Abstract
The 5th generation (5G) mobile communication technology is an important technology for high throughput, low latency and high reliability. Vehicular Ad-hoc Networks (VANET) provides information switching through Vehicle-to-Vehicle (V2V) wireless network communication technology, where the performance requirements for low latency and high transmission capacity is the most challenging. The multi-hop routing-linking strategies investigated in previous works, First Nearest Vehicle (FNV), Second Nearest Vehicle (SNV) and Third Nearest Vehicle (TNV) can provide different requirements for the transmission delay time and transmission capacity. However, the three routing methods are suffered by the variation situation on the vehicle densities and the transmission range in vehicular network (VN). Therefore, this study explored the application of Fuzzy inference system (FIS) for the V2V routing issues. The proposed fuzzy inference routing (FIR) mechanism was designed to compromise the advantage of the multi-hop routing methods and to reach the requirements of transmission delay time and high reliability. Simulation results show that the proposed fuzzy inference routing-premium (FIR-P) can outperform the multi-hop routing methods and satisfy the 90% transmission delay less than 1 ms for VN.
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Acknowledgments
This work was funded in part by Ministry of Science and Technology of Taiwan under Grant MOST 108-2221-E-324-010 and MOST 108-2635-E-150-001.
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Huang, YF., Bayu, T.I., Liu, SH., Huang, HY., Huang, W. (2020). Applications of Fuzzy Inference System on V2V Routing in Vehicular Networks. In: Nguyen, N., Jearanaitanakij, K., Selamat, A., Trawiński, B., Chittayasothorn, S. (eds) Intelligent Information and Database Systems. ACIIDS 2020. Lecture Notes in Computer Science(), vol 12034. Springer, Cham. https://doi.org/10.1007/978-3-030-42058-1_21
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DOI: https://doi.org/10.1007/978-3-030-42058-1_21
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