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Arithmetic optimization based secure intelligent clustering algorithm for Vehicular Adhoc Network.

Asad Ali1, Muhammad Assam2, Masoud Alajmi3

  • 1Department of CS and IT, University of Engineering and Technology, Peshawar, KPK, Pakistan.

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Summary
This summary is machine-generated.

This study introduces AOACNET, a secure vehicular clustering method using the Arithmetic Optimization Algorithm (AOA) to enhance reliability in vehicular adhoc networks (VANETs). The system effectively prevents malicious nodes and improves data transmission security.

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Area of Science:

  • Computer Science
  • Network Security
  • Artificial Intelligence

Background:

  • Vehicular Adhoc Networks (VANETs) face challenges like data loss and link disruption due to high vehicle mobility and dynamic topologies.
  • Network reliability is compromised by malicious vehicles spreading fake messages, endangering lives and efficiency.
  • Secure and efficient communication is crucial in dense vehicular networks, making vehicular clustering a potential solution.

Purpose of the Study:

  • To design a secure and intelligent vehicular clustering algorithm for VANETs.
  • To optimize cluster formation and prevent the inclusion of malicious nodes.
  • To enhance the reliability and security of communication in dense vehicular networks.

Main Methods:

  • The Arithmetic Optimization Algorithm (AOA) was employed to achieve optimal vehicular cluster formation.
  • A performance value system was implemented, rewarding legitimate transmissions (+1) and penalizing fake messages (-1) to filter nodes.
  • Vehicles with a performance value above a threshold (0) were admitted as cluster members.

Main Results:

  • The proposed AOACNET algorithm demonstrated superior performance in simulations.
  • The algorithm achieved up to 25% improvement over existing methods in key optimization objectives.
  • Evaluated metrics included cluster count, load balancing, computational time, network overhead, and delay.

Conclusions:

  • AOACNET effectively enhances security and reliability in VANETs through intelligent clustering.
  • The AOA-based approach successfully optimizes cluster formation and mitigates risks from malicious nodes.
  • The proposed method offers a significant improvement for secure and efficient vehicular communication.