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    宫晓利, 于海洋, 孙承君, 李涛, 张金, 马捷. XOS:面向用户体验质量的高能效异构多核调度算法[J]. 计算机研究与发展, 2016, 53(7): 1467-1477. DOI: 10.7544/issn1000-1239.2016.20160113
    引用本文: 宫晓利, 于海洋, 孙承君, 李涛, 张金, 马捷. XOS:面向用户体验质量的高能效异构多核调度算法[J]. 计算机研究与发展, 2016, 53(7): 1467-1477. DOI: 10.7544/issn1000-1239.2016.20160113
    Gong Xiaoli, Yu Haiyang, Sun Chengjun, Li Tao, Zhang Jin, Ma Jie. XOS: A QoE Oriented Energy Efficient Heterogeneous Multi-Processor Schedule Mechanism[J]. Journal of Computer Research and Development, 2016, 53(7): 1467-1477. DOI: 10.7544/issn1000-1239.2016.20160113
    Citation: Gong Xiaoli, Yu Haiyang, Sun Chengjun, Li Tao, Zhang Jin, Ma Jie. XOS: A QoE Oriented Energy Efficient Heterogeneous Multi-Processor Schedule Mechanism[J]. Journal of Computer Research and Development, 2016, 53(7): 1467-1477. DOI: 10.7544/issn1000-1239.2016.20160113

    XOS:面向用户体验质量的高能效异构多核调度算法

    XOS: A QoE Oriented Energy Efficient Heterogeneous Multi-Processor Schedule Mechanism

    • 摘要: 智能移动设备的重要作用日益凸显,然而,对于性能的追求与有限电池容量的矛盾制约了产业的发展.异构多核处理器架构以其平衡性能与能耗的优势,成为一种新型的解决方案.用户体验优化是智能移动设备的重要设计目标.借助一个分段式的用户体验模型,提出了面向异构多核设备的XOS(experience oriented scheduler)调度算法.XOS能够跨层获取任务信息,识别与用户直接交互的任务组,保证这些任务的计算资源分配以保障用户体验,同时限制非交互性任务的计算资源以降低能耗.通过建立一套仿真系统验证了算法的有效性并进行了调整优化,然后在Odroid-XU3开发板Android系统中进行了原型实现和验证.实验结果表明:XOS算法对于不同类型的任务仅产生了2.7%~7.3%的用户体验下降,但节省了8%~48%的能量.

       

      Abstract: Smart mobile devices are playing a more and more important part in people’s daily life. However, the pursuit of increasing performance of mobile devices directly conflicts with the limited battery capacity. The inevitable contradiction between them begins to block the development of smart mobile devices. To overcome this limitation, the heterogeneous multi-processor architecture can balance the user experience and the energy consumption on smart mobile devices, which makes it become a new solution. Based on a compartmental QoE model, a schedule mechanism called XOS oriented heterogeneous multi-processor devices is presented to provide a high energy efficient solution. In XOS, the user interaction tasks are recognized by the operating system based on the cross-layer information, and more computing resources are allocated to these tasks to guarantee the quality of experience, while resources would be limited for other tasks to reduce energy consumption. A simulation system is built to verify the effectiveness of the XOS model and then make a reasonable optimization. Then the implementation and the experiment of the XOS are conducted on Odroid-XU3 board with Android operation system. The result shows that the tasks scheduled by XOS decelerate lessens 2.7%~7.3% QoE lost, whereas they reduce 8%~48% energy consumption at the same time.

       

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