A new model shows reduced end-to-end delay in data transmission for VANETs, indicating improved connectivity and traffic flow.
VANETs act as the central nervous system of the ITS. VANETs provides on‐the‐go wireless network services thereby supporting a wide variant of applications such as traffic safety and monitoring, environment and pollution management, emergency and disaster management and comfortainment based applications. VANETs are highly distinguished by the dynamic nature of nodes with varying speeds leading to frequent disconnections causing delay during data transmission. Therefore ensuring the connectivity between vehicles is a major problem which is needed to be addressed. This work attempts to alleviate the problem of delay in VANET communication by proposing a stochastic model to ensure multi‐hop connectivity between the nodes. The major novelty of the proposed model involves a contention based queuing model. The problem of congestion among cars to use RSUs for data transmission has been simulated to measure the network's efficiency. The simulation framework considers a highway environment to evaluate traffic flow. Collision between any two vehicles on the highway lanes causes a serious congestion leading to traffic jams, delays which deceases the operating efficiency of VANETs. To address this issue and enhance VANET performance, the M/M/1 queuing model is employed and assessed using metrics like end‐to‐end delay (E2E), waiting time, and the number of vehicles competing for multi‐hop connectivity. The performance analysis of the proposed system is analyzed using a scenario with 1000 vehicles per hour by varying traffic arrival rates (10, 20, 30, 50, and 100 vehicles/s), and a transmission rate of 10 Mbps. The Poisson Probability Distribution (PPD) and Binomial Distribution (BD) are utilized to validate the vehicle arrival and service rates. The result gives a significant reduction in E2E delay with the proposed method, achieving up to 30% improvement when compared with other existing systems under huge traffic. The waiting time distribution and queue length also demonstrated that minimizing the service rates based on traffic flow could further decrease delays. These improvements validate the efficiency of the contention‐based M/M/1 queuing model for multi‐hop communication in VANETs.
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Jeyachandhiran et al. (2025) studied this question.
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