动态电源管理的在线优化技术

Online optimization of dynamic power management

中文关键词  动态电源管理  智能节能  半Markov决策过程  在线优化

英文关键词  dynamic power management  intelligent energy saving  semi-Markov decision process  online optimization

中文摘要

      研究离散事件动态系统中的一类随机离散动态系统—–半Markov决策过程, 在动态电源管理问题中的应用. 动态电源管理问题存在于很多便携式电子设备中, 其主要目的是根据电子设备的状态通过电源管理策略选择关闭 或休眠一些元器件, 从而实现节省电子设备功耗, 延长电池使用时间的目的. 首先讨论了动态电源管理问题的建模, 给出了一种带有禁止时间的在线优化方法, 该方法通过设备自身运行数据, 自主地学习并改进电源的动态管理策 略, 从而使每台电子设备具有个性化的动态电源管理方式, 其优化过程可以在设备充电时完成, 不需要通过云传输 和云计算, 避免了隐私数据的泄漏. 最后通过仿真实验验证了算法的有效性.

英文摘要

      This paper mainly considers the application of Semi-Markov decision process (SMDP), which is a stochastic discrete event dynamic system (DEDS), in the dynamic power management (DPM) problems. There are the DPM problems in many portable devices, which can provide satisfactory performance with minimum power consumption by selectively turning off system components, which enter the idle state, to save the energy consumption and prolong the service time. Firstly, the SMDP model of DPM is introduced and then an online optimization approach with forbidden time is presented. This approach can learn to improve the policy of DPM by analyzing the data from the device itself and make the device have an individual power management policy. The optimization can be implemented during the charging and thus does not need the cloud transportation and computation, which avoids the leak of private data. Finally, a simulation example is applied to illustrate the applicability of the approach.