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CACONET: Ant Colony Optimization (ACO) Based Clustering Algorithm for VANET

Author

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  • Farhan Aadil
  • Khalid Bashir Bajwa
  • Salabat Khan
  • Nadeem Majeed Chaudary
  • Adeel Akram

Abstract

A vehicular ad hoc network (VANET) is a wirelessly connected network of vehicular nodes. A number of techniques, such as message ferrying, data aggregation, and vehicular node clustering aim to improve communication efficiency in VANETs. Cluster heads (CHs), selected in the process of clustering, manage inter-cluster and intra-cluster communication. The lifetime of clusters and number of CHs determines the efficiency of network. In this paper a Clustering algorithm based on Ant Colony Optimization (ACO) for VANETs (CACONET) is proposed. CACONET forms optimized clusters for robust communication. CACONET is compared empirically with state-of-the-art baseline techniques like Multi-Objective Particle Swarm Optimization (MOPSO) and Comprehensive Learning Particle Swarm Optimization (CLPSO). Experiments varying the grid size of the network, the transmission range of nodes, and number of nodes in the network were performed to evaluate the comparative effectiveness of these algorithms. For optimized clustering, the parameters considered are the transmission range, direction and speed of the nodes. The results indicate that CACONET significantly outperforms MOPSO and CLPSO.

Suggested Citation

  • Farhan Aadil & Khalid Bashir Bajwa & Salabat Khan & Nadeem Majeed Chaudary & Adeel Akram, 2016. "CACONET: Ant Colony Optimization (ACO) Based Clustering Algorithm for VANET," PLOS ONE, Public Library of Science, vol. 11(5), pages 1-21, May.
    • Handle: RePEc:plo:pone00:0154080
    DOI: 10.1371/journal.pone.0154080
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    References listed on IDEAS

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    Cited by:

    1. Ghassan Husnain & Shahzad Anwar & Gulbadan Sikander & Armughan Ali & Sangsoon Lim, 2023. "A Bio-Inspired Cluster Optimization Schema for Efficient Routing in Vehicular Ad Hoc Networks (VANETs)," Energies, MDPI, vol. 16(3), pages 1-20, February.
    2. Atif Ishtiaq & Sheeraz Ahmed & Muhammad Fahad Khan & Farhan Aadil & Muazzam Maqsood & Salabat Khan, 2019. "Intelligent clustering using moth flame optimizer for vehicular ad hoc networks," International Journal of Distributed Sensor Networks, , vol. 15(1), pages 15501477188, January.
    3. Salil Bharany & Sandeep Sharma & Surbhi Bhatia & Mohammad Khalid Imam Rahmani & Mohammed Shuaib & Saima Anwar Lashari, 2022. "Energy Efficient Clustering Protocol for FANETS Using Moth Flame Optimization," Sustainability, MDPI, vol. 14(10), pages 1-22, May.
    4. Christy Jackson Joshua & Prassanna Jayachandran & Abdul Quadir Md & Arun Kumar Sivaraman & Kong Fah Tee, 2023. "Clustering, Routing, Scheduling, and Challenges in Bio-Inspired Parameter Tuning of Vehicular Ad Hoc Networks for Environmental Sustainability," Sustainability, MDPI, vol. 15(6), pages 1-19, March.
    5. Abida Sharif & Jian Ping Li & Muhammad Asim Saleem & Gunasekaran Manogran & Seifedine Kadry & Abdul Basit & Muhammad Attique Khan, 2021. "A dynamic clustering technique based on deep reinforcement learning for Internet of vehicles," Journal of Intelligent Manufacturing, Springer, vol. 32(3), pages 757-768, March.
    6. Rahim, Sahar & Wang, Zhen & Ju, Ping, 2022. "Overview and applications of Robust optimization in the avant-garde energy grid infrastructure: A systematic review," Applied Energy, Elsevier, vol. 319(C).
    7. Sahar Ebadinezhad & Ziya Dereboylu & Enver Ever, 2019. "Clustering-Based Modified Ant Colony Optimizer for Internet of Vehicles (CACOIOV)," Sustainability, MDPI, vol. 11(9), pages 1-22, May.
    8. Rejab Hajlaoui & Eesa Alsolami & Tarek Moulahi & Hervé Guyennet, 2019. "Construction of a stable vehicular ad hoc network based on hybrid genetic algorithm," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 71(3), pages 433-445, July.

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