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@article{146729,
        author = {Dr.G.Mary Valantina},
        title = {A Statistical Approach to the Modeling of DSRC for Vehicular Adhoc networks},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {5},
        number = {1},
        pages = {785-788},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=146729},
        abstract = {Automobile-to-car safety communications centered on the committed brief-variety verbal exchange technological know-how have the capabilities to enable a suite of purposes that help avoid traffic accidents. The performance of those applications, mostly affected by the reliability of verbal exchange links, stringently ties back to the MAC and PHY layer design, which that has been standardized as IEEE 802.11p. The link reliabilities depend upon the sign-to-interference plus- noise ratio (SINR), which, in flip, is determined by the places and transmit vigor values of the transmitting nodes. For this reason, an accurate network model wants to take into account the community geometry. For such geometric units, nevertheless, there's a lack of mathematical figuring out of the characteristics and performance of IEEE 802.11p. Main questions such because the scalability efficiency of IEEE 802.11p ought to be answered by way of simulations, which can be very time consuming and furnish confined insights to future protocol design. On this paper, we investigate the performance of IEEE 802.11p by way of proposing a novel mathematical model situated on queuing conception and stochastic geometry. In unique, we lengthen the Marten hard-core style-II system with a discrete and non uniform distribution, which is used to derive the temporal states of back off counters. With the aid of doing so, concurrent transmissions from nodes inside the carrier sensing stages of each and every other are taken into account, main to a more correct approximation to actual community dynamics. A assessment with network Simulator 2 (ns2) simulations indicates that our model achieves a Excellent approximation in networks with different densities},
        keywords = {},
        month = {},
        }