Fog Computing has emerged as a pivotal technology for enabling low-latency, context-
aware, and efficient computing at the edge of the network. Effective task scheduling plays a …

Accurately quantifying plant available water capacity (PAWC) of soil is important for
maximising crop yields in dryland cropping systems, as PAWC positively correlates with crop …

The cloud-fog computing paradigm is a novel hybrid computing model that delivers
computational services to Fog nodes situated near data sources. This paradigm features a …

Face emotion recognition (FER) has found several applications across numerous industries.
One such application area lies in the field of human–computer interaction, where it can …

As the volume and velocity of Big Data continue to grow, traditional cloud computing
approaches struggle to meet the demands of real-time processing and low latency. Fog …

In light of the rapidly growing and advancing Internet of Things (IoT) technology, delay
sensitive tasks, deadline aware tasks, and power intensive IoT applications are on the rise …

The fog computing paradigm was introduced to overcome challenges that cannot be
addressed by conventional cloud computing, such as the lower response latency for real …

Virtualized fog–cloud computing (VFCC) has emerged as an optimal platform for processing
the increasing number of emerging Internet of Things (IoT) applications. VFCC resources …

The No Free Lunch theorem states that no single algorithm can universally serve as the best
solution for all optimization purposes. Consequently, it becomes imperative to adapt or …

Immediate response for real-time systems such as smart cities, autonomous vehicles,
healthcare, and industrial automation is supported by integrating Internet of Things (IoT) …