## 4 Congestion Control Based on the RED Algorithm
### The Cred Algorithm
Finally, we optimize the pheromone of the probabilistic transfer formula in the ACA to effectively improve the shortcomings of resource allocation in many aspects. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Serial Number** & **Nodes Count** & **Computational Time (ms)** \\ \hline
1 & 10 & 12 \\ \hline
2 & 20 & 27 \\ \hline
3 & 30 & 35 \\ \hline
4 & 40 & 48 \\ \hline
5 & 50 & 69 \\ \hline
6 & 60 & 72 \\ \hline
7 & 70 & 100 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Execution time of the algorithm for different node sizes. In the future, we will expand the proposed algorithm to edge and fog computing. Furthermore, we will also consider the challenges of resource allocation in specific IoT scenarios such as smart cities and smart driving. Meanwhile, we plan to introduce deep reinforcement learning to detect and multiplex link resources to reduce the network signalling overhead and achieve effective V2V communications. Conceptualization, Y.H. ; methodology, Y.H. and P.H. ; software, Z.Z. ; validation, L.L. ; formal analysis, B.Y. ; investigation, Z.Z. ; data curation, Y.H. ; writing--original draft preparation, Y.H. and Z.Z. ; writing--review and editing, P.H. ; visualization, B.Y. ; supervision, J.P.; project administration, L.L. All authors have read and agreed to the published version of the manuscript. This research was funded by the Henan Science and Technology Plan Project under Grant No. 232102210112, Grant No. 232102520004. Not applicable. The authors declare no known competing interests or personal relationships that could appear to influence the work reported in this paper. ## References

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