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Unified energy aware mapping of multimedia applications on media cloud infrastructure

机译:媒体云基础架构上多媒体应用程序的统一能源感知映射

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Media clouds provide an infrastructure for distributed processing and storage of multimedia applications. Each device in the media cloud is usually a mobile system consisting of several heterogeneous Processing Elements (PE). Energy efficiency has always been a challenge in this environment. In this paper, we propose a unified energy efficient algorithm for mapping multimedia applications on a media cloud infrastructure. The algorithm considers the distribution of tasks at two levels: among devices in the cloud and PEs of each device. The proposed algorithm heuristically finds the most energy efficient device for each task at the first stage. In the second stage, the least energy consuming PE among all available PEs is chosen for mapping. The efficiency of the proposed scheme has been evaluated by mapping H.264/AVC decoder on a media cloud. Simulation results indicate that by offloading application tasks on more power efficient PEs, the overall energy consumption for this application would be reduced by up to 12 times in a typical scenario in comparison to local processing. Meanwhile, the performance of the heuristic has been compared to the optimal solution.
机译:媒体云为多媒体应用程序的分布式处理和存储提供了基础架构。媒体云中的每个设备通常是由几个异构处理元素(PE)组成的移动系统。在这种环境下,能源效率一直是一个挑战。在本文中,我们提出了一种用于在媒体云基础架构上映射多媒体应用程序的统一节能算法。该算法在两个级别上考虑任务的分布:云中的设备之间以及每个设备的PE。所提出的算法在第一阶段试探性地为每个任务找到最节能的设备。在第二阶段,选择所有可用PE中能耗最低的PE进行映射。已通过在媒体云上映射H.264 / AVC解码器来评估所提出方案的效率。仿真结果表明,通过在更高能效的PE上分担应用程序任务,与本地处理相比,在典型情况下,此应用程序的总能耗将减少多达12倍。同时,将启发式算法的性能与最佳解决方案进行了比较。

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