The study focuses on Quality of Service (QoS) issues in learning automata-based AODV (LA-AODV) for V2V communication protocols. It analyzes and compares the LAAODV protocol with the original AODV protocol in dynamic traffic situations. The study evaluates critical metrics such as the number of vehicles, average speed, congestion spots, and vehicle time loss across various traffic scenarios, including smooth traffic, steady flow traffic, and heavy traffic. NS3 and SUMO are used as essential tools for this evaluation. The study finds that the LA-AODV protocol performs better in smooth traffic conditions than AODV. It demonstrates a $38.27 \%$ higher packet delivery ratio (PDR), an $\mathbf{8 5 . 2 6 \%}$ lower packet loss ratio (PLR), and a remarkable $56.62 \%$ increase in average throughput compared to AODV. Both protocols exhibit similar performance in steady flow traffic with high PDRs $(97.60 \%$ and $96.87 \%$, respectively) and low PLRs ($2 \%$ and $3 \%$, respectively). However, AODV outshines LA-AODV with a higher PDR $\mathbf{(} \mathbf{9 7 . 6 0 \% )}$) than LA-AODV $(\mathbf{9 6 . 8 7 \%}$) in heavy traffic. LA-AODV, on the other hand, excels in average throughput by $17.24 \%$ in heavy traffic. The study offers valuable insights for improving V2V communication protocols and enhancing communication efficiency to handle dynamic and traffic situations.
Optimizing AODV Routing Protocol to Improve Quality of Service Performance for V2V Communication
06.06.2024
457811 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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