RT Conference Proceedings
T1 Using energy consumption for self-adaptation in FaaS.
A1 Serrano Gutiérrez, Pablo
A1 Ayala-Viñas, Inmaculada
K1 Internet de los objetos
AB One of the programming models that has been developingthe most in recent years is Function as a Service (FaaS). The growing concernover data centre energy footprints has driven sustainable softwaredevelopment. In serverless applications, energy consumption depends onthe energy consumption of the application’s functions. However, measuringenergy proves challenging, and the results’ variability complicatesoptimisation efforts at runtime. This article addresses this issue by measuringserverless function energy consumption and exploring integrationinto an optimisation system that selects implementations based on theircurrent energy footprint. For this, we have integrated an energy measurementsoftware into a FaaS system. We have analysed how to properlyprocess the data and how to use them to perform self-adaptation.We present a series of methods and policies that make our system notonly capable of detecting variations in the energy consumption of thefunctions, but it does so taking into account the variability in the measurementsthat each function may present. Our experiments showcaseproper integration in a self-adaptive system, showing a reduction up to5% in energy consumption due to functions in a test application.
PB Springer Nature
YR 2024
FD 2024
LK https://hdl.handle.net/10630/31964
UL https://hdl.handle.net/10630/31964
LA eng
NO https://link.springer.com/book/9783031664588
NO Política de acceso abierto tomada de: https://www.springernature.com/gp/open-research/policies/book-policies
NO Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 2 mar 2026