Semantic Based Prefetching in News-on-Demand Video Servers

  • Authors:

  • Ahmed Mostefaoui;Harald Kosch;Lionel Brunie

  • Affiliations:

  • Information Systems Engineering Laboratory, National Institute of Applied Sciences Lyon, France. Ahmed.Mostefaoui@insa-lyon.fr;Institute of Information Technology, University Klagenfurt, Austria. harald.kosch@itec.uni-klu.ac.at;Information Systems Engineering Laboratory, National Institute of Applied Sciences Lyon, France. Lionel.Brunie@insa-lyon.fr

  • Venue:
  • Multimedia Tools and Applications
  • Year:
  • 2002

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Abstract

In video databases, a video document has two abstractions. The high level abstraction corresponds to the view in which the contents of that video document are seen by end users, and the low level abstraction corresponds to the physical organization of that video document. Due to the huge size of continuous data, reducing I/O has become a key issue. The latter has been mostly addressed by developing appropriate buffering techniques. In addition, prefetching techniques play a major role to meet the video data requirements. In this paper, we propose a novel prefetching strategy based not only on run-time information (objects access frequencies for example) but also on knowledge about clips structures. The proposed technique merges the two views of a video document to trigger prefetching at the video server level. Simulation experiments for a News-on-Demand application performed on different request scenarios show an improvement of about 18% in the buffer hit-rate with respect, first to the available buffer size and second to the request arrival rate.