Editorial

AI-enabled Systems in Edge-cloud Environments

Abstract

In the era of artificial intelligence (AI), smart devices such as autonomous vehicles, drones, and service robots are increasingly collaborating to perform complex tasks for humans. However, the centralized control and optimiza- tion of these widely distributed devices suffer from significant scalability limitations. At the same time, traditional cloud infrastructures are struggling to meet the demands of collecting and processing massive volumes of data from countless devices, often leading to increased latency and reduced service responsiveness.

To address these challenges, edge-cloud computing has emerged as a promising infrastructure that enhances efficiency, scalability, and data privacy for delivering data-centric, AI-enabled services. In an edge-cloud ecosystem, multiple computing tiers – including edge devices, fog nodes, and centralized clouds – collaborate to support data collection, processing, and decision- making closer to data sources. These tiers must coordinate dynamically, considering available computing resources while ensuring service quality, safety, and accuracy.