<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-06-01T14:49:29Z</responseDate><request verb="GetRecord" identifier="oai:riuma.uma.es:10630/31964" metadataPrefix="marc">https://riuma.uma.es/rest/oai/request</request><GetRecord><record><header><identifier>oai:riuma.uma.es:10630/31964</identifier><datestamp>2026-02-03T12:23:11Z</datestamp><setSpec>com_10630_2254</setSpec><setSpec>col_10630_37959</setSpec></header><metadata><record xmlns="http://www.loc.gov/MARC21/slim" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:doc="http://www.lyncode.com/xoai" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.loc.gov/MARC21/slim http://www.loc.gov/standards/marcxml/schema/MARC21slim.xsd">
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   <datafield ind2=" " ind1=" " tag="720">
      <subfield code="a">Serrano Gutiérrez, Pablo</subfield>
      <subfield code="e">author</subfield>
   </datafield>
   <datafield ind2=" " ind1=" " tag="720">
      <subfield code="a">Ayala-Viñas, Inmaculada</subfield>
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      <subfield code="c">2024</subfield>
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      <subfield code="a">One of the programming models that has been developing&#xd;
the most in recent years is Function as a Service (FaaS). The growing concern&#xd;
over data centre energy footprints has driven sustainable software&#xd;
development. In serverless applications, energy consumption depends on&#xd;
the energy consumption of the application’s functions. However, measuring&#xd;
energy proves challenging, and the results’ variability complicates&#xd;
optimisation efforts at runtime. This article addresses this issue by measuring&#xd;
serverless function energy consumption and exploring integration&#xd;
into an optimisation system that selects implementations based on their&#xd;
current energy footprint. For this, we have integrated an energy measurement&#xd;
software into a FaaS system. We have analysed how to properly&#xd;
process the data and how to use them to perform self-adaptation.&#xd;
We present a series of methods and policies that make our system not&#xd;
only capable of detecting variations in the energy consumption of the&#xd;
functions, but it does so taking into account the variability in the measurements&#xd;
that each function may present. Our experiments showcase&#xd;
proper integration in a self-adaptive system, showing a reduction up to&#xd;
5% in energy consumption due to functions in a test application.</subfield>
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      <subfield code="a">https://link.springer.com/book/9783031664588</subfield>
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      <subfield code="a">https://hdl.handle.net/10630/31964</subfield>
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      <subfield code="a">Internet de los objetos</subfield>
   </datafield>
   <datafield ind2="0" ind1="0" tag="245">
      <subfield code="a">Using energy consumption for self-adaptation in FaaS.</subfield>
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