<div class="csl-bib-body">
<div class="csl-entry">Herrera, J. L., Sedlak, B., & Dustdar, S. (2026). Active Inference for Sustainable Computing Continuum Systems. <i>IEEE Internet Computing</i>, <i>30</i>(1), 81–90. https://doi.org/10.1109/MIC.2025.3590621</div>
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dc.identifier.issn
1089-7801
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/227615
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dc.description.abstract
The computing continuum (CC) is expected to improve the quality of service of distributed applications. However, adding more devices to current cloud datacenters to implement the CC can increase the energy-related CO2 emissions of the paradigm. Sustainability requires intelligently managing applications through the CC, considering both the energy consumption and carbon intensity of energy sources. Moreover, the CC provider should perform this management, given their control of devices and networks. This work provides an overview on achieving sustainability in the CC and the associated challenges, proposing an architecture that leverages active inference to learn, manage, and reconfigure the system to achieve a low carbon footprint while meeting the service level objectives of applications.
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dc.description.sponsorship
European Commission
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dc.language.iso
en
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dc.publisher
IEEE COMPUTER SOC
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dc.relation.ispartof
IEEE Internet Computing
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dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
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dc.subject
Active Inference
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dc.subject
Sustainability
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dc.subject
Computing Continuum
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dc.title
Active Inference for Sustainable Computing Continuum Systems