RT conference output
T1 Automatic Generation of Greener Software Program Versions with Genetic Algorithms
A1 Aragón Jurado, José Miguel
A1 Torre Macías, Juan Carlos de la
A1 Ruiz Villalobos, Patricia
A1 Dorronsoro Díaz, Bernabé
A2 Ingeniería Informática
AB There is a plethora of different computing hardware (HW) architectures nowadays, many of themimplementing energy efficient designs, as it is the case of mobile computing devices, smartphones,or Internet of Things (IoT) devices. However, software (SW) is who ultimately drives the behaviorof HW, and it should be specifically designed for the architecture it will be executed in, in ordermake an appropriate use of available resources for optimal energy efficiency. Unfortunately, thisis a complex task, requiring expert hands with deep knowledge on the specific HW architecture.Therefore, there is a clear need of tools that can automatically modify SW code to generate anequivalent program version to improve energy efficiency of the device when executing it, what wecall a greener version of the program.There is a gap in the literature regarding the development of generic tools for SW energyconsumption optimization [7, 8]. Some works focus on time optimization [3], while others make useof consumption estimations [6, 11] and/or modify the semantics [5], limiting their applicability.This extended abstract presents our work [4] recently published in Internet of Things journal,where a novel combinatorial optimization problem, called the Green Software Code OptimizationProblem (gSCOP), is presented for automatically optimizing SW into greener versions usingmetaheuristics. The methodology makes use of a custom current meter that is perfectly synchronizedwith the experiments, making it possible to get accurate measurements, as well as to allowsystematic experimentations.
YR 2025
FD 2025-04
LK http://hdl.handle.net/10498/36460
UL http://hdl.handle.net/10498/36460
LA eng
DS Repositorio Institucional de la Universidad de Cádiz
RD 11-nov-2026