In recent times, the Internet of Things (IoT) applications, including smart transportation, smart
healthcare, smart grid, smart city, etc. generate a large volume of real-time data for decision …

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 …

With the rise in Internet of Things (IoT) technology in recent years the amount of resource
requirement of various IoT applications substantially increases. The data generated by …

The Internet of Things (IoT) paradigm is being rapidly adopted for the creation of smart
environments in various domains. The IoT-enabled cyber-physical systems associated with …

With the increasing use of the Internet of Things (IoT) in various fields and the need to
process and store huge volumes of generated data, Fog computing was introduced to …

This work presents a novel Evolutionary Quantum Neural Network (EQNN) based workload
prediction model for Cloud datacenter. It exploits the computational efficiency of quantum …

Due to recent advancements in quantum drones, the Internet of Quantum Drones (IoQDs),
and Drone-to-Satellite connectivity, several advantages have been anticipated for real-time …

With the advent of the Internet of Things (IoT) paradigm, the cloud model is unable to offer
satisfactory services for latency‐sensitive and real‐time applications due to high latency and …

Internet of Things (IoT) is defined as the interconnection of millions of wireless devices to
acquire data in a ubiquitous manner. With multiple devices targeting to perceive data over a …

Due to increased use of IoT devices and data sensors a huge amount of data is being
produced for processing in real‐time. Fog computing has evolved as a solution for fast …