Paper Info
Title
An online optimization for dynamic power management
Abstract
In this paper, we combine a spherical coordinate method and a gradient learning optimization algorithm to solve the dynamic power management (DPM) problem. In our approach, the DPM is modeled as a constrained SMDP problem with unknown model parameters. By utilizing an augmented Lagrange multiplier method, we provide an online optimization method for the DPM. This method may estimate the gradient of the augmented Lagrange function with respect to the policy parameters and optimize the performance in an online way. The simulation tests show that the method has better convergence property and higher efficiency. © 2016 IEEE.
Year
DOI
Venue
2016
10.1109/ICIT.2016.7474988
Proceedings of the IEEE International Conference on Industrial Technology
Keywords
Field
DocType
Lagrange multiplier method, spherical coordinates, power management, single-sample-path based gradient estimation
Convergence (routing),Mathematical optimization,Algorithm design,Control theory,Computer science,Constraint algorithm,Stochastic process,Augmented Lagrangian method,Online optimization,Exponential distribution,Spherical coordinate system
Conference
Volume
Citations 
PageRank 
2016-May
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Zhai Jianfeng110.72
Yanjie Li2418.99
Haoyao Chen318923.79