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Intelligent Data Transmission Through Stability-Oriented Multi-agent Clustering in VANETs

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Evolution in Computational Intelligence (FICTA 2023)

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 370))

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Abstract

Vehicular Ad hoc Networks (VANETs) are one of the intelligent data transmission technologies which captured the attention of maximum of the applications of Intelligent Transport Systems. Due to the high mobility nature of VANETs, the consumption of energy is increased during the process of communication between the vehicles which leads to an increase in the end-to-end delay of the network. To overcome the network from this drawback Stability-Oriented Multi-agent Clustering (SOMAC)-based effective CH selection is performed in VANETs to improve the effectiveness of the communication. The parameters which are considered for the process of CH selection are distance, speed, connectivity, average acceleration and velocity, and residual energy. According to the parameters, the weight factor of the vehicle is measured and the vehicle with the highest weight factor is chosen as a CH. Two types of vehicles are present in the network which is a smart vehicles and ordinary vehicles. Smart vehicles can able to communicate directly with the RSU, but it is fewer in number. The ordinary vehicle is huge in numbers, and it transmits the data to the RSU using the CH. Effective CH selection provides a better communication platform for ordinary vehicles where it can reduce the energy consumption and delay of the network. The proposed SOMAC approach is simulated by using NS2 and evaluates the performance by focusing on the four performance metrics which are end-to-end delay (E2E), packet delivery ratio (PDR), throughput (TP), and energy efficiency (EE). Also, it compares with the earlier research on DGCM and ECRDP. From the simulation outcome, it is proven that the proposed SOMAC approach produced better PDR, TP, and EE as well as lower end-to-end delay when compared with the earlier works.

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Author information

Authors and Affiliations

  1. Department of Computer Technical Engineering, College of Information Technology, Imam Ja‘afar Al-Sadiq University, 66002, Al-Muthanna, Samawah, Iraq

    Ali Alsalamy

  2. Department of Medical Instruments Engineering Techniques, Al-Farahidi University, Baghdad, Iraq

    Mustafa Al-Tahai

  3. Department of Computer Technical Engineering, Bilad Alrafidain University College, 32001, Diyala, Baqubah, Iraq

    Aryan Abdlwhab Qader

  4. College of Engineering Technology, Department of Medical Device Industry Engineering, National University of Science and Technology, Dhi Qar, Nasiriyah, Iraq

    Sahar R. Abdul Kadeem

  5. University of Mashreq, Research Center, Baghdad, Iraq

    Sameer Alani

  6. Computer Technology Engineering, College of Engineering Technology, Al-Kitab University, Kirkuk, Iraq

    Sarmad Nozad Mahmood

Authors
  1. Ali Alsalamy
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  2. Mustafa Al-Tahai
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  3. Aryan Abdlwhab Qader
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  4. Sahar R. Abdul Kadeem
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  5. Sameer Alani
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  6. Sarmad Nozad Mahmood
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Corresponding author

Correspondence to Ali Alsalamy .

Editor information

Editors and Affiliations

  1. Department of Electronics Engineering, Faculty of Engineering and Technology (UNSIET), Veer Bahadur Singh Purvanchal University, Jaunpur, Uttar Pradesh, India

    Vikrant Bhateja

  2. Middlesex University, London, UK

    Xin-She Yang

  3. Faculty of Engineering, University of Porto, Porto, Portugal

    Marta Campos Ferreira

  4. Cardiff Metropolitan University, Cardiff, Warwickshire, UK

    Sandeep Singh Sengar

  5. Institute for Technological Development and Innovation in Communications, University of Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain

    Carlos M. Travieso-Gonzalez

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Alsalamy, A., Al-Tahai, M., Qader, A.A., Kadeem, S.R.A., Alani, S., Mahmood, S.N. (2023). Intelligent Data Transmission Through Stability-Oriented Multi-agent Clustering in VANETs. In: Bhateja, V., Yang, XS., Ferreira, M.C., Sengar, S.S., Travieso-Gonzalez, C.M. (eds) Evolution in Computational Intelligence. FICTA 2023. Smart Innovation, Systems and Technologies, vol 370. Springer, Singapore. https://doi.org/10.1007/978-981-99-6702-5_33

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