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Multimedia decoding is one of the key parts of many popular mobile multimedia applications, such as video telephony, streaming, and video playback. Since the multimedia decoding consumes a significant amount of energy on processors, it is crucial to lower the power consumption and prolong the battery life. In this paper, the statistical analysis of more than 600 processor load trace files is first presented. From the analysis, we found that it is feasible to predict the processor load of multimedia applications accurately using a low order linear time series model if the load is sampled using the feature period, which is obtained with Fast Fourier Transformation. Based on the analysis, we propose a novel interval-based DVS scheme to achieve penalty controllable energy reduction. The DVS scheme does not need any task profile or involvement of application program, and it is compatible with the service model of general purpose mobile operating systems. In addition, the proposed DVS scheme can handle the nonstationary behavior using an efficient online change detector, and important parameters, such as coefficients of the linear time series model, are estimated on the fly. More importantly, the proposed scheme can keep the Overscaling Rate (OSR) around a certain predefined value. Since the OSR has a simple and stable relationship with the Deadline Miss Rate (DMR), the penalty incurred by DVS is effectively controlled. Experimental results show that the proposed DVS scheme achieves a much smaller prediction error than previous approaches and achieves a significant processor energy reduction with adjustable and controlled penalty.
Low power, Dynamic Voltage Scaling, mobile multimedia.

R. Y. Yao, Z. Guo, M. Li and W. Zhu, "A Novel Penalty Controllable Dynamic Voltage Scaling Scheme for Mobile Multimedia Applications," in IEEE Transactions on Mobile Computing, vol. 5, no. , pp. 1719-1733, 2006.
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