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On balancing between transcoding overhead and spatial consumption in content adaptation

机译:内容自适应中代码转换开销与空间消耗之间的平衡

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We propose a method that can find the optimal tradeoff point between transcoding overhead (CPU cost) and storage needed for the various pre-processed content variants (I/O cost). The method selectively pre-adapts a subset of content variants and leaves the generation of the residue to dynamic content adaptation with this pre-adapted subset as an input. We prove bounds regarding the optimality of the algorithm employed. The proposed model creates a collaborative environment across the components of client, proxy and server, based on which we study the distribution of adaptation complexity across these components. We use simulation to verify the projected benefits. The method has been successfully implemented in a trial PDF document content adaptation system.
机译:我们提出了一种方法,可以找到代码转换开销(CPU成本)和各种预处理的内容变体所需的存储(I / O成本)之间的最佳折衷点。该方法选择性地预适应内容变体的子集,并以该预适应的子集作为输入,将残差的生成留给动态内容适应。我们证明了关于所用算法的最优性的界限。所提出的模型在客户端,代理和服务器的各个组件之间创建了一个协作环境,在此基础上,我们研究了这些组件之间的适应复杂性分布。我们使用模拟来验证预期收益。该方法已在试用PDF文档内容修改系统中成功实现。

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