Artificial Intelligence (AI) at the edge is the utilization of AI in real-world devices. Edge AI
refers to the practice of doing AI computations near the users at the network's edge, instead …

Fog computing is a paradigm that brings computational resources and services to the
network edge in the vicinity of user devices, lowering latency and connecting with cloud …

Mobile edge computing (MEC) is an emergent architecture where cloud computing services
are extended to the edge of networks leveraging mobile base stations. As a promising edge …

Due to the current structure of digital factory, it is necessary to build the smart factory to
upgrade the manufacturing industry. Smart factory adopts the combination of physical …

In recent years, the number of Internet of Things (IoT) devices/sensors has increased to a
great extent. To support the computational demand of real-time latency-sensitive …

Emerging technologies such as the Internet of Things (IoT) require latency-aware
computation for real-time application processing. In IoT environments, connected things …

With the rapid growth of Internet of Things (IoT) applications, the classic centralized cloud
computing paradigm faces several challenges such as high latency, low capacity and …

With the increasing advancement in the applications of the Internet of Things (IoT), the
integrated Cloud Computing (CC) faces numerous threats such as performance, security …

Fog computing is a paradigm that utilizes the advantages of both the cloud and the edge
devices providing quality services, reducing latency, providing mobility support, multi …

Contrary to using distant and centralized cloud data center resources, employing
decentralized resources at the edge of a network for processing data closer to user devices …