Efficient Grid-Based Video Storage and Retrieval

  • Authors:
  • Pablo Toharia;Alberto Sánchez;José Luis Bosque;Oscar D. Robles

  • Affiliations:
  • Dpto. de Arquitectura y Tecnología de Computadores, Ciencia de la Computación e Inteligencia Artificial, Móstoles Madrid, Spain 28933;Dpto. de Arquitectura y Tecnología de Computadores, Ciencia de la Computación e Inteligencia Artificial, Móstoles Madrid, Spain 28933;Dpto. de Eléctronica y Computadores, U. Cantabria, Santander, Spain 39005;Dpto. de Arquitectura y Tecnología de Computadores, Ciencia de la Computación e Inteligencia Artificial, Móstoles Madrid, Spain 28933

  • Venue:
  • OTM '08 Proceedings of the OTM 2008 Confederated International Conferences, CoopIS, DOA, GADA, IS, and ODBASE 2008. Part I on On the Move to Meaningful Internet Systems:
  • Year:
  • 2008

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Abstract

Different fields, such as news broadcasting (news, shows, series, etc), advertising, and medical applications, require to store a large amount of video data which can be used later on. Content-Based Video Retrieval (CBVR) systems are very attractive since they can help users to retrieve video sequences over large video databases with respect to some specific topic, character or place. In most cases, stored videos belong to different organizations and have a quite demanding storage capacity. These features fit in a natural way into the concept of grid computing, that provides a great computing and storage capacity thanks to the use of heterogeneous resources put together by the cooperation and resource sharing among different institutions. This paper presents a Grid and Content-based VIdeo Retrieval (GCViR) system that offers a good cost/performance ratio to select the most suitable grid resources for data storage in order to store and retrieve large video data providing flexibility and scalability. An evaluation shows the feasibility and benefits of this approach.