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Multimedia prefetching with optimal Markovian policies

Pleşca, Cezar and Charvillat, Vincent and Tsang Ooi, Wei Multimedia prefetching with optimal Markovian policies. (2016) Journal of Networks and Computer Applications, 69. 40-53. ISSN 1084-8045

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Official URL: https://doi.org/10.1016/j.jnca.2016.05.002

Abstract

Multimedia prefetching is able to reduce the end-to-end latency and improve the video quality perceived by users. Previous work modeled prefetching as applying sequential decisional policies under uncertainty, using a Markov Decision Process model that integrated both user behavior and resources availability, to achieve optimal prefetching policies under realistic assumptions. In this paper, we extended the existing MDP model by considering more complex and aggressive policies, while preserving the optimality of the prefetching policy. We further enriched the extended model by considering user's profile to provide finer prefetching policies. The proposed extensions and the associated policies are validated through comparison against the existing model and against heuristics found in related work. We showed that our profiles-aware optimal policies can be achieved up to 28% latency reduction with respect to known heuristics.

Item Type:Article
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE)
Other partners > Military Technical Academy (ROMANIA)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UPS (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Other partners > National University of Singapore - NUS (REPUBLIC OF SINGAPORE)
Laboratory name:
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Deposited By: IRIT IRIT
Deposited On:21 Feb 2019 08:34

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