Proceedings of the 3rd International Conference on Wireless Communication and Sensor Networks (WCSN 2016)

System Message Based Predict Policy for Dynamic Power Management

Authors
Xi-Qiang Ma, Fang Yang, Ji-Shun Li, Yu-Jun Xue
Corresponding Author
Xi-Qiang Ma
Available Online December 2016.
DOI
https://doi.org/10.2991/icwcsn-16.2017.117How to use a DOI?
Keywords
DPM; equipment utilization rate; predict policy
Abstract
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.
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Proceedings
3rd International Conference on Wireless Communication and Sensor Networks (WCSN 2016)
Part of series
Advances in Computer Science Research
Publication Date
December 2016
ISBN
978-94-6252-302-9
ISSN
2352-538X
DOI
https://doi.org/10.2991/icwcsn-16.2017.117How to use a DOI?
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  -