Publication: Sistema IoT para monitorización del estado de un centro de proceso de datos de grandes dimensiones
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Publication Date
2017
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Igual Peña, Francisco
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Abstract
Los Centros de Proceso de Datos (CPD) son grandes instalaciones con centenares de equipos de alto rendimiento funcionando de manera concurrente. El correcto control de parámetros como la temperatura, humedad o consumo energético se convierte en un aspecto clave para un funcionamiento correcto, eficiente y seguro. En este proyecto, se propone el despliegue de una infraestructura compuesta por un elevado número de sensores inalámbricos de bajo consumo y coste en distintos puntos de un CPD de grandes dimensiones siguiendo el paradigma IoT (Internet of Things), controlando y reportando periódicamente distintos parámetros como temperatura, humedad, consumo energético, presencia o humos entre otros. Dicha información será centralizada en un panel de control web que ofrezca una visión integral y en tiempo real del estado del CPD y, bajo ciertas circunstancias, tome de manera automática decisiones que aseguren el correcto funcionamiento del mismo cuando alguno de dichos parámetros supere los límites aceptables.
Además, se demuestra la flexibilidad de la solución aplicando el entorno desarrollado a dos escenarios diferentes: la monitorización de una sala fría equipada con un elevado número de servidores; y la monitorización de un laboratorio científico en el ámbito de la Física de Materiales, donde el correcto control de la temperatura resulta clave para la corrección experimental y la seguridad durante el proceso.
Data Processing Centers (DPC) are large installations with hundreds of high-performance computers running concurrently. The correct control of parameters like temperature, humidity or energy consumption is a key aspect for a correct, efficient and safe operation. In this project, we propose the deployment a high number of low-power wireless sensors at different points in a large DPC following the IoT (Internet of Things) paradigm, controlling and periodically reporting parameters such as temperature, humidity, energy consumption, presence or smoke among others. This information will be centralized in a web control panel that offers an integral and real time view on the state of the DPC and under certain circumstances, automatically making decisions that ensure the proper functioning of the same when any of those parameters exceeds acceptable limits. In addition, it demonstrates the flexibility of the solution by applying the developed environment to two different scenarios: the monitoring of a cold room equipped with a high number of servers; and monitoring of a scientific laboratory in the field of materials physics, where the correct temperature control is key to the experimental correctness and security in the process.
Data Processing Centers (DPC) are large installations with hundreds of high-performance computers running concurrently. The correct control of parameters like temperature, humidity or energy consumption is a key aspect for a correct, efficient and safe operation. In this project, we propose the deployment a high number of low-power wireless sensors at different points in a large DPC following the IoT (Internet of Things) paradigm, controlling and periodically reporting parameters such as temperature, humidity, energy consumption, presence or smoke among others. This information will be centralized in a web control panel that offers an integral and real time view on the state of the DPC and under certain circumstances, automatically making decisions that ensure the proper functioning of the same when any of those parameters exceeds acceptable limits. In addition, it demonstrates the flexibility of the solution by applying the developed environment to two different scenarios: the monitoring of a cold room equipped with a high number of servers; and monitoring of a scientific laboratory in the field of materials physics, where the correct temperature control is key to the experimental correctness and security in the process.
Description
Trabajo de Fin de Grado en Ingeniería de Computadores (Universidad Complutense, Facultad de Informática, curso 2016/2017)