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Leveraging Lightweight Machine Learning for RF Jamming Detection in Mobile ad-hoc Networks: A Three-Tier Edge-Fog-Cloud Computing Approach

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Published in:Cybernetics and Information Technologies
Format: Online Article RSS Article
Published: 2026
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container_title Cybernetics and Information Technologies
description
discipline_display Technology & Engineering
discipline_facet Technology & Engineering
format Online Article
RSS Article
genre Journal Article
id rss_article:25786
institution FRELIP
journal_source_facet Cybernetics and Information Technologies
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Leveraging Lightweight Machine Learning for RF Jamming Detection in Mobile ad-hoc Networks: A Three-Tier Edge-Fog-Cloud Computing Approach
Internet
Technology & Engineering — Computing
Technology & Engineering
sub_discipline_display Technology & Engineering — Computing
sub_discipline_facet Technology & Engineering — Computing
subject_display Internet
Technology & Engineering — Computing
Technology & Engineering
Internet
Technology & Engineering — Computing
Technology & Engineering
subject_facet Internet
Technology & Engineering — Computing
Technology & Engineering
title Leveraging Lightweight Machine Learning for RF Jamming Detection in Mobile ad-hoc Networks: A Three-Tier Edge-Fog-Cloud Computing Approach
title_auth Leveraging Lightweight Machine Learning for RF Jamming Detection in Mobile ad-hoc Networks: A Three-Tier Edge-Fog-Cloud Computing Approach
title_full Leveraging Lightweight Machine Learning for RF Jamming Detection in Mobile ad-hoc Networks: A Three-Tier Edge-Fog-Cloud Computing Approach
title_fullStr Leveraging Lightweight Machine Learning for RF Jamming Detection in Mobile ad-hoc Networks: A Three-Tier Edge-Fog-Cloud Computing Approach
title_full_unstemmed Leveraging Lightweight Machine Learning for RF Jamming Detection in Mobile ad-hoc Networks: A Three-Tier Edge-Fog-Cloud Computing Approach
title_short Leveraging Lightweight Machine Learning for RF Jamming Detection in Mobile ad-hoc Networks: A Three-Tier Edge-Fog-Cloud Computing Approach
title_sort leveraging lightweight machine learning for rf jamming detection in mobile ad-hoc networks: a three-tier edge-fog-cloud computing approach
topic Internet
Technology & Engineering — Computing
Technology & Engineering
url https://sciendo.com/article/10.2478/cait-2026-0005