System Message Based Predict Policy for Dynamic Power Management
Xi-Qiang Ma, Fang Yang, Ji-Shun Li, Yu-Jun Xue
Available Online December 2016.
- https://doi.org/10.2991/icwcsn-16.2017.117How to use a DOI?
- DPM; equipment utilization rate; predict policy
- According to the traditional dynamic power management random policy can't also pointed out that moment of decision and state transition, dynamic power management improvement algorithm, SMBPP(System message based predict policy) is presented in this paper. Firstly, the existing dynamic power management policy algorithm which neglects the application characteristics of the workload is introduced. Secondly, based on the information of the system, the equipment utilization rate of the task is established, and the distribution is updated according to the actual interval time. Thirdly, the predict policy based on task equipment utilization is proposed, and the influence of the strategy parameters on the system sensitivity is analyzed.. Finally, the algorithm is used in wind power bearing state monitoring device. Experimental results show that with the performance constrain, the algorithm pointed out moment of decision and state transition, more stable and more effectively reduces the power consumption.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Xi-Qiang Ma AU - Fang Yang AU - Ji-Shun Li AU - Yu-Jun Xue PY - 2016/12 DA - 2016/12 TI - System Message Based Predict Policy for Dynamic Power Management BT - 3rd International Conference on Wireless Communication and Sensor Networks (WCSN 2016) PB - Atlantis Press SN - 2352-538X UR - https://doi.org/10.2991/icwcsn-16.2017.117 DO - https://doi.org/10.2991/icwcsn-16.2017.117 ID - Ma2016/12 ER -