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  <doi_batch_id>aspg-2-3464-1791417177</doi_batch_id>
  <timestamp>20261007235257</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>Journal of Cybersecurity and Information Management</full_title>
    <abbrev_title>JCIM</abbrev_title>
    <issn media_type="print">2769-7851</issn>
    <issn media_type="electronic">2690-6775</issn>
   </journal_metadata>
   <journal_issue>
    <publication_date media_type="online">
     <year>2025</year>
    </publication_date>
    <journal_volume>
     <volume>15</volume>
    </journal_volume>
    <issue>2</issue>
   </journal_issue>
   <journal_article publication_type="full_text">
    <titles>
     <title>Efficient Deployment Approach in WSNs Using Heuristic Technique</title>
    </titles>
    <contributors>
     <person_name sequence="first" contributor_role="author">
      <given_name>Noor Ali</given_name>
      <surname>Abbas</surname>
      <affiliations>
       <institution>
        <institution_name>College of Science for Women-Computer Science Dept, University of Babylon, Babylon, Iraq</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Muhammed Abaid</given_name>
      <surname>Mahdi</surname>
      <affiliations>
       <institution>
        <institution_name>College of Science for Women-Computer Science Dept, University of Babylon, Babylon, Iraq</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Mahdi Abed</given_name>
      <surname>Salman</surname>
      <affiliations>
       <institution>
        <institution_name>College of Science for Women-Computer Science Dept, University of Babylon, Babylon, Iraq</institution_name>
       </institution>
      </affiliations>
     </person_name>
    </contributors>
    <jats:abstract>
     <jats:p>Several researchers have paid attention to designing deployment algorithms in WSNs. In fact, there are many different ways to deploy sensors in sensors' fields. Selecting one of them mainly is based on the application for which WSN design. However, two main factors should be considered when designing a deployment approach in WSN: coverage and connectivity. In this paper, we present a genetic algorithm (GA) to enhance the sensor deployment in WSNs while concurrently improving the coverage and connectivity rate. The most popular deployment approach is to deploy sensor nodes randomly in the field. Although this approach is simple and easy, it may not achieve good results. In the proposed GA algorithm, the metaheuristic algorithm is used to deploy sensors. Simulations demonstrate that GA achieves a good deployment result compared to other research papers by ensuring maximum network coverage and connectivity rate by achieving efficient coverage and connectivity.</jats:p>
    </jats:abstract>
    <publication_date media_type="online">
     <year>2025</year>
    </publication_date>
    <pages>
     <first_page>322</first_page>
     <last_page>330</last_page>
    </pages>
    <publisher_item>
     <item_number item_number_type="article-number">3464</item_number>
    </publisher_item>
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     <ai:license_ref applies_to="vor">https://creativecommons.org/licenses/by/4.0/</ai:license_ref>
    </ai:program>
    <doi_data>
     <doi>10.54216/JCIM.150224</doi>
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