  <?xml version="1.0"?>
<journal>
 <journal_metadata>
  <full_title>Journal of Intelligent Systems and Internet of Things</full_title>
  <abbrev_title>JISIoT</abbrev_title>
  <issn media_type="print">2690-6791</issn>
  <issn media_type="electronic">2769-786X</issn>
  <doi_data>
   <doi>10.54216/JISIoT</doi>
   <resource>https://www.americaspg.com/journals/show/3602</resource>
  </doi_data>
 </journal_metadata>
 <journal_issue>
  <publication_date media_type="print">
   <year>2019</year>
  </publication_date>
  <publication_date media_type="online">
   <year>2019</year>
  </publication_date>
 </journal_issue>
 <journal_article publication_type="full_text">
  <titles>
   <title>Efficient CH selection for Traffic Congestion Reduction and To Improve Network Connectivity in Vehicular Adhoc Networks</title>
  </titles>
  <contributors>
   <organization sequence="first" contributor_role="author">Department of Computer Sciences, College of Science, University of Al Maarif, Al Anbar,31001, Iraq</organization>
   <person_name sequence="first" contributor_role="author">
    <given_name>Mohammed</given_name>
    <surname>Mohammed</surname>
   </person_name>
   <organization sequence="first" contributor_role="author">Department of Electrical Engineering, College of Engineering, University of Anabr, Ramadi, Iraq</organization>
   <person_name sequence="additional" contributor_role="author">
    <given_name>Ahmed Jamal</given_name>
    <surname>Ahmed</surname>
   </person_name>
   <organization sequence="first" contributor_role="author">Department of Computer science , College of Science, University of diyala, Diyala, Iraq</organization>
   <person_name sequence="additional" contributor_role="author">
    <given_name>Hazim Noman</given_name>
    <surname>Abed</surname>
   </person_name>
   <organization sequence="first" contributor_role="author">Department of Computer Sciences, College of Science, University of Al Maarif, Al Anbar,31001, Iraq</organization>
   <person_name sequence="additional" contributor_role="author">
    <given_name>Mahmood</given_name>
    <surname>AlSaadi</surname>
   </person_name>
  </contributors>
  <jats:abstract xml:lang="en">
   <jats:p>Vehicular ad hoc network (VANET) is an innovative technology that has attracted many researchers and the industrial sector. The increase in vehicle movement and the requirement for effective traffic management systems have resulted in the development of VANETs. The Super Cluster Head based Efficient Traffic Control (SCHETF) model aims to alleviate traffic congestion and decrease energy consumption in VANETs through a novel integration of Cluster Head (CH) election, cluster gateway formation, and effective data transmission. SCHETF utilizes a parameter-driven CH election process that considers factors such as network connectivity, distance, speed, and trust levels. This approach guarantees the most suitable CH selection, reducing energy expenditure while enhancing network efficiency. The model assesses network connectivity through indicators like traffic flow and lane weights, ensuring precise determination of link reliability. Metrics for distance and speed are normalized to evaluate the changing behavior of vehicles, while trust ratings are given based on historical and community information to improve reliability. The creation of cluster gateways reduces unnecessary cluster formations by implementing Cluster Gateway Creation (CGC) at strategic sites, lessening communication load, and boosting cluster stability. Efficient data transmission is accomplished by appointing several Cluster Gateway (CGW) within clusters. A backoff timer mechanism gives priority to the CGW that is farthest from the CH for message forwarding, avoiding unnecessary repetitions and guaranteeing effective message dispatch. The model is smart clustering and gateway strategies lessen signaling load during handovers and enhance resource management in dynamic vehicular settings. The SCHETF model offers a thorough framework for tackling the challenges faced by VANETs, providing scalable and energy-efficient communication options. This improves data distribution, assures dependable connectivity, and plays a crucial role in the progress of intelligent transportation systems. The model has been put into practice through experimentation in Network Simulator 2 (NS2). The parameters considered in this study encompass energy efficiency, throughput, packet delivery ratio, end-to-end delay, packet loss, and routing overhead. To undertake a comparison study, the developed SCHETF findings are compared to older approaches such as Evolutionary Algorithm-based Vehicular Clustering Technique (EAVCT), Region Collaborative Management for Dynamic Clustering (RCMDC), and Novel Hypergraph Clustering Model (NHGCM). The outcomes indicate that the suggested SCHETF strategy outperforms previous methods.</jats:p>
  </jats:abstract>
  <publication_date media_type="print">
   <year>2025</year>
  </publication_date>
  <publication_date media_type="online">
   <year>2025</year>
  </publication_date>
  <pages>
   <first_page>142</first_page>
   <last_page>151</last_page>
  </pages>
  <doi_data>
   <doi>10.54216/JISIoT.160112</doi>
   <resource>https://www.americaspg.com/articleinfo/18/show/3602</resource>
  </doi_data>
 </journal_article>
</journal>
