A Fuzzy Rule-Based System to Predict Energy Consumption of Genetic Programming Algorithms

Josefa Díaz Álvarez1, Franciso Chávez de la O1, Pedro A. Castillo2, Juan Angel García1, Francisco J. Rodriguez3 and Francisco Fernández de Vega1

  1. Mérida Campus, University of Extremadura
    Mérida, Spain
    {mjdiaz, fchavez, juangm, fcofdez}@unex.es
  2. Computer Architecture and Technology Department. University of Granada
    Spain
    pacv@ugr.es
  3. Computer Science Department. University of Burgos
    Spain
    fjrdiaz@ubu.es

Abstract

In recent years, the energy-awareness has become one of the most interesting areas in our environmentally conscious society. Algorithm designers have been part of this, particularly when dealing with networked devices and, mainly, when handheld ones are involved. Although studies in this area has increased, not many of them have focused on Evolutionary Algorithms. To the best of our knowledge, few attempts have been performed before for modeling their energy consumption considering different execution devices. In this work, we propose a fuzzy rulebased system to predict energy comsumption of a kind of Evolutionary Algorithm, Genetic Prohramming, given the device in wich it will be executed, its main parameters, and a measurement of the difficulty of the problem addressed. Experimental results performed show that the proposed model can predict energy consumption with very low error values.

Key words

Green computing, energy-aware computing, performance measurements, evolutionary algorithms

Digital Object Identifier (DOI)

https://doi.org/10.2298/CSIS180110026A

Publication information

Volume 15, Issue 3 (October 2018)
Year of Publication: 2018
ISSN: 2406-1018 (Online)
Publisher: ComSIS Consortium

Full text

DownloadAvailable in PDF
Portable Document Format

How to cite

Álvarez, J. D., O, F. C. d. l., Castillo, P. A., García, J. A., Rodriguez, F. J., Vega, F. F. d.: A Fuzzy Rule-Based System to Predict Energy Consumption of Genetic Programming Algorithms. Computer Science and Information Systems, Vol. 15, No. 3, 635–654. (2018), https://doi.org/10.2298/CSIS180110026A