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 …

Resource management in computing is a very challenging problem that involves making
sequential decisions. Resource limitations, resource heterogeneity, dynamic and diverse …

Artificial intelligence (AI) technologies have emerged as pivotal enablers across a multitude
of industries, including consumer electronics, healthcare, and manufacturing, largely due to …

The digital landscape of the Internet of Energy (IoE) is on the brink of a revolutionary
transformation with the integration of edge Artificial Intelligence (AI). This comprehensive …

Over the past six decades, the computing systems field has experienced significant
transformations, profoundly impacting society with transformational developments, such as …

Abstract Edge Artificial Intelligence (AI) incorporates a network of interconnected systems
and devices that receive, cache, process, and analyse data in close communication with the …

The Edge Intelligence (EI) paradigm has recently emerged as a promising solution to
overcome the inherent limitations of cloud computing (latency, autonomy, cost, etc.) in the …

Edge artificial intelligence (AI) is an innovative computing paradigm that aims to shift the
training and inference of machine learning models to the edge of the network. This paradigm …

As a specific category of artificial intelligence (AI), generative artificial intelligence (GenAI)
generates new content that resembles what humans create. The rapid development of …

Future AI applications require performance, reliability and privacy that the existing, cloud-
dependant system architectures cannot provide. In this article, we study orchestration in the …