# Fog Computing Architecture for Load Balancing in Parallel Production with a Distributed MES
## 5 Discussion  
This study utilized advanced technologies on an initial architecture, aiming to develop a phased deployment from a traditional 3.0 industrial infrastructure to a more digitized 4.0 environment. However, some issues were identified that are important to resolve for SME ecosystems: the flexible behavior of the initial architecture when production capacity is expanded and the operational latency of the MES with embedded artificial intelligence. Given these observations, another MES system was adopted for managing the second production line, which was coordinated from an FC node that integrated an optimization algorithm for load balancing. An accelerated processing unit was also coupled to each MES to free up computing capacity. Unlike others, this study shows the practical positive impact of architectures with flexibility features; i.e., during the process, advanced technologies were deployed in stages, and methods were incorporated that ensured a smooth workflow throughout the supply chain, and even more so when the contribution was directed at the needs of SMEs for innovation and development (R&D). We emphasize this approach because, during the review of the literature on similar studies, we found solutions with a strong dependence on robust technological infrastructures and, consequently, a level of high complexity in implementing advanced and emerging solutions, as well as the high costs associated with these technological integrations. These factors alienate and discourage small businesses from R&D. This study put into practice the favorable contextualization provided by the use of FC systems because the FC node ensured direct communication with the MESs and provided resilience during internet service interruptions. Even more important is its contribution to executing task orchestration with stable load balancing, as the FC node incorporates a hybrid algorithm based on ILP and heuristic rules, which allows the parameters to be adjusted according to business operational needs. On the other hand, equipping an R&D architecture for an SME with advanced technologies requires an analysis of the computational power of the management and distribution nodes, which are limited. In this situation, without modifying the technologies of the initial architecture, it was possible to reduce the computational load for thermal tolerance by utilizing an edge acceleration module, which ensures connectivity and interoperability throughout the architecture. By expanding the base study's architecture, substantial improvements are reflected throughout the production chain. This means that latency in bidirectional communication between the MES edge devices and the FC node was significantly reduced, from approximately 1.7 [s] to 22 [ms]. The same occurred with the computational processing time of the MESs, which went from approximately 21 [s] to 6 [s]. These results have a significant impact on key optimization factors, including energy consumption, responsiveness, thermal stability, scalability, and flexibility. Going one layer higher within the extended architecture, task orchestration is optimally executed in the FC node based on the operational weights in the plant (energy consumption and part manufacturing time). Furthermore, as this algorithm does not rely on robust optimization, it optimizes its resources and facilitates adaptable growth and a flexible architecture for future scenarios. In other words, the literature encompasses multiple advanced approaches to load balancing in \begin{table}
\begin{tabular}{l c c} \hline \hline
**Performance Variables** & **Initial Study MES** & **Extended Study MES** \\ \hline CPU & 100\% & 40\% \\ \hline Temperature & 80 \({}^{\circ}\)C & 64 \({}^{\circ}\)C \\ \hline Stock update time and & 21 [s] (MES-CLOUD) & 6.2 [s] MES-FC node \\ other concurrent events. & & \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Comparison of MES performance variables executed on initial and evolutionary architecture.