A Complexity-Aware Video Adaptation Mechanism for Live Streaming Systems
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Research Article A Complexity-Aware Video Adaptation Mechanism for Live Streaming Systems Meng-Ting Lu,1 Jason J. Yao,1 and Homer H. Chen2 1 Department
of Electrical Engineering, Graduate Institute of Communication Engineering, National Taiwan University, Taipei 10617, Taiwan 2 Department of Electrical Engineering, Graduate Institute of Communication Engineering, and Graduate Institute of Networking and Multimedia, National Taiwan University, Taipei 10617, Taiwan Received 3 October 2006; Accepted 21 March 2007 Recommended by Alex Kot The paradigm shift of network design from performance-centric to constraint-centric has called for new signal processing techniques to deal with various aspects of resource-constrained communication and networking. In this paper, we consider the computational constraints of a multimedia communication system and propose a video adaptation mechanism for live video streaming of multiple channels. The video adaptation mechanism includes three salient features. First, it adjusts the computational resource of the streaming server block by block to provide a fine control of the encoding complexity. Second, as far as we know, it is the first mechanism to allocate the computational resource to multiple channels. Third, it utilizes a complexity-distortion model to determine the optimal coding parameter values to achieve global optimization. These techniques constitute the basic building blocks for a successful application of wireless and Internet video to digital home, surveillance, IPTV, and online games. Copyright © 2007 Meng-Ting Lu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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INTRODUCTION
Multimedia streaming is one of the most challenging services over the Internet, for which bandwidth is a primary constraint. For live streaming of multiple channels, the computational resource also becomes a critical issue. Our objective of this work is to develop a video adaptation mechanism to control the allocation of both bandwidth and computational resources for live streaming. The problem of resource-constrained video coding has been the focus of research for the past several decades. For bandwidth constraint, various rate-distortion (R-D) models [1–4] have been proposed to deal with the tradeoff between information rate and distortion. For computational resource constraint, many algorithms have been developed to regulate the complexity of an encoder. Tai et al. [5] reported a software-based computation-aware scheme that terminates the searching process once a specified amount of computation has been reached. Chen et al. [6] developed an adaptive search strategy to find the best block matching in a computation-limited environment. Zhao and Richardson [7] designed adaptive algorithms for DCT and motion estimation to reduce the complexity of each function and maintain
the computational cost at the target level. Zhong and C
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