An intelligent hybrid prairie dog optimization algorithm‐based stable cluster reliable routing scheme for VANETs
Summary Vehicular ad hoc network (VANET) is most significant for supporting intelligent transportation system (ITS)‐based technologies, but it gets hurdled by sparse distribution of vehicles on highways, and dynamically challenging topology that arises due to increase in traffic. Hence, energy stabl...
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crwiley:10.1002/dac.5549 2024-06-02T08:04:16+00:00 An intelligent hybrid prairie dog optimization algorithm‐based stable cluster reliable routing scheme for VANETs Nithyanandam, Gopinath Ambiyaram, Chinnasamy Prabathkumar, Selvakumari 2023 http://dx.doi.org/10.1002/dac.5549 https://onlinelibrary.wiley.com/doi/pdf/10.1002/dac.5549 en eng Wiley http://onlinelibrary.wiley.com/termsAndConditions#vor International Journal of Communication Systems volume 36, issue 14 ISSN 1074-5351 1099-1131 journal-article 2023 crwiley https://doi.org/10.1002/dac.5549 2024-05-03T10:57:24Z Summary Vehicular ad hoc network (VANET) is most significant for supporting intelligent transportation system (ITS)‐based technologies, but it gets hurdled by sparse distribution of vehicles on highways, and dynamically challenging topology that arises due to increase in traffic. Hence, energy stable and optimized cluster construction maximizes the network lifetime. In this paper, Hybrid Prairie Dogs and Beluga Whale Optimization‐based Node Clustering (HPDBWOA‐NC) mechanism is proposed with the parameters of highway route, node velocity, number of vehicular nodes, and communication for achieving stable cluster construction in VANETs. It is proposed with the balanced exploration and exploitation potential of Prairie Dog Optimization Algorithm (PDOA) and Beluga Whale Optimization Algorithm (BWOA) for establishing optimal clusters that increase the network stability during the routing process. It integrated the exploration and exploitation capabilities of PDOA and BWOA and confirmed better optimized clusters which confirmed reliable data delivery by preventing the issue of premature convergence. It constructed clusters and selected cluster heads (CHs) depending on the fitness factors of energy, interdistance between vehicles, communication range, and vehicular density. The results of the proposed HPDBWOA‐NC generated optimal number of CHs in the network which is comparatively 34.21% better than the benchmarked mechanisms. The mean throughput and packet delivery ratio (PDR) achieved by the proposed HPDBWOA‐NC are identified to be significantly improved by 25.48% and 28.91% better than the investigated metaheuristic clustering protocols. The statistical study also guaranteed an increased factor of 81, during the processing of optimizing the clusters during the employment of ITS applications in VANETs. Article in Journal/Newspaper Beluga Beluga whale Beluga* Wiley Online Library International Journal of Communication Systems 36 14 |
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English |
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Summary Vehicular ad hoc network (VANET) is most significant for supporting intelligent transportation system (ITS)‐based technologies, but it gets hurdled by sparse distribution of vehicles on highways, and dynamically challenging topology that arises due to increase in traffic. Hence, energy stable and optimized cluster construction maximizes the network lifetime. In this paper, Hybrid Prairie Dogs and Beluga Whale Optimization‐based Node Clustering (HPDBWOA‐NC) mechanism is proposed with the parameters of highway route, node velocity, number of vehicular nodes, and communication for achieving stable cluster construction in VANETs. It is proposed with the balanced exploration and exploitation potential of Prairie Dog Optimization Algorithm (PDOA) and Beluga Whale Optimization Algorithm (BWOA) for establishing optimal clusters that increase the network stability during the routing process. It integrated the exploration and exploitation capabilities of PDOA and BWOA and confirmed better optimized clusters which confirmed reliable data delivery by preventing the issue of premature convergence. It constructed clusters and selected cluster heads (CHs) depending on the fitness factors of energy, interdistance between vehicles, communication range, and vehicular density. The results of the proposed HPDBWOA‐NC generated optimal number of CHs in the network which is comparatively 34.21% better than the benchmarked mechanisms. The mean throughput and packet delivery ratio (PDR) achieved by the proposed HPDBWOA‐NC are identified to be significantly improved by 25.48% and 28.91% better than the investigated metaheuristic clustering protocols. The statistical study also guaranteed an increased factor of 81, during the processing of optimizing the clusters during the employment of ITS applications in VANETs. |
format |
Article in Journal/Newspaper |
author |
Nithyanandam, Gopinath Ambiyaram, Chinnasamy Prabathkumar, Selvakumari |
spellingShingle |
Nithyanandam, Gopinath Ambiyaram, Chinnasamy Prabathkumar, Selvakumari An intelligent hybrid prairie dog optimization algorithm‐based stable cluster reliable routing scheme for VANETs |
author_facet |
Nithyanandam, Gopinath Ambiyaram, Chinnasamy Prabathkumar, Selvakumari |
author_sort |
Nithyanandam, Gopinath |
title |
An intelligent hybrid prairie dog optimization algorithm‐based stable cluster reliable routing scheme for VANETs |
title_short |
An intelligent hybrid prairie dog optimization algorithm‐based stable cluster reliable routing scheme for VANETs |
title_full |
An intelligent hybrid prairie dog optimization algorithm‐based stable cluster reliable routing scheme for VANETs |
title_fullStr |
An intelligent hybrid prairie dog optimization algorithm‐based stable cluster reliable routing scheme for VANETs |
title_full_unstemmed |
An intelligent hybrid prairie dog optimization algorithm‐based stable cluster reliable routing scheme for VANETs |
title_sort |
intelligent hybrid prairie dog optimization algorithm‐based stable cluster reliable routing scheme for vanets |
publisher |
Wiley |
publishDate |
2023 |
url |
http://dx.doi.org/10.1002/dac.5549 https://onlinelibrary.wiley.com/doi/pdf/10.1002/dac.5549 |
genre |
Beluga Beluga whale Beluga* |
genre_facet |
Beluga Beluga whale Beluga* |
op_source |
International Journal of Communication Systems volume 36, issue 14 ISSN 1074-5351 1099-1131 |
op_rights |
http://onlinelibrary.wiley.com/termsAndConditions#vor |
op_doi |
https://doi.org/10.1002/dac.5549 |
container_title |
International Journal of Communication Systems |
container_volume |
36 |
container_issue |
14 |
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1800748899980279808 |