Design Analysis for Ensuring Multimedia QoS over Scarce Resource Network Applications

The existing multimedia software in e-learning does not provide par excellence multimedia data service to the common user; hence e-learning services are still short of intelligence and sophisticated end user tools for visualization and retrieval. Delivery of video in the presence of bandwidth constraints is one of the most important video processing problems. The work presents an innovative and complete end-to-end solution for e-learning multimedia delivery package for the client-server model. An efficient approach has been proposed to achieve content based embedded scalable motion compensated video compression, for the e-learning videos, to save and/or efficiently utilize the network bandwidth. The serious bottleneck in multimedia e-learning is the non-availability of required bandwidth. While much research has been done on multimedia compression and network resource optimization, multimedia delivery is still a big concern especially for scarce resource networks. The virtues of network aware video coding and application of domain specific compression techniques have not yet been fully explored. This work deals with the issue of intelligent transmission of important segments of the video sequence over scarce resource networks. We incorporate the knowledge of the network conditions to determine how various parts of the video frames are encoded. An estimate of the available network bandwidth is obtained which is then distributed optimally between the different frame constituents based on their relative importance and motion by the bandwidth allocation module. We have devised a simple approach to classify the videos into visual objects and used Discrete Wavelet Transform based Color Embedded Zerotree Wavelet (CEZW) coding to obtain a scalable bitstream that provides dynamic response to changing network conditions. The above approach helps to reach an optimal trade off between perceptual quality of the video and the available network bandwidth. The results are compared with the state of the art compression and transmission schemes over the network to illustrate the superior performance of our approach.