Enabling resource scheduling in cloud distributed videoconferencing systems

Alonso González, Álvaro; Rodríguez Pérez, Pedro; Aguado Cortezón, Ignacio y Salvachúa Rodríguez, Joaquín (2016). Enabling resource scheduling in cloud distributed videoconferencing systems. En: "The Seventh International Conferences on Cloud Computing, GRIDs, and Virtualization (CLOUD COMPUTING 2016)", 20/03/2015 - 24/03/2015, Rome, Italy. pp. 51-56.

Descripción

Título: Enabling resource scheduling in cloud distributed videoconferencing systems
Autor/es:
  • Alonso González, Álvaro
  • Rodríguez Pérez, Pedro
  • Aguado Cortezón, Ignacio
  • Salvachúa Rodríguez, Joaquín
Tipo de Documento: Ponencia en Congreso o Jornada (Artículo)
Título del Evento: The Seventh International Conferences on Cloud Computing, GRIDs, and Virtualization (CLOUD COMPUTING 2016)
Fechas del Evento: 20/03/2015 - 24/03/2015
Lugar del Evento: Rome, Italy
Título del Libro: The Seventh International Conferences on Cloud Computing, GRIDs, and Virtualization (CLOUD COMPUTING 2016)
Fecha: 2016
Materias:
Palabras Clave Informales: Cloud computing; videoconferencing; distributed MCU; scheduling
Escuela: E.T.S.I. Telecomunicación (UPM)
Departamento: Ingeniería de Sistemas Telemáticos [hasta 2014]
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

When deploying videoconferencing systems in Cloud based infrastructures, one of the most complex challenges is to distribute Multipoint Control Units (MCUs) among different servers. By addressing this challenge, we can improve the flexibility and the performance of this type of systems. However, to actually take advantage of the Cloud possibilities we have also to introduce mechanisms to dynamically schedule the distribution of the MCUs across the available resources. In this paper, we propose a resource scheduling model for videoconferencing systems and, starting from an existing MCU distribution architecture, we design a solution to enable the resource scheduling basing on custom criteria. These criteria can be based on the characteristics of each server or in their status in real time. We validate the extended model by setting up a typical videoconferencing deployment among a set of Cloud providers and testing a decision algorithm. We conclude that the proposed model enables the use of a wide range of algorithms that can be adapted to the needs of different Cloud deployment.

Más información

ID de Registro: 42825
Identificador DC: http://oa.upm.es/42825/
Identificador OAI: oai:oa.upm.es:42825
URL Oficial: https://www.thinkmind.org/download.php?articleid=cloud_computing_2016_3_20_20042
Depositado por: Memoria Investigacion
Depositado el: 17 Jul 2016 09:18
Ultima Modificación: 17 Jul 2016 09:18
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