Planificación cloud basada en un sistema fuzzy. Análisis de interpretabilidad
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2020-12-14
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[ES] Este proyecto realiza un análisis e implementación de sistemas y algoritmos que hacen uso de la Lógica Difusa en lenguaje de programación Python. La Lógica Difusa funciona haciendo uso de reglas y conjuntos de pertenencia para obtener una salida en un sistema. Las reglas se generan utilizando la Computación Evolutiva, que mediante simulaciones y algoritmos intenta solventar este inconveniente. Las reglas obtenidas con los métodos mencionados son procesadas por una aplicación intérprete, permitiendo la obtención de parámetros como la interpretabilidad de las reglas, haciendo posible un análisis de estas. Finalmente, se añade una aplicación web junto al simulador “WorkflowSim” y se integran todos los componentes de la aplicación con tecnología Docker. La aplicación web permitirá la selección de parámetros de simulación, “WorkflowSim” generará resultados de consumo de energía para ser optimizados y Docker permitirá que el sistema sea escalable
[EN] This project performs and analysis and implementation of systems and algorithms which make use of Fuzzy Logic in Python programming language. Fuzzy Logic works by using rules and membership sets to get a system output. The rules are generated by Evolutionary Computation, which through simulations and algorithms tries to solve this problem. The obtained rules with the mentioned methods are processed by an interpreter application, allowing the obtaining of parameters such as the rules interpretability, making a rule analysis possible. Finally, a web application is added along with “WorkflowSim” simulator and all application components are integrated with Docker Technology. The web application will allow the selection of simulation parameters, “WorkflowSim” will generate energy consumption results to be optimized and Docker will allow the system to be scalable.
[EN] This project performs and analysis and implementation of systems and algorithms which make use of Fuzzy Logic in Python programming language. Fuzzy Logic works by using rules and membership sets to get a system output. The rules are generated by Evolutionary Computation, which through simulations and algorithms tries to solve this problem. The obtained rules with the mentioned methods are processed by an interpreter application, allowing the obtaining of parameters such as the rules interpretability, making a rule analysis possible. Finally, a web application is added along with “WorkflowSim” simulator and all application components are integrated with Docker Technology. The web application will allow the selection of simulation parameters, “WorkflowSim” will generate energy consumption results to be optimized and Docker will allow the system to be scalable.