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Interactive scheduling for mobile multimedia service in M2M environment

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Abstract

Computational load of motion estimation in advanced video coding (AVC) standard is significantly high and its more true for HDTV sequences. In this paper, video processing algorithm is mapped onto a learning method to improve machine to machine (M2M) architecture, namely, the parallel reconfigurable computing (PRC) architecture, which consists of multiple units, First, we construct a directed acyclic graph (DAG) to represent the video coding algorithms comprising motion estimation. In the future trillions of devices are connected (M2M) together to provide services and that time power management would be a challenge. Computation aware scheme for different machine is reduced by dynamically scheduling usage of multi-core processing environment for video sequence depending up complexity of the video. And different video coding algorithm is selected depending upon the nature of the video. Simulation results show the effectiveness of the proposed method.

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Acknowledgments

This research is support by Kyungpook National University Research Fund 2012. This work was partially supported by URP-CEST 2013 [Undergraduate Research Program - Center for Embedded Software Technology], Kyungpook National University, Korea.

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Authors and Affiliations

  1. The School of Computer Science and Engineering, Kyungpook National University, Daegu, South Korea

    Anand Paul

  2. Department of Multimedia, Sungkyul University, Anyang-si, South Korea

    Seungmin Rho

  3. Department of Electrical Engineering, Feng Chia University, Taichung, Taiwan

    K. Bharnitharan

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  1. Anand Paul
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  2. Seungmin Rho
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  3. K. Bharnitharan
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Correspondence to Seungmin Rho.

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Paul, A., Rho, S. & Bharnitharan, K. Interactive scheduling for mobile multimedia service in M2M environment. Multimed Tools Appl 71, 235–246 (2014). https://doi.org/10.1007/s11042-013-1490-0

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