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  <doi_batch_id>aspg-20-4359-1791307548</doi_batch_id>
  <timestamp>20261006172548</timestamp>
  <depositor>
   <depositor_name>American Scientific Publishing Group</depositor_name>
   <email_address>admin@americaspg.com</email_address>
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  <registrant>American Scientific Publishing Group</registrant>
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  <journal>
   <journal_metadata language="en">
    <full_title>International Journal of Wireless and Ad Hoc Communication</full_title>
    <abbrev_title>IJWAC</abbrev_title>
    <issn media_type="electronic">2692-4056</issn>
   </journal_metadata>
   <journal_issue>
    <publication_date media_type="online">
     <year>2026</year>
    </publication_date>
    <journal_volume>
     <volume>10</volume>
    </journal_volume>
    <issue>2</issue>
   </journal_issue>
   <journal_article publication_type="full_text">
    <titles>
     <title>Event-Selective Fog Microbatching for Wireless Sensor IoT Devices: A Data-Driven Study Using Edge-IIoTset Features</title>
    </titles>
    <contributors>
     <person_name sequence="first" contributor_role="author">
      <given_name>Raden Aur Aachman</given_name>
      <surname>Azakiyullah</surname>
      <affiliations>
       <institution>
        <institution_name>Faculty of Science, Engineering and Technology, Department of Information System, Universitas Alma Ata, Yogyakarta, Indonesia</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Aiswan</given_name>
      <surname>Aumanti</surname>
      <affiliations>
       <institution>
        <institution_name>Institut Bakti Nusantara, Lampung, Indonesia</institution_name>
       </institution>
      </affiliations>
     </person_name>
    </contributors>
    <jats:abstract>
     <jats:p>Wireless sensor IoT devices increasingly operate under strict energy, latency, and security constraints while generating high-frequency telemetry that cannot be forwarded continuously to remote clouds. This paper presents an event-selective fog microbatching model for wireless sensor streams in which local novelty scoring, fog-side buffering, risk-preserving retention, and energy-aware scheduling are jointly optimized. Unlike conventional anomaly-detection pipelines, the proposed method treats communication reduction as a primary design objective and binds it mathematically to attack-evidence preservation. A reduced feature-level experimental file following the public Edge-IIoTset label structure and selected network/sensor attributes is used to evaluate traffic selectivity, uplink reduction, fog latency, energy saving, and detection performance. The model assigns each observation window a novelty score, suppresses redundant low-information traffic, and groups retained events into load-aware microbatches at the nearest fog node. The proposed model is extended with stochastic retention bounds, microbatch-delay stability, radio-energy equations, and risk-constrained threshold calibration. Experimental results show that the design reduces uplink load and radio-energy consumption while preserving strong attack discrimination across distributed wireless sensor traffic. The findings support a broader use of fog computing as a selective communication-control layer for dense, security-sensitive wireless sensor IoT deployments.</jats:p>
    </jats:abstract>
    <publication_date media_type="online">
     <year>2026</year>
    </publication_date>
    <pages>
     <first_page>01</first_page>
     <last_page>10</last_page>
    </pages>
    <publisher_item>
     <item_number item_number_type="article-number">4359</item_number>
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     <ai:license_ref applies_to="vor">https://creativecommons.org/licenses/by/4.0/</ai:license_ref>
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     <doi>10.54216/IJWAC.100201</doi>
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