Cloud Computing, IoT, and Big Data: Technologies and Applications

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: closed (15 April 2025) | Viewed by 1078

Special Issue Editors


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Guest Editor
Ericsson Canada Inc., Ville Saint Laurent, QC H4S 0B6, Canada
Interests: cybersecurity; edge/cloud computing; SDN

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Guest Editor
Centre for Smart Analytics, Federation University Australia, Gippsland Campus, Churchill, VIC 3841, Australia
Interests: fog/edge computing; crowd computing; blockchain; next-generation computing

Special Issue Information

Dear Colleagues,

This Special Issue on "Cloud Computing, IoT, and Big Data: Technologies and Applications" aims to gather cutting-edge research and advancements in these inter-related fields. It will cover a broad spectrum of topics, including the latest developments in cloud infrastructure, innovative applications of IoT technologies, and sophisticated big data analytics techniques. Our goal is to provide a comprehensive platform for researchers and practitioners to share their findings, discuss challenges, and explore future directions in leveraging these technologies for various applications, from smart cities to healthcare and beyond. We invite original research articles, reviews, and case studies that contribute to the understanding and advancement of these dynamic areas.

Dr. Wajid Rafique
Dr. Sudheer Kumar Battula
Guest Editors

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Keywords

  • cloud computing
  • big data analytics
  • smart cities
  • data security and privacy
  • machine learning in cloud and IoT
  • edge computing
  • IoT applications
  • big data infrastructure
  • cloud services

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Published Papers (1 paper)

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Research

34 pages, 16501 KiB  
Article
Vehicle-to-Everything-Car Edge Cloud Management with Development, Security, and Operations Automation Framework
by DongHwan Ku, Hannie Zang, Anvarjon Yusupov, Sun Park and JongWon Kim
Electronics 2025, 14(3), 478; https://doi.org/10.3390/electronics14030478 - 24 Jan 2025
Viewed by 765
Abstract
Modern autonomous driving and intelligent transportation systems face critical challenges in managing real-time data processing, network latency, and security threats across distributed vehicular environments. Conventional cloud-centric architectures typically struggle to meet the low-latency and high-reliability requirements of vehicle-to-everything (V2X) applications, particularly in dynamic [...] Read more.
Modern autonomous driving and intelligent transportation systems face critical challenges in managing real-time data processing, network latency, and security threats across distributed vehicular environments. Conventional cloud-centric architectures typically struggle to meet the low-latency and high-reliability requirements of vehicle-to-everything (V2X) applications, particularly in dynamic and resource-constrained edge environments. To address these challenges, this study introduces the V2X-Car Edge Cloud system, which is a cloud-native architecture driven by DevSecOps principles to ensure secure deployment, dynamic resource orchestration, and real-time monitoring across distributed edge nodes. The proposed system integrates multicluster orchestration with Kubernetes, hybrid communication protocols (C-V2X, 5G, and WAVE), and data-fusion pipelines to enhance transparency in artificial intelligence (AI)-driven decision making. A software-in-the-loop simulation environment was implemented to validate AI models, and the SmartX MultiSec framework was integrated into the proposed system to dynamically monitor network traffic flow and security. Experimental evaluations in a virtual driving environment demonstrate the ability of the proposed system to perform automated security updates, continuous performance monitoring, and dynamic resource allocation without manual intervention. Full article
(This article belongs to the Special Issue Cloud Computing, IoT, and Big Data: Technologies and Applications)
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