Analysis of Simulated Environments for Clustering and Microservice Management for IoT Edge and Fog Computing Networks

This project addresses critical challenges in distributed computing within Internet of Things (IoT) environments, specifically focusing on resource optimization through Fog and Edge Computing. As IoT networks grow in scale and complexity, efficient data management and latency reduction become essential for critical applications. The research team proposes using advanced simulation tools to model complex interactions between IoT devices, fog nodes, and the cloud. The methodology focuses on the design and implementation of clustering algorithms and microservices management. Through computational simulations, the project seeks to evaluate system performance under various workloads, comparing results with real-world environments to validate model accuracy. This approach allows for the identification of optimal strategies for task distribution and data storage. As a result, the project expects to provide technical recommendations for the practical implementation of these architectures, improving the scalability and responsiveness of IoT systems. The project not only contributes to technological advancement in computational infrastructures but also fosters human talent development and the generation of scientific knowledge publishable in indexed journals.<br/><br/><b>Goal</b>: <br/>Analyze simulated clustering and microservices management environments to optimize performance in Edge and Fog Computing architectures applied to IoT networks. The goal is to improve efficiency, reduce latency, and optimize resource distribution in distributed systems.<br/><br/><b>Research lines</b>: <br/>High performance computing<br/>Cloud Computing