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 …

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

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

Autonomic computing investigates how systems can achieve (user) specified “control”
outcomes on their own, without the intervention of a human operator. Autonomic computing …

Fog computing is a paradigm that utilizes the advantages of both the cloud and the edge
devices providing quality services, reducing latency, providing mobility support, multi …

Structural health monitoring (SHM) and damage assessment of civil engineering
infrastructure are complex tasks. Structural health and strength of structures are influenced …

In recent times, the machine learning (ML) community has recognized the deep learning
(DL) computing model as the Gold Standard. DL has gradually become the most widely …

Cloud computing is a mainstay of modern technology, offering cost-effective and scalable
solutions to a variety of different problems. The massive shift of organization resource needs …

Abstract The United Nations (UN) 2030 Agenda makes it clear that growth and sustainable
management are not confined to cities, but also to those living in rural and villages. In …

Fog computing, as a distributed paradigm, offers cloud-like services at the edge of the
network with low latency and high-access bandwidth to support a diverse range of IoT …