Paper Info
Title
Constructing an Accurate and a High-Performance Power Profiler for Embedded Systems and Smartphones.
Abstract
The main objective of this paper is to present a new accurate power profiler for embedded systems and smartphones. The second objective is, for it, to be a tutorial explaining the main steps to build power profilers for embedded and mobile systems, in general. We start our work by firstly describing the general methodology of building a power profiler. Then, we showcase how each step is undertaken to build a profiler with two power models. The first one was an artificial neural network (called N2) that presented a lot of noise in its estimation. After debugging and improvement, the second model, a NARX neural network (we call N3) was built. It eliminated all the drawback of the first model and had a mean absolute percentage error of 2.8%.
Year
DOI
Venue
2018
10.1145/3242102.3242139
MSWIM '18: 21st ACM Int'l Conference on Modelling, Analysis and Simulation of Wireless and Mobile Systems Montreal QC Canada October, 2018
Field
DocType
ISBN
Drawback,Mean absolute percentage error,Nonlinear autoregressive exogenous model,Curve fitting,Computer science,Artificial neural network,Power consumption,Embedded system,Debugging
Conference
978-1-4503-5960-3
Citations 
PageRank 
References 
0
0.34
10
Authors
4
Name
Order
Citations
PageRank
Oussama Djedidi100.34
m a djeziri211.04
Nacer Kouider M'sirdi35211.59
Aziz Naamane462.73