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 …

Cloud computing with its three key facets (ie, Infrastructure-as-a-Service, Platform-as-a-
Service, and Software-as-a-Service) and its inherent advantages (eg, elasticity and …

Context: A fog computing architecture that is geographically distributed and to which a
variety of heterogeneous devices are ubiquitously connected at the end of a network in …

Recently much emphasize is given on integrating Edge, Fog and Cloud infrastructures to
support the execution of various latency sensitive and computing intensive Internet of Things …

The digital world is expanding rapidly and advances in networking technologies such as 4G
long-term evolution (LTE), wireless broadband (WiBro), low-power wide area networks …

The exponential growth in Internet of Things (IoT) devices and the limitations of cloud
computing in terms of latency and quality of service for time-sensitive applications have led …

The world is witnessing an unprecedented growth of cyber-physical systems (CPS), which
are foreseen to revolutionize our world via creating new services and applications in a …

In recent years, fog computing has emerged as a computing paradigm to support the
computationally intensive and latency-critical applications for resource limited Internet of …

Fog computing is an architectural style in which network components between devices and
the cloud execute application-specific logic. We present the first review on fog computing …

The Internet of Things (IoT) paradigm holds significant promises for remote health
monitoring systems. Due to their life-or mission-critical nature, these systems need to …