Hadoop, a distributed processing framework for big-data, is now widely used for multimedia processing. However, when processing video data from a Hadoop distributed file system (HDFS), unnecessary network traffic is generated due to an inefficient HDFS block slice policy for picture frames in video files. We propose a new block replication policy to solve this problem and compare the newly proposed HDFS with the original HDFS via extensive experiments. The proposed HDFS reduces network traffic, and increases locality between processing cores and file locations.

This paper analyzes the conventional unequal erasure protection (UXP) scheme for scalable video transmission, and proposes a dynamic hybrid UXP/ARQ transmission framework to improve the performance of the conventional UXP method for bandwidth-constrained scalable video transmission. This framework applies automatic retransmission request (ARQ) to the conventional UXP scheme for scalable video transmission, and dynamically adjusts the transmission time budget of each group of picture (GOP) according to the feedback about the transmission results of the current and previous GOPs from the receiver. Moreover, the parameter of target video quality is introduced and optimized to adapt to the channel condition in pursuit of more efficient dynamic time allocation. In addition, considering the play-out deadline constraint, the time schedule for the proposed scalable video transmission system is presented. Simulation results show that compared with the conventional UXP scheme and its enhanced method, the average peak signal to noise ratio (PSNR) of the reconstructed video can be improved significantly over a wide range of packet loss rates. Besides, the visual quality fluctuation among the GOPs can be reduced for the video which has much movement change.

The non-reference method is widely useful for picture quality estimation on the decoder side. In other work, we discussed pure non-reference estimation using only the decoded picture, and we proposed quantitative estimation methods for mosquito noise and block artifacts. In this paper, we discuss the estimation method as it applies to the degradation of the temporal domain. In the proposed method, motion compensated inter-picture differences and motion vector activity are the basic parameters of temporal degradation. To obtain these parameters, accurate but unstable motion estimation is used with a 1/16 reduction of processing power. Similar values of the parameters in the pictures can be seen in the stable original picture, but temporal degradation caused by the coding increases them. For intra-coded pictures, the values increase significantly. However, for inter-coded pictures, the values are the same or decrease. Therefore, by taking the ratio of the peak frame and other frames, the absolute value of the temporal degradation can be estimated. In this case, the peak frame may be intra-coded. Finally, we evaluate the proposed method using coded pictures with different quantization.