Abstract-This paper proposes the use of Adaptive LDPC AL-FEC codes for content download services over erasure channels. In Adaptive LDPC codes, clients inform the content download server of the losses they are experiencing. Using this information, the server makes FEC parity symbols available to the client at an optimum code rate. This paper presents an analytical model of the proposed Adaptive LDPC codes. The model is validated through measurements realized with an application prototype. Additionally, results show the performance of these codes in different scenarios, compared to the performance of nonadaptive AL-FEC, Optimum LDPC AL-FEC codes and an almost ideal rateless code. Adaptive LDPC AL-FEC codes achieve download times similar to almost ideal rateless codes with less coding complexity, at the expense of an interaction channel between server and clients.
Abstract. Multimedia content adaption strategies are becoming increasingly important for effective video streaming over the actual heterogeneous networks. Thus, evaluation frameworks for adaptive video play an important role in the designing and deploying process of adaptive multimedia streaming systems. This paper describes a novel simulation framework for rate-adaptive video transmission using the Scalable Video Coding standard (H.264/SVC). Our approach uses feedback information about the available bandwidth to allow the video source to select the most suitable combination of SVC layers for the transmission of a video sequence. The proposed solution has been integrated into the network simulator NS-2 in order to support realistic network simulations. To demonstrate the usefulness of the proposed solution we perform a simulation study where a video sequence was transmitted over a three network scenarios. The experimental results show that the Adaptive SVC scheme implemented in our framework provides an efficient alternative that helps to avoid an increase in the network congestion in resource-constrained networks.Improvements in video quality, in terms of PSNR (Peak Signal to Noise Ratio) and SSIM (Structural Similarity Index) are also obtained.
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