Efficient personalized scalable video adaptation decision-taking engine based on MPEG-21

This paper presents a novel algorithm designed to efficiently adapt scalable video. The algorithm is able to take the optimal decision among all possible video adaptations. It takes into account information about network, user terminal and user preferences. This information is gathered together by means of MPEG-21 DIA descriptors. The optimal adaptation option is achieved through the application of the Viterbi algorithm. The results prove that the presented decision-taking engine offers an optimal and efficient solution for personalized scalable video adaptation in heterogeneous environments.