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 …

Recent years have disclosed a remarkable proliferation of compute-intensive applications in
smart cities. Such applications continuously generate enormous amounts of data which …

Mobile Edge Computing (MEC) pushes computing functionalities away from the centralized
cloud to the network edge, thereby meeting the latency requirements of many emerging …

The ever-increasing number of resource-constrained machine-type communication (MTC)
devices is leading to the critical challenge of fulfilling diverse communication requirements …

Multi-access Edge Computing (MEC) is a key solution that enables operators to open their
networks to new services and IT ecosystems to leverage edge-cloud benefits in their …

Multi-access mobile edge computing (MEC), which enables mobile users (MUs) to offload
their computation-workloads to the computation-servers located at the edge of cellular …

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 …

In vehicular networks, in-vehicle user equipment (UE) with limited battery capacity can
achieve opportunistic energy saving by offloading energy-hungry workloads to vehicular …

Driven by the explosive data traffic and new quality of service requirement of mobile users,
the communication industry has been experiencing a new evolution by means of network …

Mobile Edge Computing (MEC) pushes computing functionalities away from the centralized
cloud to the proximity of data sources, thereby reducing service provision latency and saving …