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PSO‐FRL: A Hybrid Optimization and Adaptation Approach for Task Scheduling in Edge Enabled Sensor Networks

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Bibliographic Details
Published in:Internet Technology Letters
Format: Online Article RSS Article
Published: 2026
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container_title Internet Technology Letters
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discipline_display Computer Science
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institution FRELIP
journal_source_facet Internet Technology Letters
last_indexed 2026-06-17T02:03:19.776Z
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle PSO‐FRL: A Hybrid Optimization and Adaptation Approach for Task Scheduling in Edge Enabled Sensor Networks
Computer Science
General
Computer Science
sub_discipline_display General
sub_discipline_facet General
subject_display Computer Science
General
Computer Science
Computer Science
General
Computer Science
subject_facet Computer Science
General
Computer Science
title PSO‐FRL: A Hybrid Optimization and Adaptation Approach for Task Scheduling in Edge Enabled Sensor Networks
title_auth PSO‐FRL: A Hybrid Optimization and Adaptation Approach for Task Scheduling in Edge Enabled Sensor Networks
title_full PSO‐FRL: A Hybrid Optimization and Adaptation Approach for Task Scheduling in Edge Enabled Sensor Networks
title_fullStr PSO‐FRL: A Hybrid Optimization and Adaptation Approach for Task Scheduling in Edge Enabled Sensor Networks
title_full_unstemmed PSO‐FRL: A Hybrid Optimization and Adaptation Approach for Task Scheduling in Edge Enabled Sensor Networks
title_short PSO‐FRL: A Hybrid Optimization and Adaptation Approach for Task Scheduling in Edge Enabled Sensor Networks
title_sort pso‐frl: a hybrid optimization and adaptation approach for task scheduling in edge enabled sensor networks
topic Computer Science
General
Computer Science
url https://onlinelibrary.wiley.com/doi/10.1002/itl2.70298?af=R