## 1 Introduction  
The rapid growth of the online gaming industry has brought new challenges in ensuring an optimal quality of experience (QoE) for players. Massively multiplayer online (MMO) games, in particular, require robust solutions to address the issues of network latency, scalability, and load distribution, which are critical to maintaining seamless and immersive gameplay. Latency, a fundamental factor in online gaming, directly impacts player engagement and responsiveness, often resulting in frustration and reduced satisfaction when poorly managed. These challenges highlight the importance of innovative approaches to enhance QoE in online gaming environments.  
This study proposes a dynamic low-latency load balancing model tailored for MMO games, leveraging a hybrid fog and edge computing architecture. Unlike traditional centralized cloud-based architectures, this model distributes computational tasks closer to playersthrough fog nodes, reducing latency and improving system responsiveness. The model addresses key challenges such as load variability, uneven resource allocation, and latency spikes, demonstrating its potential to transform gaming experiences. As shown in previous studies, advancements in load balancing frameworks, such as task-based strategies [1], cloud-P2P integrations [2], and meta-reinforcement learning algorithms [3], have significantly improved resource allocation and scalability. Building on these contributions, this research offers a novel approach combining fog and edge computing to achieve dynamic load balancing in real-time environments.  
A critical aspect of this work is that the proposed model was evaluated through simulations rather than real-world deployments. The simulated scenarios replicated diverse gaming environments to analyze system performance under varying conditions of load and latency. This distinction underscores the importance of validating theoretical models in controlled environments before real-world application. Furthermore, the proposed model's performance was benchmarked against a model based on the article titled \"A Cloud Gaming Architecture Leveraging Fog for Dynamic Load Balancing in Cluster-Based MMOs\", which used a conventional cloud-centric approach. This comparative analysis demonstrates the improvements achieved in latency reduction and load distribution efficiency.  
The main contributions of this article are as follows:  
Development of a dynamic load balancing model that integrates fog and edge computing for MMO games, demonstration of significant reductions in average latency (67.5%) and latency variability (65.8%) through simulation experiments, comparative analysis with a base model to highlight the effectiveness of the proposed approach, and recommendations for enhancing scalability and QoE in hybrid gaming architectures.  
The rest of the article is organized as follows: Section 2 presents the related work, providing an overview of existing load balancing techniques and hybrid architectures. Section 3 describes the base model, detailing its design and limitations. This study builds on the work in [4] titled \"A Cloud Gaming Architecture Leveraging Fog for Dynamic Load Balancing in Cluster-Based MMOs\". This model was chosen as a baseline due to its innovative use of fog computing for load balancing in cluster-based MMO environments. However, it presented key limitations, such as a lack of consideration for variable latency conditions and uneven load distribution in certain scenarios. Addressing these limitations motivated the development of the improved model presented in this study. Section 4 introduces the proposed dynamic low-latency load balancing model and its key components. Section 5 outlines the simulation setup and methodology. Section 6 discusses the results, while Section 7 compares the base model and the proposed model. Finally, Section 8 concludes the study and suggests directions for future research.