Abstract
With the emergence of vehicular Internet-of-Things (IoT) applications, it is a significant challenge for vehicular IoT systems to obtain higher throughput in vehicle-to-cloud multipath transmission. Network Coding (NC) has been recognized as a promising paradigm for improving vehicular wireless network throughput by reducing packet loss in transmission. However, existing researches on NC do not consider the influence of the rapid quality change of wireless links on NC schemes, which poses a great challenge to dynamically adjust the coding rate according to the variation of link quality in vehicle-to-cloud multipath transmission in order to avoid consuming unnecessary bandwidth resources and to increase network throughput. Therefore, we propose an Adaptive Network Coding (ANC) scheme brought by the novel integration of the Hidden Markov Model (HMM) into the NC scheme to efficiently adjust the coding rate according to the estimated packet loss rate (PLR). The ANC scheme conquers the rapid change of wireless link quality to obtain the utmost throughput and reduce the packet loss in transmission. In terms of the throughput performance, the simulations and real experiment results show that the ANC scheme outperforms state-of-the-art NC schemes for vehicular wireless multipath transmission in vehicular IoT systems.
Highlights
The future vehicular Internet-of-Things (IoT) is an important branch of IoT
We carry out a lot of simulations and real experiments in order to verify the superior of the Adaptive Network Coding (ANC) scheme compared with other Network Coding (NC) schemes
We proposed a brand-new network coding scheme combined with Hidden Markov Model (HMM)
Summary
The future vehicular Internet-of-Things (IoT) is an important branch of IoT. The development of vehicular IoT has promoted the development of vehicular applications. In this paper, aiming to counter the rapid change of wireless link quality, we investigate how to optimize network coding to dynamically adjust the coding rate in order to increase vehicular-to-cloud transmission throughput and reduce packet loss. Based on the designed architecture, a novel network coding scheme is introduced to dynamically adjust the coding rate according to the estimated moment PLR to increase throughput and reduce packet loss. When compared with the current NC schemes, ANC significantly improves network throughput performance and reduces multipath transmission packet loss. We introduce wavelets into Hidden Markov Model (HMM) to fit in with the rapid change of link quality in the cellular-based vehicular wireless networks This estimation method effectively reduces the error range of estimated PLR.
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