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Designing a real-time video-streaming system involves the challenges of, network congestion and bandwidth fluctuations, lowering the video quality. In this paper, a realtime video-streaming system is designed and implemented for scalable video coding (SVC) with an adaptive control scheme, containing macro- and micro-control, to resolve the bandwidth fluctuation and network congestion. Under macro-control, the server allocates appropriated video-streaming of SVC for heterogeneous clients based on terminal capacity and network conditions. Under micro-control, the server changes the video frame rate based on video bit rates and network bandwidth. The streaming system with the adaptive control scheme is implemented to improve the peak signal noise ratio (PSNR) by 4.01 % to 10.89 % of the Foreman and Stefan videos. [ABSTRACT FROM AUTHOR]

This paper presents a novel algorithm designed to efficiently adapt scalable video using MPEG-21. 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 decision on the optimal adaptation 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. [ABSTRACT FROM AUTHOR]