Call for papers: Cloud, fog, and edge computing technologies

This Collection invites submissions of original research into techniques that facilitate the deployment of cloud, fog, and edge computing technologies, driving advancements in efficient data processing and storage across diverse network environments.

Published in Computational Sciences

Call for papers: Cloud, fog, and edge computing technologies
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Collection Overview

Scientific Reports has launched a Guest-Edited Collection on Cloud, fog, and edge computing technologies.

Cloud, fog, and edge computing are essential for optimizing data processing and storage in modern networks, requiring innovative solutions to enhance efficiency and performance. These technologies distribute computing resources across various layers, from centralized cloud servers to localized edge devices, ensuring faster data processing and reduced latency. The focus for cloud, fog, and edge computing lies in developing robust architectures and frameworks that can seamlessly integrate these layers, providing significant improvements in scalability, reliability, and real-time data handling.

This will be a Collection of original research papers and will be open for submissions from all authors – on the condition that the manuscripts fall within the scope of the Collection and of Scientific Reports more generally. We are welcoming submissions until 28th February 2026.

Why is this Collection important? 

"This call provides an opportunity for the authors to submit their original research about techniques that facilitate the deployment of cloud, fog, and edge computing technologies, driving advancements in efficient data processing and storage across diverse network environments. Currently, cloud, fog, and edge computing technologies are employed in various services and are essential for optimising data processing and storage in modern networks, which require innovative solutions to enhance efficiency and performance. This presents a valuable opportunity for researchers to publish their outstanding research as open access with a leading publisher, allowing readers to access it for further advancements and impact." - Sukhpal Singh Gill

"The topic is relevant because it deals with technologies that are changing modern information systems. Distributed technologies in the Cloud, in the Fog and at the Edge improve scalability, reliability, and performance, and their integration in a compute continuum facilitates global accessibility and cost-efficiency. However, many issues need to be investigated for their massive and worldwide adoption." - Maria Fazio

Why submit to a Collection? 

Collections like this one help promote high-quality science. They are led by Guest Editors, who are experts in their fields, and In-House Editors and are supported by a dedicated team of Commissioning Editors and Managing Editors at Springer Nature. Collection manuscripts typically see higher citations, downloads, and Altmetric scores, and provide a one-stop-shop on a cutting-edge topic of interest. 

Who is involved? 

Guest Editors:

  • Maria Fazio, University of Messina, Italy
  • Sukhpal Singh Gill, Queen Mary University of London, UK
  • Mohit Kumar, Dr B R Ambedkar NIT Jalandhar, India

Internal Team:

  • In-House Editor: Dr. Thomas TischerScientific Reports, Germany
  • Commissioning Editor: Faija Miah, Fully OA Brands, Springer Nature, UK
  • Managing Editor: Sarah Jane Hunt, Fully OA Brands, Springer Nature, UK

How can I submit my paper? 

Visit the Collection page to find out more about this collection and submit your article.

Please sign in or register for FREE

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Follow the Topic

Cloud Computing
Mathematics and Computing > Computer Science > Computer Engineering and Networks > Cloud Computing
Computer and Information Systems Applications
Mathematics and Computing > Computer Science > Computer and Information Systems Applications
Computer Application in Administrative Data Processing
Mathematics and Computing > Computer Science > Computer and Information Systems Applications > Computer Application in Administrative Data Processing

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