OptiFlow: Optimizing Traffic Flow in ITS With Improved Cluster Routing
Intelligent Transport Systems (ITS) rely heavily on Vehicular Ad hoc Networks (VANET) to facilitate effective communication, especially Vehicle-to-Everything (V2X) communication. However, current research has identified challenges in node management, security, and routing within VANET, calling for b...
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| Format: | Article |
| Language: | English |
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IEEE
2024-01-01
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| Series: | IEEE Open Journal of Vehicular Technology |
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| Online Access: | https://ieeexplore.ieee.org/document/10738438/ |
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| author | Roopa Tirumalasetti Sunil Kumar Singh |
| author_facet | Roopa Tirumalasetti Sunil Kumar Singh |
| author_sort | Roopa Tirumalasetti |
| collection | DOAJ |
| description | Intelligent Transport Systems (ITS) rely heavily on Vehicular Ad hoc Networks (VANET) to facilitate effective communication, especially Vehicle-to-Everything (V2X) communication. However, current research has identified challenges in node management, security, and routing within VANET, calling for bespoke solutions to address these issues. This study introduces an innovative cluster-based routing strategy using Enhanced Slap Swarm Optimization (ESSO) and Evaluation with Mixed Data Multi-criteria Decision-Making (EVAmix MCDM) Method tailored to optimize routing in V2X communication. Unlike existing meta-heuristic methods, which often face slow convergence, premature convergence, and local optima stability, the proposed approach demonstrates striking results. Notably, it enhances throughput by 6278 kbps, elevates the Packet Delivery Ratio (PDR) by 95.77<inline-formula><tex-math notation="LaTeX">$\%$</tex-math></inline-formula>, and reduces end-to-end delay by 1856ms in the 300th iteration, outperforming existing cluster routing methodologies. Our findings suggest a substantial leap toward surmounting the existing challenges in V2X communication. This innovative solution advances the field and sets a course for real-time applications. This approach allows vehicles to continually monitor, adjust their position, and control their speed on highways, enhancing safety and traffic control. |
| format | Article |
| id | doaj-art-78f7ebe6a53143c8a054231bbf54775b |
| institution | OA Journals |
| issn | 2644-1330 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of Vehicular Technology |
| spelling | doaj-art-78f7ebe6a53143c8a054231bbf54775b2025-08-20T02:22:45ZengIEEEIEEE Open Journal of Vehicular Technology2644-13302024-01-0151727174510.1109/OJVT.2024.348808410738438OptiFlow: Optimizing Traffic Flow in ITS With Improved Cluster RoutingRoopa Tirumalasetti0https://orcid.org/0000-0002-2125-1381Sunil Kumar Singh1https://orcid.org/0000-0001-5262-6636VIT-AP University, Inavolu, Beside AP Secretariat, Amaravati, IndiaVIT-AP University, Inavolu, Beside AP Secretariat, Amaravati, IndiaIntelligent Transport Systems (ITS) rely heavily on Vehicular Ad hoc Networks (VANET) to facilitate effective communication, especially Vehicle-to-Everything (V2X) communication. However, current research has identified challenges in node management, security, and routing within VANET, calling for bespoke solutions to address these issues. This study introduces an innovative cluster-based routing strategy using Enhanced Slap Swarm Optimization (ESSO) and Evaluation with Mixed Data Multi-criteria Decision-Making (EVAmix MCDM) Method tailored to optimize routing in V2X communication. Unlike existing meta-heuristic methods, which often face slow convergence, premature convergence, and local optima stability, the proposed approach demonstrates striking results. Notably, it enhances throughput by 6278 kbps, elevates the Packet Delivery Ratio (PDR) by 95.77<inline-formula><tex-math notation="LaTeX">$\%$</tex-math></inline-formula>, and reduces end-to-end delay by 1856ms in the 300th iteration, outperforming existing cluster routing methodologies. Our findings suggest a substantial leap toward surmounting the existing challenges in V2X communication. This innovative solution advances the field and sets a course for real-time applications. This approach allows vehicles to continually monitor, adjust their position, and control their speed on highways, enhancing safety and traffic control.https://ieeexplore.ieee.org/document/10738438/Clusteringintelligent transport systems (ITSs)meta-heuristic approachvehicular ad-hoc networks (VANETs)vehicle routing |
| spellingShingle | Roopa Tirumalasetti Sunil Kumar Singh OptiFlow: Optimizing Traffic Flow in ITS With Improved Cluster Routing IEEE Open Journal of Vehicular Technology Clustering intelligent transport systems (ITSs) meta-heuristic approach vehicular ad-hoc networks (VANETs) vehicle routing |
| title | OptiFlow: Optimizing Traffic Flow in ITS With Improved Cluster Routing |
| title_full | OptiFlow: Optimizing Traffic Flow in ITS With Improved Cluster Routing |
| title_fullStr | OptiFlow: Optimizing Traffic Flow in ITS With Improved Cluster Routing |
| title_full_unstemmed | OptiFlow: Optimizing Traffic Flow in ITS With Improved Cluster Routing |
| title_short | OptiFlow: Optimizing Traffic Flow in ITS With Improved Cluster Routing |
| title_sort | optiflow optimizing traffic flow in its with improved cluster routing |
| topic | Clustering intelligent transport systems (ITSs) meta-heuristic approach vehicular ad-hoc networks (VANETs) vehicle routing |
| url | https://ieeexplore.ieee.org/document/10738438/ |
| work_keys_str_mv | AT roopatirumalasetti optiflowoptimizingtrafficflowinitswithimprovedclusterrouting AT sunilkumarsingh optiflowoptimizingtrafficflowinitswithimprovedclusterrouting |