Comparaci= ón del rendimiento entre las plataformas para IAAS Open Source: OpenStack y CloudStack

<= span lang=3DES-MX style=3D'font-size:16.0pt;line-height:107%;font-family:"Times = New Roman",serif; mso-ansi-language:ES-EC'> <= span lang=3DEN-US style=3D'font-size:14.0pt;line-height:107%;font-family:"Times = New Roman",serif; mso-ansi-language:EN-US'>Comparison of performance between platforms for IA= AS Open Source: OpenStack and CloudStack

= ¹<= /p>

Valeria Estefanía Illapa Robles

https://orcid.org/0009-0008-8828-690X

= =

Universidad Nacional de Chimborazo (UNACH), Riobamba, Ecuador, Campus Norte.

villapa.fis@unach.edu.ec

= ²<= /p>

Jhony = Javier Marcatoma Morocho

https://orcid.org/0009-0009-6869-3978

= =

Universidad Nacional de Chimborazo (UNACH), Riobamba , Ecuador, Campus Norte <= span style=3D'mso-ansi-language:ES-EC'>jmarcatoma.fis@unach.edu.ec =

3

Paul <= /span>Xavier Paguay Soxo

<= /span>

https://orcid.org/0000-0002-0262-9844

<= /span>

Escuela Superior Politécnica de Chimborazo (ESPOCH), Riobamba, Ecuador, Campus Ce= ntro Sede Orellana Av. 9 de octubre entre Quito y Napo. Maestría en Interconectividad en Redes

ppaguay@espoch.edu.ec

= ⁴=

René Alfonso Barragán Torres

<= /span>

https://orcid.org/0009-0001-9790-0608

<= /span>

Escuela Superior Politécnica de Chimborazo (ESPOCH), Riobamba, Ecuador, Campus Ce= ntro Sede Orellana Av. 9 de octubre entre Quito y Napo. Maestría en Interconectividad en Redes

rene.barrag= an@espoch.edu.ec

= ⁵=

Joffre Stalin Monar

<= /span>

https://orcid.org/0000-0002-6534-183X

<= /span>

Escuela Superior Politécnica de Chimborazo (ESPOCH), Riobamba, Ecuador, Campus Ce= ntro Sede Orellana Av. 9 de octubre entre Quito y Napo. Maestría en Seguridad Telemática

jmonar@espoch.edu.ec

Artículo de Investigación Científica y Tecnológica

Enviado: 15/10/2023

Revisado: 10/11/2023

Aceptado: 04/12/2023

Publicado:30/01/2024

DOI: https://doi.org/10.33262/c= ienciadigital.v8i1.2877

Cítese:

Illapa Robles, V. E., Marcatoma Morocho= , J. J., Paguay Soxo, P. X., Barragán Torres, R. A., & Monar, J. S. (2024). Comparación del rendimiento entre las plataformas para IAAS Open Source: OpenStack y CloudStack. Ciencia Digital, 8(1), 145-172. https://doi.or= g/10.33262/cienciadigital.v8i1.2877

CIENCIA DIGITAL, es una revista multidisciplinaria, trimestral, que se publicará en soporte electrónico tiene como misión contribuir a la   formación de profesionales competentes con vi= sión humanística y crítica que sean capaces de exponer sus resultados investigativos y científicos en la misma medida que se promueva mediante = su intervención cambios positivos en la sociedad. = https://cienciadigital.org

La revista es editada por la Editorial Ciencia Digital (Editorial de prestigio registrada en la Cámara Ecuatoria= na de Libro con No de Afiliación 663) www.celibro.org.ec

Esta revista está protegida bajo una licencia Creative Commons Atribución-NoComercial-CompartirIgual 4.0 International. Copia de la licencia: https://creativecommons.org/licenses/by-nc-sa/4.0/deed.es<= /span>

Palabras claves: =

OpenStack, CloudStack, IaaS, rendimiento, Nube Privada, Cloud Computing

Resumen

Introducción: La implementación de una plataforma IaaS en la UNACH representa una gran oportunidad para mejorar la infraestructura tecnológica de la institución, fortalecer las capacidades de estudiantes y docentes, y promover la innovación y la competitividad. Objetivo: Comparar las plataformas OpenSta= ck y CloudStack mediante el rendimiento en un entorno virtualizado para la implementación de una nube privada en la Universidad Nacional de Chimbora= zo. Metodología: El establecimiento del escenario contó = con la instalación de tres nodos: el nodo controlador, el nodo cómputo y un n= odo de almacenamiento desplegados sobre Proxmox VE. Resultados: Se realizó el análisis de cada dimensión obtenidos del Modelo de FURPS con una muestra de 35 pruebas, un porcentaje de error del 0.05%, verificando = en primera instancia la normalidad de los datos y posteriormente las pruebas= de contraste correspondientes, obteniendo de esta manera para la dimensión de Tiempo de proces= amiento una diferencia de 5.6% de mejor desempeńo a favor de OpenStack así también en los indicadores de Uso de R= AM con un 0.89%, Uso de CPU con un 2.67% y Tráfico de Red Saliente con un 2.= 07%. Conclusión: Se calculó un resultado general a través de un análisis multicriterio con= el método de NAIADE obteniendo que el desempeńo es similar. Área de estudio gener= al: Computación. Área de estudio específica: Computación en la nube.

Keywords:

OpenStack, CloudStack, IaaS, rendimiento, Nube Privada, Cloud Computing

Abstract

Introduction: The implementation of= an IaaS platform at UNACH represents a great opportunity to improve the technological infrastructure of the institution, strengthen the capacitie= s of students and teachers, and promote innovation and competitiveness. Obj= ective: To compare OpenStack and CloudStack platforms through performance in a virtualised environment for the implementation of a private cloud at the National University of Chimborazo. Methodology: The establishment of the scenario included the installation of thr= ee nodes: the controlling node, the computation node and the storage node deployed on Proxmox VE. R= esults: The analysis of each of the dimensio= ns of the FURPS model was carried out with a sample of 35 tests, an error rate = of 0.05%, the first time the normality of the data and the corresponding contrast tests, obtaining this way for the processing time of a differenc= e of 5.6% The best use of OpenStack The use of RAM with 0.89%, The use of the = CPU with 2.67% and Outgoing Network Traffic with a 2.07%. Conclusion: a general result was calculated through a multicriteria analysis w= ith the NAIADE method, obtaining that the performance is similar. =

Introdu= cción

Según Tam Malaga (2015), la computación en= la Nube “es parte de la realidad de este tiempo, como concepto se encuentra en= la mente de todos e implica que consideremos, de una manera totalmente distint= a, los límites en capacidad de almacenamiento, procesamiento y ancho de banda; distinta de cuando sólo se dispone de las capacidades de la infraestructura propia (ya sea de la persona o de la organización). En otras palabras, much= as iniciativas que serían imposibles de considerar por la alta inversión en in= fraestructura hoy son posibles gracias a la nube”.

= Infraestructura como Servicio (IaaS) es uno de los tipos de computación en la nube que ofre= cen varios de las opciones que se encuentran en el mercado, mediante estas soluciones, los usuarios pueden emplear recursos virtuales, como servidores virtuales, redes virtuales, router virtuales bajo demanda (Yamoto, 2018)= . En el paradigma de la computación en la nube, el proveedor de IaaS puede proporcionar recursos básicos (es decir, CPU, memoria RAM, almacenamiento, redes) como instancias virtuales a los usuarios (estudiantes, docentes) (Zangara et al., 2015), eliminando la necesidad de que los usuarios posean y operen estos recursos, lo que puede conducir a un mejor desempeńo en sus actividades (Salam et al., 2015).

= OpenStack y CloudStack son las plataformas open source para Cloud más utilizadas en la actualidad y su uso sigue en aumento (Yamoto et al., 2014). OpenStack es un software en la nube que ofrece la capacidad de controlar grandes logros de cómputo, almacenamiento y recursos de red (Sharma, 2015), por otro lado CloudStack es una plataforma de software de código abierto, escrito en Java, diseńado para el desarrollo y la gestión de la Infraestructura de nube como= un servicio (IaaS) (Sabharwal & Shankar, 2013). <= /p>
Debido al auge de las diferentes ofertas para la implementación de servicios IaaS, existen varios= estudios que analizan los diferentes parámetros de funcionamiento como el de Yamato = et al. (2015) que realiza un estudio de desarrollo del servidor de gestión de recursos permitiendo la producción de servicios en la nube basados en OpenStack, midiendo el rendimiento de los múltiples usos de las API para demostrar que esta implementación reduce el tiempo de espera por parte de l= os usuarios.

Badia et al. (2013) pres= enta mecanismos diseńados para el despliegue automatizado de las principales plataformas IaaS de código abierto: Nimbus, OpenNebula, CloudStack y OpenSt= ack permitiendo a los usuarios comparar cada arquitectura y el rendimiento ofre= cido por cada una de ellas para hacer uso de acuerdo con sus necesidades. <= /o:p>

Kim et al. (2017) hace u= na comparación de las plataformas OpenSource: CloudStack y OpenStack proporcionando sus propias interfaces de programación (API) para gestionar = los recursos de la nube que cada una de ellas ofrecen. Además, muestra los deta= lles de implementación de la API integrada y la evaluación del rendimiento. Concluyendo que la sobrecarga impuesta en la interfaz es insignificantemente pequeńa y puede ser utilizada con éxito para el acceso multi-cloud.

Hahm et al. (2014) hace = un análisis de las plataformas OpenSource: OpenStack, CloudStack y OpenNebula, seleccionando CloudStack para comprobar las funcionalidades y el rendimiento que esta plataforma ofrece a través de escenarios de prueba.

La Universidad Nacional = de Chimborazo (UNACH) cuenta con el Centro de Tecnologías Educativas (CTE), en= el cual se encuentra una infraestructura tecnológica donde están alojadas, aplicaciones informáticas para los procesos regulares de la institución, ta= nto académica como administrativa. Dentro de las tareas académicas, varios de l= os proyectos que se desarrollan requieren de infraestructura tecnológica para = su implementación, por lo que una solución iCloud es requerida. Es importante = por ello implementar una plataforma IaaS que ofrezca un alto rendimiento, abarc= ando las diferentes dimensiones como: tiempo de respuesta, tiempo de procesamien= to y consumo de recursos, así de esta manera se espera que los estudiantes y docentes de la UNACH puedan realizar soluciones informáticas que les permit= an ponerse al día en el creciente auge de la tecnología.

La presente investigación tiene como objetivo realizar la comparación del rendimiento entre las plataformas IaaS Open Source OpenStack y CloudStack para su posterior implementación de un servidor iCloud IaaS en la Universidad Nacional de Chimborazo.

Para la comparación se l= levó a cabo en primera instancia una revisión bibliográfica de las herramientas motivos de la comparación, posteriormente se seleccionó dimensiones e indicadores de comparación obtenidas del modelo FURPS. Posteriormente se realizó la implementación del escenario de pruebas sobre un servidor Proxmo= x VE donde se obtuvieron las muestras con cada plataforma. A continuación, se aplicaron algoritmos estadísticos para la verificación de diferencias exist= entes entre las plataformas, así como un análisis multicriterio para un resultado general, al final se detallan las conclusiones del trabajo donde se muestra= una ligera ventaja de OpenStack sobre CloudStack en varios indicadores analizad= os.=

Revisión Bibliográfica

Para Celaya & Sakellariou (2014),= Cloud computing se podría definir como un modelo de servicio a través de Internet donde se comparten una amplia gama = de recursos TIC: red, aplicaciones, servicios, almacenamiento, infraestructura= s, etc. De esta manera las empresas se pueden centrar en su negocio externaliz= ando (outsourcing) determinados servicios. Estos servicios se caracterizan por s= er escalables, bajo demanda, flexibles y seguros. Permiten a las empresas focalizarse en sus ventajas competitivas y convertir las inversiones en un gasto variable. Para = Clavijo & Ledesma & Duque (2018), e= l Cloud Computing, se refiere a un conjunt= o de servicios ofrecidos a través de internet, mediante aplicaciones configuradas por medio de la convergencia de hardware y software en centros de datos alrededor del mundo.

La base de las solucione= s de Cloud Computing es la virtualización. La virtualización es un marco o metodología de dividir los recursos de una computadora en múltiples Entorno= s de ejecución, aplicando uno o más conceptos o tecnologías tales como partición= de hardware y software, tiempo compartido, simulación parcial o completa de la máquina, emulación, calidad de servicio, y muchos otros. El software de virtualización hace posible ejecutar múltiples sistemas operativos y múltip= les aplicaciones en el mismo servidor al mismo tiempo (Sharma, 2015).

Para Portnoy (2012), la virtualización es el motor que impulsará la computación en la nube al conve= rtir el centro de datos, que solía ser un proceso práctico e intensivo para las personas, en un “autogestionable”, altamente escalable, altamente disponibl= e, pilas de recursos fácilmente consumibles. Antes de la virtualización, los administradores de sistemas gastaban el 70 por ciento o más de su tiempo en funciones de rutina y reaccionar a los problemas, que dejaron poco tiempo p= ara la innovación o el crecimiento. La virtualización y, por extensión, la computación en la nube brinda mayores oportunidades de automatización que reducen los costos administrativos y aumentar la capacidad de una empresa p= ara implementar soluciones dinámicamente.

IAAS significa Infrae= structure as a Service o Infraestructura como servicio. Es un modelo de distribuc= ión de infraestructura de computación como un servicio, normalmente mediante una plataforma de virtualización. En vez de adquirir servidores, espacio en un centro de datos o equipamiento de redes, los clientes compran todos estos recursos a un proveedor de servicios externo. Dicho de otra forma, lo que ofrece el proveedor en este caso son máquinas virtuales, ya sean Linux, Win= dows u otros sistemas operativos. El cliente instala sus aplicaciones en ellas, = así como la arquitectura necesaria, etc.

Entre los diferentes proveedores IAAS públicos que se encuentran en el mercado destacan Amazon Web Services (AWS) e IBM SmarthCloud, Entre las opciones para la implementación de IAAS privados se tienen a OpenStack y CloudStack.

Los componentes que conforman la arquitectura de las plataformas Open Source: OpenStack y CloudStack donde se puede observar que OpenStack brinda la posibilidad = de dividirse en 3 nodos al momento de su implementación (CloudStack.apache.org, 2016; OpenStack.org, s.f.; European Commission, 2010), como se muestra en la figura 1.

Figura 1

Arquitectura de CloudSt= ack y OpenStack

=

<= /span>

= Se plantea un análisis comparativo de las propiedades (Sabharwal & Shankar, 2013; Sharma, 2015), que ofrecen las plataformas Open Source: OpenStack y CloudStack al momento de ser implementadas, como se muestra en la figura 2.=

=

=

=

Figur= a 2

Propiedades de las Plataformas OpenStack y CloudStack

=

Metodología

La investigación, de acuerdo con Tamayo (2006), se define como “un esfuerzo que se emprende para resolver un problema claro es= tá, un problema de conocimiento”, por su lado, Ibarra & Onofre (2022), la definen como “una actividad encaminada a la solución de problemas. Su objetivo consiste en hallar respuesta a preguntas mediante el empleo de procesos científicos”. En la tabla 1 se observa los resultados de la búsqueda bibliográfica del tema motivo de investigación

Tabla 1

Me= todología Research

CRITERIO

DETALLE=

FOCALIZACIÓN

= En el siguiente proyecto de investigación se pretende dar respuesta a la siguiente pregunta: żCuál de las dos plataformas: OpenStack y CloudStack ofrecen un mejor rendimiento en la implementación de la nube privada de la Universidad Nacional de Chimborazo?

ESTRATEGIA DE BÚSQUEDA:

ÁREA:

OpenStack y CloudStack, medición del rendimiento de las plataformas Open Source OpenS= tack y CloudStack en la implementación de una nube privada.<= /p>
PROPÓSITO DE= LA BÚSQUEDA:

Analizar las características y funcionalidades de las plataformas Open Source: OpenSta= ck y CloudStack, para seleccionar la más adecuada e implementar una nube priva= da.

FUENTES DE INFORMACIÓN

Books, Journal, Technical Report, PhD thesis, Handbook.=

MOTORES DE BÚSQUEDA

ProQuest, Sc= opus

CRITERIOS DE BÚSQUEDA

“Performance” Openstack AND Cloudstack

"OpenStack" AND "CloudStack"=

“Private Cloud” “Cloud Computing iaas”

CRITERIOS DE= SELECCIÓN

Documentos q= ue contengan información sobre las características y funcionalidades de las plataformas Open Source: OpenStack y CloudStack que nos permitan medir el rendimiento en la implementación de una nube privada.

CRITERIOS DE EXCLUSIÓN

ü Se excluyen documentos que analicen otras características difere= ntes al rendimiento como: la portabilidad, seguridad, disponibilidad, integrid= ad, fiabilidad.

ü Información que se encuentre inferior al 2013.=

ü Todas las plataformas que no sean Open Source.=

CRITERIOS DE EVALUACIÓN DE CONTENIDO

Exactitud, objetividad, cobertura, vigencia, relevancia en función a la pregunta de investigación.
Se investiga en autores que han hecho aportes a = los artículos consultados.

ANÁLISIS DE INFORMACIÓN

Se proporcio= na una visión general para medir el rendimiento en la implantación de una nu= be privada, para lo cual se analizará dos plataformas Open Source: OpenStack= y CloudStack, determinando la óptima ya que no existe un estudio comparativo entre estas dos plataformas acerca del rendimiento que ofrecen las mismas= .

QUERY

PROQUEST

SCOPUS

TOTAL

“Performance” Openstack AND Cloudstack

153

14

167

"OpenSt= ack" AND "CloudStack"

343

38

381

“Private Cloud” “Cloud Computing iaas”

7

1

8

TOTAL:<= /o:p>

503

53

556

Tipo De Estudio

Según el objeto de estudio la presente investigaci= ón es del tipo aplicativa, la cual tiene por objetivo la generación de conocimiento con aplicación directa y a mediano plazo en la sociedad o en el sector productivo. Este tipo de estudios presenta un gran valor agregado po= r la utilización del conocimiento que proviene de la investigación básica. (Lozada, 2014). Según el nivel de medición y análisis de la inform= ación, es una investigación descriptiva, la cual consiste en la caracterización de= un hecho, fenómeno, individuo o grupo, con el fin de establecer su estructura o comportamiento. Los resultados de este tipo de investigación se ubican con = un nivel intermedio en cuanto a la profundidad de los conocimientos se refiere= .

Población y Muestra= <= /h2>
Para el análisis de los indicadores la muestra utilizada es 35 pruebas, para cada una de las dimensiones con sus diferentes indicadores.

Procedimientos<= /h2>
Al trabajar directamente con equipos, el procedimi= ento que se adoptan es la investigación documental de las plataformas Open Source propuestas, que permitan implementar y verificar su código, a través de su documentación que se encuentra alojadas en las páginas web de las comunidad= es de software libre, utilizando el método científico el cual contiene los siguientes pasos:

·         Planteamiento del problema, que es obj= eto principal de estudio.

·         El apoyo del proceso previo a la formulación de la hipótesis.

·         Levantamiento de la información necesa= ria.

·         Análisis e interpretación de Resultado= s.

·         Proceso de la Comprobación de la Hipót= esis.

·      =    Difusión de resultados.

Procesamiento y Análisis<= o:p>

La información relacionada a la investigación es analizada y presentada en figuras, con los análisis estadísticos de Shapiro-Wilk para las pruebas de normalidad cuya aplicación es apropiada en tamańo de muestras inferiores a 50 = (Razali & Wah, 2011). Por otra parte, para las pruebas de normalidad en grupos de muestras mayore= s o igual a 50 como fue el caso del tiempo de procesamiento con 385 pruebas, se utilizó el análisis estadístico de Kolmogorov-Smirnov, apropiado para este = tipo de conjunto de datos.

Una vez realizada la prueba de normalidad, puede resultar dos escenarios, el primero correspondiente a datos sin una distribución normal (Nachar, 2008), y el segundo a datos con una distribución normal, en ambos casos se procederá con las prue= bas de análisis de significación, que para el primer escenario (datos no normal= es) se utilizó la fórmula de U de Mann-Whitney mientras que para el segundo esc= enario (datos normales) se utilizó la prueba t.

Para los casos en las que existió una diferencia significativa, la fórmula de variación porcentual fue utilizada para encont= rar la diferencia expresada en porcentaje entre ambas plataformas, la fórmula e= s la siguiente:

<= /span>

(1)

Donde:

·      =    VP es la variación porcentual expresad= a en porcentaje

·      =    VMayor es el valor mayor de entre los datos a comparar

·      =    VMenor es el valor menor de entre los datos a comparar

Indicadores de evaluación del rendimiento<= /o:p>

La evaluación del rendimiento de sistemas informát= icos ha sido abordada en diferentes trabajos de investigación, cada uno de ellos proponiendo una cantidad de variables e indicadores, para el presente traba= jo se ha seleccionado los indicadores que proponen tanto el modelo FURPS (Constanzo, 2014), así como el propuesto por Comas & Nogueira & Medina (2014), entre las que se mencionan las siguientes dimensiones e indicadores:

·      =    Tiempo de respuesta: Tiempo en milisegundos que tarda en completar una tarea, desde el momento que se invo= ca hasta que se recibe la respuesta, este indicador será realizado mediante pruebas de ping al servidor.

·      =    Tiempo de procesamiento: Tiempo en milisegundos que se tarda en completar una tarea, este indicador se llevará= a cabo con tareas como: crear, eliminar, bloquear, suspender, reiniciar y acc= eder a una instancia (máquina virtual).

·      =    Consumo de recursos: El consumo de recursos se divide a su vez en 3 subcriterios como son: Uso de CPU expresad= o en porcentaje, Uso de Memoria RAM expresado en MegaBytes, Lectura de Disco expresado en KiloBytes y Tráfico de Red tanto de entrada y salida expresado= en KiloBytes.

·         Eficacia: Número de tareas completadas= sin errores.

Importante indicar que, para la presente investiga= ción con excepción del indicador de eficacia, en todos los demás el objetivo es minimizar los tiempos y consumo de recursos.

Herramientas de Análisis

La herramienta para el análisis de datos es el paq= uete informático IBM SPSS Statistics, que es un conjunto de herramientas = de análisis predictivo y de datos completo, enfocado para usuarios empresarial= es, analistas y programadores estadísticos (IBM SPSS Statistics Family, 2015). Existen versiones comerciales, así como versiones estudiantiles para el aprendizaje. Para la generación de los gráficos estadísticos se utilizó el programa de hoja de cálculo Excel.

Las dimensiones propuestas para el análisis del rendimiento miden diferentes aspectos que inciden en el resultado final, sin embargo, contienen unidades de medidas diferentes, para la consolidación de= los datos obtenidos de las pruebas, en este caso las medias estadísticas de cada dimensión, se utilizó el método conocido como NAIADE (Munda, 2006). NAIADE (Novel Approach to Imprecise Assessment and Decision Environments) es un mé= todo multicriterio discreto, cuya matriz de impacto (o evaluación) puede incluir medidas claras, estocásticas o indefinidas del desempeńo de una alternativa= con respecto al criterio de evaluación, por tanto este método es muy flexible p= ara aplicaciones del mundo real. NAIADE ha sido creado y desarrollado en varias versiones por el profesor Giuseppe Munda (Falconí & Burbano, 2004).

Para la implementación de las pruebas se utilizó el hipervisor Proxmox VE que es una plataforma completa de código abierto para= la virtualización empresarial. Con la interfaz web integrada, puede administrar fácilmente máquinas virtuales y contenedores, almacenamiento y conexión definidos por software, agrupación de alta disponibilidad y múltiples herramientas listas para usarse en una sola solución (Proxmox Server Soluti= ons GmbH, 2004-2017), además permite obtener datos sobre la el rendimiento, porcentaje de RAM utilizada, CPU, velocidad de procesamiento, tráfico de re= d de las instancias, que permitió la obtención de indicadores para la investigac= ión.

Escenario

Para la realización de la solución se propone el siguiente escenario aplicado en la instalación de las plataformas OpenStack= y CloudStack (ver tabla 2).

Tabla 2

Ha= rdware del Servidor

Plataforma d= e virtualización

Proxmox VE 4= .2-2

RAM

78..63 GB

CPU

12 x Intel(R) Xeon(E) CPU E5-2620 2GHz (1 Socket)

Disco Duro

300 GB<= /o:p>

Para la implementación del escenario de pruebas se= lo realizó sobre un servidor Proxmox VE en la cual de un modo anidado se insta= ló las plataformas OpenStack y CloudStack, así como el servidor para el monito= reo de la utilización de recursos, cuya disposición se observa en la figura 3.<= o:p>

Figura 3

Escenario de despliegue de las pruebas

Se= rvidor de Monitoreo

Ope= nStack

Clo= udStack



El Hardware de las máquinas virtuales para cada plataforma, así como del servidor utilizado para el monitoreo se detallan en las tablas 3 y 4.

Tabla 3

Ha= rdware virtualizado para Openstack y Cloudstack

Sistema Operativo

Ubuntu 15.04=

Memoria RAM<= o:p>

15 GB

CPU

8 CPUs<= /o:p>

Disco Duro

150 GB<= /o:p>

Tabla 4

Hardware virtualizado del servidor de monitoreo

Herramienta<= o:p>

Nagios3, Cac= ti

Sistema Operativo

Ubuntu 15.04=

RAM

2 GB

CPU

4 CPUs<= /o:p>

Disco Duro

15 GB

La arquitectura de implementación para cada plataf= orma se utilizó la denominada “Todo en Uno”, que se observan en las figuras 4 y = 5.

Figura 4

Arquitectura de Cloudstack Todo en Uno

Zona

Pod

Clúster

Host

Primary Storage

Secondary Storage

DB _ MySQL

SERVIDOR DE ADMINISTRACIÓN


Figura 5

Arquitectura Opencloud "Todo en Uno"

Resultados

Se destacan los resultados relevantes sin incurrir= en repeticiones de información.

En el presente apartado se muestran los resultados= de la evaluación del rendimiento de cada plataforma en cada una de sus dimensi= ones como tiempo de respuesta, tiempo de procesamiento y consumo de recursos.

Dimensión Tiempo de respuesta<= o:p>

Con las pruebas de normalidad de Shapiro-Wilk, se observa que con un nivel de significancia de 0.00 tanto para OpenStack como para CloudStack, los datos no son normales, como se observa en la tabla 5.<= o:p>

Tabla 5

Pr= ueba de normalidad de datos del tiempo de respuesta

Shapiro-Wilk

Estadístico

gl

Sig.

OpenStack

,848

35

,000

CloudStack

,847

35

,000

&n= bsp;

Realizando la prueba de contraste se observa un va= lor de U de Mann-Whitney de 570 y una significancia asintótica (bilateral) de 0= .618 mayor a 0.5, por lo tanto, se evidencia que NO existe una diferencia significativa en cuanto al tiempo de respuesta entre ambas plataformas (ver tabla 6).

Tabla 6

Pr= ueba de contraste del tiempo de respuesta

Tiempo de Respuesta (ms)

U de Mann-Whitney

570,000

W de Wilcoxon

1200,000

Z

-,499

Sig. asintótica (bilateral)

,618

&n= bsp;

Dimensión Tiempo de procesamiento

Para la dimensión del tiempo de procesamiento se h= an llevado a cabo las siguientes tareas: crear, eliminar, apagar, encender, reiniciar, suspender, reanudar, bloquear, desbloquear, snapshot y de ingreso a la consola de una instancia, para cada tarea se ha analizado la normalidad de los datos mediante la prue= ba de Shapiro-Wilk, donde como resultado se obtuvo que los datos no son normal= es en todos los casos de prueba como se observa en la tabla 7.

Tabla 7

Pr= uebas de normalidad del tiempo de procesamiento

Tipo

Shapiro-Wilk=

Estadístico<= o:p>

gl

Sig.

Tiempo de Proc. Creación (ms)<= /p>

OpenStack

0,931

35

0,03

CloudStack

0,927

35

0,022

Tiempo de Proc. Eliminación (ms)

OpenStack

0,811

35

0=

CloudStack

0,694

35

0=

Tiempo de Proc. Snapshot (ms)<= /p>

OpenStack

0,495

35

0=

CloudStack

0,696

35

0=

Tiempo de Proc. Iniciar (ms)

OpenStack

0,639

35

0=

CloudStack

0,582

35

0=

Tiempo de Proc. Apagar (ms)

OpenStack

0,627

35

0=

CloudStack

0,854

35

0=

Tiempo de Proc. Reiniciar (ms)=

OpenStack

0,74

35

0=

CloudStack

0,673

35

0=

Tiempo de Proc. Suspender (ms)=

OpenStack

0,855

35

0=

CloudStack

0,87

35

0,001

Tiempo de Proc. Reanudar (ms)<= /p>

OpenStack

0,855

35

0=

CloudStack

0,698

35

0=

Tiempo de Proc. Bloquear (ms)<= /p>

OpenStack

0,326

35

0=

CloudStack

0,635

35

0=

Tiempo de Proc. DesBloquear (ms)

OpenStack

0,937

35

0,046

CloudStack

0,634

35

0=

Tiempo de Proc. Ingreso (ms)

OpenStack

0,625

35

0=

CloudStack

0,705

35

0=

A continuación, se procede con el análisis de los datos aplicando la prueba de U de Mann-Whitney, donde se observa en la tabl= a 8 que el nivel de significancia asintótica es menor a 0.05 en todos los casos= por lo cual se acepta la hipótesis nula, la cual establece que si existe una diferencia significativa entre las plataformas en cada una de las tareas llevadas a cabo.

Tabla 8

Pr= ueba de contraste del tiempo de procesamiento

U de Mann-Whitney

W de Wilcoxon

Z

Sig. asintótica (bilateral)

Tiempo de Pr= oc. Creación (ms)

440

1070

-2,027<= /o:p>

0,043

Tiempo de Pr= oc. Eliminación (ms)

83,5

713,5

-6,225<= /o:p>

0=

Tiempo de Pr= oc. Snapshot (ms)

436,5

1066,5<= /o:p>

-2,081<= /o:p>

0,037

Tiempo de Pr= oc. Iniciar (ms)

355,5

985,5

-3,028<= /o:p>

0,002

Tiempo de Pr= oc. Apagar (ms)

407

1037

-2,426<= /o:p>

0,015

Tiempo de Pr= oc. Reiniciar (ms)

394,5

1024,5<= /o:p>

-2,571<= /o:p>

0,01

Tiempo de Pr= oc. Suspender (ms)

265,5

895,5

-4,085<= /o:p>

0=

Tiempo de Pr= oc. Reanudar (ms)

372,5

1002,5<= /o:p>

-2,827<= /o:p>

0,005

Tiempo de Pr= oc. Bloquear (ms)

414

1044

-2,34

0,019

Tiempo de Pr= oc. DesBloquear (ms)

357,5

987,5

-3,013<= /o:p>

0,003

Tiempo de Pr= oc. Ingreso (ms)

121,5

751,5

-5,835<= /o:p>

0=

&n= bsp;

En la figura 6 se observa la comparación de las me= dias estadísticas de cada tarea de la dimensión Tiempo de Procesamiento, en la q= ue se observa que OpenStack obtiene un mejor desempeńo ya que requiere de menos tiempo en segundos para ejecutar las tareas.

Figura 6

Comparación de las medias del tiempo de procesamiento por tarea

Consolidando los datos del tiempo de procesamiento= se realiza un análisis de todas las tareas, procediendo a la prueba de normali= dad, como en este caso la cantidad de datos supera las 50 pruebas, por lo que se utiliza la fórmula de Kolmogorov-Smirnov, donde se evidencia con un nivel de significancia de 0, que los datos NO poseen una distribución normal como se observa en la tabla 9.                =

Tabla 9

Pr= ueba de normalidad del Tiempo de procesamiento

Tipo Plataforma

Kolmogorov-S= mirnova

Estadístico<= o:p>

gl

Sig.

Tiempo de Procesamiento (ms.)<= /p>

OpenStack

,310

385

,000

CloudStack

,317

385

,000

Realizando la prueba de contraste se observa que el valor de la significancia asintótica es menor a 0.05 por lo tanto se eviden= cia que, SI existe una diferencia significativa en cuanto al tiempo de procesamiento entre las dos plataformas motivo del estudio, con lo cual se corrobora el análisis previo con cada tarea de la dimensión del tiempo de procesamiento = (ver tabla 10).

Tabla 10

Pr= ueba de contraste del consolidado del tiempo de procesamiento<= /i>

Tiempo de Procesamiento (ms.)

Máximas diferencias extremas

Absoluta

,117

Positivo

,117

Negativo

0,000

Z de Kolmogorov-Smirnov

1,622

Sig. asintótica (bilateral)

,010

En la figura 7 se observa la comparación del tiemp= o de procesamiento entre las dos plataformas, donde OpeStack obtiene un mejor rendimiento al requerir un promedio de 10.3 segundos, frente a los 10.9 segundos de CloudStack para completar las tareas.

Figura 7

Co= mparación del tiempo de procesamiento

Dimensión Consumo de recursos<= o:p>

Para la dimensión del consumo de recursos se ha dividido en 4 indicadores:

·      =    Uso de memoria RAM, expresado en Giga Bytes de utilización.

·      =    Uso de CPU, expresado en porcentaje de utilización.

·      =    Lectura de Disco, expresado Kilo Bytes= de utilización y,

·      =    Tráfico de red entrante y saliente expresados en Kilo Bytes.

Para la recolección de los datos de cada indicador= se utilizó la consola de rendimiento de Proxmox como se observa en la figura 8= , 9, 10 y 11.

Figura 8

Consola de rendimiento (uso de RAM)

Figura 9

Consola de rendimiento (uso de CPU)=

Figura 10

Co= nsola de rendimiento (Lectura de disco)

Figura 11

Co= nsola de rendimiento (Tráfico de red)

En la tabla 11 se observan los resultados de l= as pruebas de normalidad para cada indicador, donde se evidencia que únicamente los datos del indicador “Lectura de disco” (en ambas plataformas) y “Tráfic= o de Red Entrante” de Cloud Stack presentan un comportamiento normal, por lo tan= to para el análisis de contraste de los indicadores RAM, CPU y Tráficos de Red= se utilizó la prueba de U de Man-Whitney mientras que para la Lectura de Disco mediante la prueba t.

Tabla 11

Pr= ueba de normalidad de datos de consumo de recursos

Tipo

Shapiro-Wilk=

Estadístico<= o:p>

gl

Sig.

RAM

OpenStack

,780

35

,000

CloudStack

,928

35

,024

CPU

OpenStack

,205

35

,000

CloudStack

,305

35

,000

DISCO

OpenStack

,964

35

,293

CloudStack

,965

35

,314

Tráfico de Red Entrante

OpenStack

,915

35

,010

CloudStack

,948

35

,098

Tráfico de Red Saliente

OpenStack

,511

35

,000

CloudStack

,580

35

,000

En la tabla 12 se observa = los resultados de las pruebas de contraste para los datos no normales correspondientes a la utilización de RAM, CPU y Tráfico de Red (Entrante y Saliente), donde se evidencia que el nivel de significancia tanto para la R= AM, CPU y Tráfico Saliente es menor a 0,05, por lo tanto, SI existe una diferen= cia significativa, mientras que para el Tráfico Entrante el valor es 0.391 mayo= r a 0,05 por lo tanto NO existe una diferencia significativa entre las platafor= mas.

Tabla 12

Pr= uebas de contraste de las subdimensiones Uso de Memoria RAM, Uso de CPU y Tráfico= de Red

RAM

CPU

Tráfico de R= ed Entrante

Tráfico de R= ed Saliente

U de Mann-Whitney

389,500=

306,500=

539,500=

310,500=

W de Wilcoxon

1019,500

936,500=

1169,500

940,500=

Z

-2,627<= /o:p>

-3,600<= /o:p>

-,858

-3,567<= /o:p>

Sig. asintótica (bilateral)

,009

,000

,391

,000

En la figura 11 se muestran las comparaciones de las medias estadísticas de los indicadores donde si ex= iste una diferencia significativa, como son los casos de Uso de RAM, CPU y Tráfi= co Saliente, se observa que de igual manera OpenStack tiene una ligera ventaja= al requerir menor cantidad de recursos para llevar a cabo el trabajo.

Figura 12

Co= mparación de las medias estadísticas de las dimensiones con diferencia significativa<= o:p>

La tabla 13 muestra los resultados de la prueba de contraste de los datos normales correspondientes= a la Lectura de disco, utilizando la prueba t se obtiene un nivel se significancia de 0.186, cuyo valor es mayor a 0.05, con lo cual se evidencia que no existe una diferencia significativa entre las plataformas en esta dimensión.

Tabla 13

Pr= ueba de contraste de la subdimensión Lectura de Disco

Suma de cuadrados

gl

Media cuadrá= tica

F=

Sig.

Entre grupos

107,409=

1=

107,409=

1,788

,186

Dentro de grupos

4084,206

68

60,062<= /o:p>

Total

4191,615

69

Dimensión de Eficac= ia<= /h2>
Para la dimensión de eficacia se tomó en cuenta las tareas llevadas a cabo sin erro= res, que en ambas plataformas se completaron satisfactoriamente.

Datos consolidados<= /span><= /h2>
Una vez obtenidos los resultados del análisis de t= odas las dimensiones, se obtiene la tabla de medias estadísticas de cada dimensi= ón como se observa en la tabla 14.

Tabla 14

Ma= triz de Impacto del Análisis Multicriterio con NAIADE

Dimensi= ones y Variables

Unidad = de Medida

Tipo

Objetiv= o

OpenSta= ck

CloudSt= ack

Tiempo de Respuesta

Miliseg= undos

Cuantit= ativa

Minimiz= ar

467.74<= o:p>

473

Tiempo de Procesamiento

Miliseg= undos

Cuantit= ativa

Minimiz= ar

10303.1=

10923.8=

Uso de RAM

MegaByt= es

Cuantit= ativa

Minimiz= ar

10.3817=

10.4751=

%Uso de CPU

Porcent= aje

Cuantit= ativa

Minimiz= ar

4.5206<= o:p>

4.6449<= o:p>

Lectura de Disco

Kilobyt= es

Cuantit= ativa

Minimiz= ar

123.639=

126.117=

Tráfico Red Entrante

Kilobyt= es

Cuantit= ativa

Minimiz= ar

2.5657<= o:p>

2.606

Tráfico Red Saliente

Kilobyt= es

Cuantit= ativa

Minimiz= ar

35.2003=

35.9477=

Aplicando la fórmula de variación porcentual (Fórm= ula 1) especificada en el apartado 3.4 (Procesamiento y Análisis), se obtiene la tabla 15 con los datos consolidados donde se muestra la diferencia porcentu= al en los casos donde hubo una diferencia significativa como son: el tiempo de= procesamiento, y consumo de recursos (utilización de memoria RAM, utilización de CPU y Trá= fico de Salida).

Tabla 15<= /span>

Datos consolidados del análisis de las dimensiones.

Dimensión

Diferencia Significativa

Mejor Plataf= orma

Diferencia Porcentual

Tiempo de respuesta

NO

-=

-=

Tiempo de procesamiento

SI

OpenStack

5.68%

Consumo de Recursos: RAM

SI

OpenStack

0.89%

Consumo de Recursos: CPU

SI

OpenStack

2.67%

Consumo de Recursos: Lectura de Disco

NO

-=

-=

Consumo de Recursos: Tráfico de Red de Entrada

NO

-=

-=

Consumo de Recursos: Tráfico de Red de Salida

SI

OpenStack

2.07%

Análisis multicriterio

Adicionalmente, para obtener un resultado general = se utilizó el análisis multicriterio con el método NAIADE propuesto por Munda = (2006), en la tabla 12 se muestran la matriz de impacto con las medias estadísticas obtenidas por cada dimensión e indicador la cual fue ingresada en el progra= ma informático.

Como resultado de la prueba de verdad se obtiene q= ue, tomando en cuenta los diferentes criterios NO se evidencia que exista una diferencia entre ambas plataformas, como se observa en la figura 13.

Figura 13

Prueba de verdad del análi= sis Multicriterio con NAIADE

Conclusiones

·      =    Las plataformas OpenStack y CloudStack= son en la actualidad alternativas ampliamente utilizadas para la implementación= de soluciones iCloud, permitiendo el ahorro de costos de licenciamiento en las organizaciones que requieren de estos servicios.

·      =    Mediante el análisis multicriterio de NAIADE se constató que no existe una diferencia marcada entre las plataform= as OpenStack y CloudStack en los diferentes criterios, mientras que realizando= un análisis estadístico más detallado e individual por cada dimensión, se evidenció que existe una diferencia significativa a favor de OpenStack en la dimensión de tiempo de procesamiento con un 5.68% de mejora así como en los indicadores de uso de RAM 0.89%, u= so de CPU 2.67% y Tráfico de Red Saliente 2.07%.

·      =    El utilizar la virtualización anidada permitió simular escenarios reales para las pruebas tanto para Openstack y Cloudstack. En la implementación de la plataforma Openstack utilizando la arquitectura por Nodos Separados se obtuvo un mejor resultado en cuanto al rendimiento frente a la arquitectura Todo en Uno.

Conflicto de intere= ses

Los autores declaramos no tener ningún tipo de conflicto de intereses en relación con el artículo presentado.

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------=_NextPart_01DA6322.6E732A10 Content-Location: file:///C:/132AC093/07VALERIAILLPA-Comparaciondelrendimientoentrelasplataformas_archivos/header.htm Content-Transfer-Encoding: quoted-printable Content-Type: text/html; charset="windows-1252"

= ISSN: 2602-8085

= Vol. 8 No. 1, pp. 145 – 172, en= ero – marzo 2024

145<= /span> | 172

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= ¹<= /p>	Valeria Estefanía Illapa Robles		https://orcid.org/0009-0008-8828-690X
= =	Universidad Nacional de Chimborazo (UNACH), Riobamba, Ecuador, Campus Norte. villapa.fis@unach.edu.ec
= ²<= /p>	Jhony = Javier Marcatoma Morocho		https://orcid.org/0009-0009-6869-3978
= =	Universidad Nacional de Chimborazo (UNACH), Riobamba , Ecuador, Campus Norte <= span style=3D'mso-ansi-language:ES-EC'>jmarcatoma.fis@unach.edu.ec =
3	Paul <= /span>Xavier Paguay Soxo	<= /span>	https://orcid.org/0000-0002-0262-9844
<= /span>	Escuela Superior Politécnica de Chimborazo (ESPOCH), Riobamba, Ecuador, Campus Ce= ntro Sede Orellana Av. 9 de octubre entre Quito y Napo. Maestría en Interconectividad en Redes ppaguay@espoch.edu.ec
= ⁴=	René Alfonso Barragán Torres	<= /span>	https://orcid.org/0009-0001-9790-0608
<= /span>	Escuela Superior Politécnica de Chimborazo (ESPOCH), Riobamba, Ecuador, Campus Ce= ntro Sede Orellana Av. 9 de octubre entre Quito y Napo. Maestría en Interconectividad en Redes rene.barrag= an@espoch.edu.ec
= ⁵=	Joffre Stalin Monar	<= /span>	https://orcid.org/0000-0002-6534-183X
<= /span>	Escuela Superior Politécnica de Chimborazo (ESPOCH), Riobamba, Ecuador, Campus Ce= ntro Sede Orellana Av. 9 de octubre entre Quito y Napo. Maestría en Seguridad Telemática jmonar@espoch.edu.ec

	Artículo de Investigación Científica y Tecnológica Enviado: 15/10/2023 Revisado: 10/11/2023 Aceptado: 04/12/2023 Publicado:30/01/2024 DOI: https://doi.org/10.33262/c= ienciadigital.v8i1.2877

Cítese:		Illapa Robles, V. E., Marcatoma Morocho= , J. J., Paguay Soxo, P. X., Barragán Torres, R. A., & Monar, J. S. (2024). Comparación del rendimiento entre las plataformas para IAAS Open Source: OpenStack y CloudStack. Ciencia Digital, 8(1), 145-172. https://doi.or= g/10.33262/cienciadigital.v8i1.2877
		CIENCIA DIGITAL, es una revista multidisciplinaria, trimestral, que se publicará en soporte electrónico tiene como misión contribuir a la formación de profesionales competentes con vi= sión humanística y crítica que sean capaces de exponer sus resultados investigativos y científicos en la misma medida que se promueva mediante = su intervención cambios positivos en la sociedad. = https://cienciadigital.org La revista es editada por la Editorial Ciencia Digital (Editorial de prestigio registrada en la Cámara Ecuatoria= na de Libro con No de Afiliación 663) www.celibro.org.ec
		Esta revista está protegida bajo una licencia Creative Commons Atribución-NoComercial-CompartirIgual 4.0 International. Copia de la licencia: https://creativecommons.org/licenses/by-nc-sa/4.0/deed.es<= /span>
Palabras claves: = OpenStack, CloudStack, IaaS, rendimiento, Nube Privada, Cloud Computing		Resumen Introducción: La implementación de una plataforma IaaS en la UNACH representa una gran oportunidad para mejorar la infraestructura tecnológica de la institución, fortalecer las capacidades de estudiantes y docentes, y promover la innovación y la competitividad. Objetivo: Comparar las plataformas OpenSta= ck y CloudStack mediante el rendimiento en un entorno virtualizado para la implementación de una nube privada en la Universidad Nacional de Chimbora= zo. Metodología: El establecimiento del escenario contó = con la instalación de tres nodos: el nodo controlador, el nodo cómputo y un n= odo de almacenamiento desplegados sobre Proxmox VE. Resultados: Se realizó el análisis de cada dimensión obtenidos del Modelo de FURPS con una muestra de 35 pruebas, un porcentaje de error del 0.05%, verificando = en primera instancia la normalidad de los datos y posteriormente las pruebas= de contraste correspondientes, obteniendo de esta manera para la dimensión de Tiempo de proces= amiento una diferencia de 5.6% de mejor desempeńo a favor de OpenStack así también en los indicadores de Uso de R= AM con un 0.89%, Uso de CPU con un 2.67% y Tráfico de Red Saliente con un 2.= 07%. Conclusión: Se calculó un resultado general a través de un análisis multicriterio con= el método de NAIADE obteniendo que el desempeńo es similar. Área de estudio gener= al: Computación. Área de estudio específica: Computación en la nube.
Keywords: OpenStack, CloudStack, IaaS, rendimiento, Nube Privada, Cloud Computing		Abstract Introduction: The implementation of= an IaaS platform at UNACH represents a great opportunity to improve the technological infrastructure of the institution, strengthen the capacitie= s of students and teachers, and promote innovation and competitiveness. Obj= ective: To compare OpenStack and CloudStack platforms through performance in a virtualised environment for the implementation of a private cloud at the National University of Chimborazo. Methodology: The establishment of the scenario included the installation of thr= ee nodes: the controlling node, the computation node and the storage node deployed on Proxmox VE. R= esults: The analysis of each of the dimensio= ns of the FURPS model was carried out with a sample of 35 tests, an error rate = of 0.05%, the first time the normality of the data and the corresponding contrast tests, obtaining this way for the processing time of a differenc= e of 5.6% The best use of OpenStack The use of RAM with 0.89%, The use of the = CPU with 2.67% and Outgoing Network Traffic with a 2.07%. Conclusion: a general result was calculated through a multicriteria analysis w= ith the NAIADE method, obtaining that the performance is similar. =

CRITERIO	DETALLE=
FOCALIZACIÓN	= En el siguiente proyecto de investigación se pretende dar respuesta a la siguiente pregunta: żCuál de las dos plataformas: OpenStack y CloudStack ofrecen un mejor rendimiento en la implementación de la nube privada de la Universidad Nacional de Chimborazo?
ESTRATEGIA DE BÚSQUEDA:	ÁREA: OpenStack y CloudStack, medición del rendimiento de las plataformas Open Source OpenS= tack y CloudStack en la implementación de una nube privada.<= /p> PROPÓSITO DE= LA BÚSQUEDA: Analizar las características y funcionalidades de las plataformas Open Source: OpenSta= ck y CloudStack, para seleccionar la más adecuada e implementar una nube priva= da.
FUENTES DE INFORMACIÓN	Books, Journal, Technical Report, PhD thesis, Handbook.=
MOTORES DE BÚSQUEDA	ProQuest, Sc= opus
CRITERIOS DE BÚSQUEDA	“Performance” Openstack AND Cloudstack "OpenStack" AND "CloudStack"= “Private Cloud” “Cloud Computing iaas”
CRITERIOS DE= SELECCIÓN	Documentos q= ue contengan información sobre las características y funcionalidades de las plataformas Open Source: OpenStack y CloudStack que nos permitan medir el rendimiento en la implementación de una nube privada.
CRITERIOS DE EXCLUSIÓN	ü Se excluyen documentos que analicen otras características difere= ntes al rendimiento como: la portabilidad, seguridad, disponibilidad, integrid= ad, fiabilidad. ü Información que se encuentre inferior al 2013.= ü Todas las plataformas que no sean Open Source.=
CRITERIOS DE EVALUACIÓN DE CONTENIDO	Exactitud, objetividad, cobertura, vigencia, relevancia en función a la pregunta de investigación. Se investiga en autores que han hecho aportes a = los artículos consultados.
ANÁLISIS DE INFORMACIÓN	Se proporcio= na una visión general para medir el rendimiento en la implantación de una nu= be privada, para lo cual se analizará dos plataformas Open Source: OpenStack= y CloudStack, determinando la óptima ya que no existe un estudio comparativo entre estas dos plataformas acerca del rendimiento que ofrecen las mismas= .
QUERY	PROQUEST	SCOPUS	TOTAL
“Performance” Openstack AND Cloudstack	153	14	167
"OpenSt= ack" AND "CloudStack"	343	38	381
“Private Cloud” “Cloud Computing iaas”	7	1	8
TOTAL:<= /o:p>	503	53	556

Plataforma d= e virtualización	Proxmox VE 4= .2-2
RAM	78..63 GB
CPU	12 x Intel(R) Xeon(E) CPU E5-2620 2GHz (1 Socket)
Disco Duro	300 GB<= /o:p>

Revisión Bibliográfica

Tipo De Estudio

Población y Muestra= <= /h2> Para el análisis de los indicadores la muestra utilizada es 35 pruebas, para cada una de las dimensiones con sus diferentes indicadores.

Procesamiento y Análisis<= o:p>

Indicadores de evaluación del rendimiento<= /o:p>

Herramientas de Análisis

Escenario

Dimensión Tiempo de respuesta<= o:p>

Dimensión Tiempo de procesamiento

Dimensión Consumo de recursos<= o:p>

Dimensión de Eficac= ia<= /h2> Para la dimensión de eficacia se tomó en cuenta las tareas llevadas a cabo sin erro= res, que en ambas plataformas se completaron satisfactoriamente.

Análisis multicriterio

Población y Muestra= <= /h2>
Para el análisis de los indicadores la muestra utilizada es 35 pruebas, para cada una de las dimensiones con sus diferentes indicadores.

Dimensión de Eficac= ia<= /h2>
Para la dimensión de eficacia se tomó en cuenta las tareas llevadas a cabo sin erro= res, que en ambas plataformas se completaron satisfactoriamente.