The emergence of cloud encoding services facilitates many content owners, such as the online video vendors, to transcode their\r\ndigital videos without infrastructure setup. Such service provider charges the customers only based on their resource consumption.\r\nFor both the service provider and customers, lowering the resource consumption while maintaining the quality is valuable and\r\ndesirable. Thus, to choose a cost-effective encoding parameter, configuration is essential and challenging due to the tradeoff\r\nbetween bitrate, encoding speed, and resulting quality. In this paper, we explore the feasibility of an automatic parameter-tuning\r\nframework, based on which the above objective can be achieved.We introduce a simple service model, which combines the bitrate\r\nand encoding speed into a single value: encoding cost. Then, we conduct an empirical study to examine the relationship between\r\nthe encoding cost and various parameter settings. Our experiment is based on the one-pass Constant Rate Factor method in x264,\r\nwhich can achieve relatively stable perceptive quality, and we vary each parameter we choose to observe how the encoding cost\r\nchanges. The experiment results show that the tested parameters can be independently tuned to minimize the encoding cost,\r\nwhich makes the automatic parameter-tuning framework feasible and promising for optimizing the cost on video encoding cloud.
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