Article details

Title: Improving Hypermedia Delivery Using Prefetching Techniques
Author(s): Cezar Pleşca   Vincent Charvillat   Romulus Grigoraş         

Abstract: Interaction with hypermedia documents is a required feature for new sophisticated, yet flexible, multimedia applications. This paper deals with hypermedia content delivery aiming to reduce navigation latencies by means of prefetching. The problem is solved using two methods: classical stochastic dynamic programming algorithms and reinforcement learning. We build upon a formal framework able to derive optimal prefetching strategies integrating both user behavior and resources availability. We extend this framework and propose more complex and aggressive policies. The proposed extensions and the associated strategies are validated through comparison with the original model and some heuristic approaches.

Keywords: prefetching policies, hypermedia, Markov Decision Processes, multimedia, reinforcement learning.

[1] R. GRIGORAŞ – Supervision de flux dans les contenus hypermédia: Optimisation de politiques de préchargement et ordonnancement causal, Thèse de doctorat, Institut National Polytechnique de Toulouse, France, 2003
[2] C. PLEŞCA – Supervision de contenus multimédia: Adaptation de contenu, politiques optimales de préchargement et coordination causale de flux, Thèse de doctorat, Institut National Polytechnique de Toulouse, France, 2007
[3] A. MOSTEFAOUI, H. KOSCH, L. BRUNIE – Semantic Based Prefetching in News-on-Demand Video Servers, Multimedia Tools and Applications, Vol. 18, No. 2, pp. 159-179, Nov. 2002
[4] N.J. TUAH, M. KUMAR, S. VENKATESH – Investigation of a Prefetch Model for Low Bandwidth Networks, Proc. of the 1st ACM International Workshop on Wireless Mobile Multimedia, WoWMoM 1998, pp. 38-47, Dallas, TX, Oct. 30, 1998
[5] N.J. TUAH, M. KUMAR, S. VENKATESH – Resource-Aware Speculative Prefetching in Wireless Networks, Wireless Networks, Vol. 9, No. 1, pp. 61-72, Jan. 2003
[6] M. ANGERMANN – Analysis of Speculative Prefetching, ACM Mobile Computing and Communications Review, Vol. 6, No. 2, pp. 13-17, Apr. 2002
[7] M.L. PUTERMAN – Markov Decision Processes: Discrete Stochastic Dynamic Programming, John Wiley & Sons, New York, NY, 1994
[8] MPEG-21 Multimedia Framework, MPEG Group,
[9] B. TROUSSE – Evaluation of the Prediction Capability of a User Behaviour Mining Approach for Adaptive Web Sites, Proc. of the 6th RIAO Conference on Content-Based Multimedia Information Access, RIAO 2000, Paris, France, Apr. 12-14, 2000
[10] T. SYEDA-MAHMOOD, D. PONCELEON – Learning Video Browsing Behavior and Its Application in the Generation of Video Previews, Proc. of the 9th ACM International Conference on Multimedia, pp. 119-128, Ottawa, Canada, 2001
[11] N. SAWHNEY, D. BALCOM, I. SMITH – Authoring and Navigating Video in Space and Time: A Framework and Approach towards Hypervideo, IEEE Multimedia, Vol. 4, No. 4, pp. 30-39, 1997
[12] J. TOLVA – MediaLoom: An Interactive Authoring Tool for Hypervideo, Master’s Thesis, Georgia Institute of Technology, Atlanta, GA, 1998
[13] R.S. SUTTON, A.G. BARTO – Reinforcement Learning: An Introduction, MIT Press, Cambridge, MA, 1998