## 6 Conclusions and Future Work  
Problems such as effective data handling surface more frequently as ad hoc networks are used more and more. Overcoming these obstacles is essential to resolving issues like broadcast storms, delays, and collisions. We have presented a milestone strategy with our suggested method, which consists of grouping vehicles, determining sub-relays, and then choosing the best relay from each group, in comparing the included methods. With this novel approach, coverage and delay problems are successfully resolved using a population of spider monkeys. The design also integrates a neural approach to machine learning, which dynamically modifies parameters in real time, which is not utilized in existing mechanisms of dissemination. This technique uses the cooperative behavior of the spider monkey algorithm to act as a learning model for reconfiguration, encouraging the choice of a global relay node. The suggested model outperforms current algorithms in identifyinglocal and global leaders. When the population is smaller, w-SMNO and our proposed algorithms demonstrated enhanced outcomes compared to the traditional ungrouped approach. Moreover, with dynamic member allocation, the proposed algorithms exhibit superior performance over other methods across varying population sizes. This study was dedicated to creating an efficient spider monkey-inspired algorithm to address the delay and collision challenges in data dissemination within VANETs. The primary goal was to enhance the performance, addressing the shortcomings observed in existing models. The results of the simulation at various time intervals indicate a significant improvement in VANET data dissemination performance, with improvements ranging from 35% to 45% for the metrics. This represents improvements in the V2V network's general quality, trustworthiness, and dependability. In densely populated areas or situations with high message transmission rates, the decision factors taken into account regularly live up to expectations. The results highlight the accuracy of the suggested method in reducing broadcast storms and validating its dependability and robustness in dynamic environments. It is reasonable to conclude that the suggested method is dependable and efficient in light of these encouraging results. In the future, the proposed method can be enhanced for the analysis of security attacks, considering the compliance of spider monkey behavior with artificial intelligence techniques.  
Conceptualization, D.G. and R.R.; methodology, D.G.; software, D.G.; validation, D.G. and R.R.; formal analysis, D.G. and R.R.; investigation, D.G. and R.R.; resources, D.G.; data curation, D.G. and R.R.; writing--original draft preparation, D.G. and R.R.; writing--review and editing, D.G.; visualization, D.G. and R.R.; supervision, R.R.; project administration, D.G. and R.R. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
On justified request, the corresponding author may share relevant data and materials used in the manuscript. The Network Simulator software with version 2.35 downloaded from www.nsnam.org is used to develop and run the algorithmic code.  
The authors declare no conflicts of interest.