An improved retransmission timeout prediction algorithm for enhancing data transmission on internet of vehicles network.

The internet of vehicles (IoV) paradigm remains the future of vehicular communication that supports unparalleled ubiquitous internet access during vehicular mobility. For reliable end-to-end data transfer, the cumbersome volume of global web traffic relies on transmission control protocol and its retransmission timeout (RTO) timer prediction algorithm. In the IoV network, the RTO estimation fails to withstand a sudden increase in roundtrip time (RTT) delays that lead to a spurious timeout condition and needless deflation in transmission rate. The enhanced learning RTO (EL-RTO) algorithm proposed in this article implements a spike suppression variable that minimize RTO prediction deficiency during sudden RTT delays in the vehicular network. The experimental results manifest that EL-RTO attains a considerable improvement in end-to-end data delivery performance, goodput, and message latency performances with minimum estimation error against the existing RTO approaches under the simulated IoV environment. [ABSTRACT FROM AUTHOR]

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