on balancing between transcoding overhead and spatial consumption in content adaptation
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.
transcode spatial content adaptation contention adapt method optimality point cost storage pre-adaptation generation dynamic input algorithm model collaboration environment component proxy server distributed complexity use simulation documentation systems mobile computing pervasive computing performance optimization