real-time, edge-based
Artificial Intelligence analytics, such as the ones required for smart video surveillance. The …

Federated learning is an innovative machine learning technique that enables the
collaborative training of a model on diverse datasets from multiple independent devices. By …

Edge computing is a novel and potential computing model which moves storage and
computing capabilities to the network edge, substantially decreasing service latency and …

Edge computing is a revolutionary approach that enables processing and decision-making
in close proximity to data sources, reducing latency and optimizing bandwidth usage. This …

Recent advancements in network-connected devices have led to a rapid increase in the
deployment of smart devices and enhanced grid connectivity, resulting in a surge in data …