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Future transportation computing model with trifold algorithm for real-time multipath networks

Bharanidharan Chandrakasan, Malathi Subramanian, Hariprasath Manoharan, Shitharth Selvarajan, Rajanikanth Aluvalu

Abstract


Purpose: In the past ten years, research on Intelligent Transportation Systems (ITS) has advanced tremendously in everyday situations to deliver improved performance for transport networks. To prevent problems with vehicular traffic, it is essential that alarm messages be sent on time. The truth is that an ITS system in and of itself could be a feature of a vehicular ad hoc network (VANET), which is a wireless network extension. As a result, a previously investigated path between two nodes might be destroyed over a short period of time. Design: The Time delay-based Multipath Routing (TMR) protocol is presented in this research which efficiently determines a route that is optimal for delivering packets to the target vehicle with the least amount of time delay. Using the TMR method, data flow is reduced, especially for daily communication. As a result, there are few packet retransmissions. Findings: To demonstrate how effective the suggested protocol is, several different protocols, including AOMDV, FF-AOMDV, EGSR, QMR, and ISR, have been used to evaluate the TMR. Simulation outcomes show how well our suggested approach performs when compared to alternative methods. Originality: Our method would accomplish two objectives as a consequence. First, it would increase the speed of data transmission, quickly transfer data packets to the target vehicle, especially warning messages, and prevent vehicular issues like automobile accidents. Second, to relieve network stress and minimize network congestion and data collisions.


Keywords


routing protocols; intelligent transportation system (ITS); vehicle-to-vehicle (V2V) protocol; time delay-based multipath routing (TMR) protocol

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References


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DOI: https://doi.org/10.32629/jai.v6i2.618

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Copyright (c) 2023 Bharanidharan Chandrakasan, Malathi Subramanian, Hariprasath Manoharan, Shitharth Selvarajan, Rajanikanth Aluvalu

License URL: https://creativecommons.org/licenses/by-nc/4.0