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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References
Khatri, S., Vachhani, H., et al.: Machine learning models and techniques for VANET based traffic management: implementation issues and challenges. Peer Peer Netw. Appl. 14(3), 1778–1805 (2020)
Abbas, A.H., Mansour, H.S., Al-Fatlawi, A.H.: Self-adaptive efficient dynamic multi-hop clustering (SA-EDMC) approach for improving VANET's performance. Int. J. Interact. Mob. Technol. 17(14) (2022)
Abbas, A.H., Ahmed, A.J., Rashid, S.A.: A cross-layer approach MAC/NET with updated-GA (MNUG-CLA)-based routing protocol for VANET network. World Electr. Veh. J. 13(5), 87 (2022)
Habelalmateen, M.I., Abbas, A.H., Audah, L., Alduais, N.A.M.: Dynamic multiagent method to avoid duplicated information at intersections in VANETs. TELKOMNIKA Telecommun. Comput. Electr (2020)
Abbas, A.H., Audah, L., Alduais, N.A.M.: An efficient load balance algorithm for vehicular ad-hoc network. In: 2018 Electrical Power, Electronics, Communications, Controls and Informatics Seminar (EECCIS), pp. 207–212. IEEE.onics and Control, 18(2), 613–621 (2018, October)
Malik, R.Q., Ramli, K.N., Kareem, Z.H., Habelalmatee, M.I., Abbas, A.H., Alamoody, A.: An overview on V2P communication system: architecture and application. In: 2020 3rd International Conference on Engineering Technology and its Applications (IICETA), pp. 174–178. IEEE (2020, September)
Kandali, K., Bennis, L., Bennis, H.: A new hybrid routing protocol using a modi_ed K-means clustering algorithm and continuous Hop_eld network for VANET. IEEE Access 9, 47169–47183 (2021)
Katiyar, A., Singh, D., Yadav, R.S.: State-of-the-art approach to clustering protocols in VANET: a survey. Wireless Netw. Netw. 26(7), 5307–5336 (2020)
Abbas, A.H., Habelalmateen, M.I., Audah, L., Alduais, N.A.M.: A novel intelligent cluster-head (ICH) to mitigate the handover problem of clustering in VANETs. Int. J. Adv. Comput. Sci. Appl. 10(6) (2019)
Mostafa, S.A., Mustapha, A., Ramli, A.A., Jubair, M.A., Hassan, M.H., Abbas, A.H. (2020, July). Comparative analysis to the performance of three mobile ad-hoc network routing protocols in time-critical events of search and rescue missions. In: International Conference on Applied Human Factors and Ergonomics, pp. 117–123. Springer, Cham
Abbas, A.H., Habelalmateen, M.I., Jurdi, S., Audah, L., Alduais, N.A.M.: GPS based location monitoring system with geo-fencing capabilities. In: AIP Conference Proceedings, vol. 2173, no. 1, p. 020014. AIP Publishing LLC (2019, November)
Husnain, G., Anwar, S.: An intelligent cluster optimization algorithm based on whale optimization algorithm for VANETs (WOACNET). PLoS One 16(4), (2021). article id: e0250271, https://doi.org/10.1371/journal.pone.0250271
Khan, Z., Koubaa, A., Fang, S., Lee, M.Y., Muhammad, K.: A connectivity-based clustering scheme for intelligent vehicles. Appl. Sci. 11(2413), 1–15 (2021). https://doi.org/10.3390/app11052413
Elira, B., Keerthana, K.P., Balaji, K.: Clustering scheme and destination aware context based routing protocol for VANET. Int. J. Intell. Netw. 2, 148–155 (2021). https://doi.org/10.1016/j.ijin.2021.09.006
Gillani, M., Niaz, H.A., Ullah, A., Farooq, M.U., Rehman, S.: Traffic aware data gathering protocol for VANETs. IEEE Access 10, 23438–23449 (2022). https://doi.org/10.1109/ACCESS.2022.3154780
Abbasi, H.I., Voicu, R.C., Copeland, J.A., Chang, Y.: Towards fast and reliable multihop routing in VANETs. In: IEEE Transactions on Mobile Computing, vol. 19, no. 10, pp. 2461–2474 (2020). https://doi.org/10.1109/TMC.2019.2923230
Jubair, M.A., Hassan, M.H., Mostafa, S.A., Mahdin, H., Mustapha, A., Audah, L.H., Abbas, A.H.: Competitive analysis of single and multi-path routing protocols in mobile Ad-Hoc network. Indonesian J. Electr. Eng. Comput. Sci. 14(2) (2019)
Hassan, M.H., Jubair, M.A., Mostafa, S.A., Kamaludin, H., Mustapha, A., Fudzee, M.F.M., Mahdin, H.: A general framework of genetic multi-agent routing protocol for improving the performance of MANET environment. IAES Int. J. Artif. Intell. 9(2), 310 (2020)
Shah, Y.A., et al.: An evolutionary algorithm-based vehicular clustering technique for VANETs. IEEE Access 10, 14368–14385 (2022). https://doi.org/10.1109/ACCESS.2022.3145905
Ahmed, G.A., Sheltami, T.R., Mahmoud, A.S., Imran, M., Shoaib, M.: A novel collaborative IoD-assisted VANET approach for coverage area maximization. IEEE Access 9, 61211–61223 (2021). https://doi.org/10.1109/ACCESS.2021.3072431
Singh, G.D., Prateek, M., Kumar, S., Verma, M., Singh, D., Lee, H.-N.: Hybrid genetic firefly algorithm-based routing protocol for VANETs. IEEE Access 10, 9142–9151 (2022). https://doi.org/10.1109/ACCESS.2022.3142811
Thakur, P., Ganpati, A.: MhCA: a novel multi-hop clustering algorithm for VANET. Int. J. Next-Gener. Comput. 12(4) (2021). https://doi.org/10.47164/ijngc.v12i4.309
Temurnikar, A., Verma, P., Dhiman, G.: A PSO enable multi-hop clustering algorithm for VANET. Int. J. Swarm Intell. Res. 13(2), 1–14 (2022). https://doi.org/10.4018/IJSIR.20220401.oa7
Jabbar, M.K., Trabelsi, H.: A novelty of hypergraph clustering model (HGCM) for urban scenario in VANET. IEEE Access, vol. 10, pp. 66672–66693 (2022). https://doi.org/10.1109/ACCESS.2022.3185075
Kandali, K., Bennis, L., et al.: An intelligent machine learning based routing scheme for VANET. IEEE Access 10, 74318–74333 (2022). https://doi.org/10.1109/ACCESS.2022.3190964
Ali, R.R., Mostafa, S.A., Mahdin, H., Mustapha, A., Gunasekaran, S.S.: Incorporating the Markov Chain model in WBSN for improving patients’ remote monitoring systems. In: International Conference on Soft Computing and Data Mining, pp. 35–46. Springer, Cham (2020, January)
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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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DOI: https://doi.org/10.1007/978-981-99-6702-5_33
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