## 8 Conclusions  
The proposed model represents a significant improvement compared to the base model, especially in key aspects such as latency, load distribution, and performance consistency. By incorporating a hybrid architecture of cloud computing and edge computing, the system optimizes the distribution of processing load and game traffic, alleviating the overload on the main servers. This equitable distribution enhances the system's scalability and flexibility, allowing for a more effective response to the variable demands of the environment.  
One of the main achievements of the model is the significant reduction in latency. With an average of 53.69 ms, this represents a 67.5% decrease compared to the 165.25 ms of the baseline model. Additionally, there is a notable reduction in latency spikes, from 485.76 ms to 192.68 ms, and a 65.8% drop in the standard deviation of latency, demonstrating greater consistency in response times and more predictable performance. This reduction in latency directly improves the user experience, offering faster and smoother interaction in massive multiplayer online (MMO) games.  
The approach of subdividing the game world into clusters and assigning fog nodes based on the average population of each area significantly contributes to more efficient load balancing. This decentralization of resources allows processing capabilities to be placed closer to end users, which, in addition to reducing latency, optimizes the use of available resources and improves system adaptability in high-demand or limited infrastructure scenarios.  
Even in configurations with fewer servers and fog nodes, the system maintains its stability with an average latency of 66.58 ms, demonstrating its ability to adapt to less-favorable conditions without severely affecting performance. When the number of servers is increased and fog nodes are reduced, the average latency improves even further, reaching 45.95 ms, maintaining high availability and optimal performance, even with 1500 simultaneous users. Ultimately, the proposed model not only optimizes load balancing and reduces latency but also ensures greater consistency in system performance, significantly improving the quality of the user experience in MMO gaming.  
The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/app15126379/s1](https://www.mdpi.com/article/10.3390/app15126379/s1)]([https://www.mdpi.com/article/10.3390/app15126379/s1](https://www.mdpi.com/article/10.3390/app15126379/s1)), Table S1: Analysis of State of the Art.  
Conceptualization, E.J.G.F.d.C., E.J.G.P. and D.J.M.; methodology, E.J.G.F.d.C. and E.J.G.P.; software, E.J.G.F.d.C.; validation, E.J.G.F.d.C., E.J.G.P. and D.J.M.; formal analysis, E.J.G.F.d.C., E.J.G.P. and D.J.M.; investigation, E.J.G.F.d.C., E.J.G.P. and D.J.M.; resources, E.J.G.F.d.C.; data curation, E.J.G.F.d.C., E.J.G.P. and D.J.; writing--original draft preparation, E.J.G.F.d.C.; writing--review and editing, E.J.G.F.d.C. and D.J.M.; visualization, E.J.G.F.d.C.; supervision, E.J.G.P. and D.J.M.; project administration, D.J.M. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.  
The data is unavailable due to privacy restrictions.  
The authors declare no conflicts of interest.