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 …

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 …

The Internet is evolving rapidly toward the future Internet of Things (IoT) which will potentially
connect billions or even trillions of edge devices which could generate huge amount of data …

MEC is an emerging paradigm that provides computing, storage, and networking resources
within the edge of the mobile RAN. MEC servers are deployed on a generic computing …

The boom in the capabilities and features of mobile devices, like smartphones, tablets, and
wearables, combined with the ubiquitous and affordable Internet access and the advances …

Despite the increasing usage of cloud computing, there are still issues unsolved due to
inherent problems of cloud computing such as unreliable latency, lack of mobility support …

The performance of mobile computing would be significantly improved by leveraging cloud
computing and migrating mobile workloads for remote execution at the cloud. In this paper …

Along the trend pushing computation from the network core to the edge where the most of
data are generated, edge computing has shown its potential in reducing response time …

Deep learning models are being deployed in many mobile intelligent applications. End-side
services, such as intelligent personal assistants, autonomous cars, and smart home services …

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 …