<div class="csl-bib-body">
<div class="csl-entry">Sedlak, B., Casamayor Pujol, V., Morichetta, A., Donta, P. K., & Dustdar, S. (2025). Adaptive stream processing on edge devices through active inference. <i>Evolving Systems</i>, <i>16</i>(4), Article 130. https://doi.org/10.1007/s12530-025-09753-2</div>
</div>
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dc.identifier.issn
1868-6478
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/221010
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dc.description.abstract
The current scenario of IoT is witnessing a constant increase on the volume of data, which is generated in constant stream, calling for novel architectural and logical solutions for processing it. Moving the data handling towards the edge of the computing spectrum guarantees better distribution of load and, in principle, lower latency and better privacy. However, managing such a structure is complex, especially when requirements, also referred to Service Level Objectives (SLOs), specified by applications’ owners and infrastructure managers need to be ensured. Despite the rich number of proposals of Machine Learning (ML) based management solutions, researchers and practitioners yet struggle to guarantee long-term prediction and control, and accurate troubleshooting. Therefore, we present a novel ML paradigm based on Active Inference (AIF)—a concept from neuroscience that describes how the brain constantly predicts and evaluates sensory information to decrease long-term surprise. We implement it and evaluate it in a heterogeneous real stream processing use case, where an AIF-based agent continuously optimizes the fulfillment of three SLOs for three autonomous driving services running on multiple devices. The agent used causal knowledge to gradually develop an understanding of how its actions are related to requirements fulfillment, and which configurations to favor. Through this approach, our agent requires up to thirty iterations to converge to the optimal solution, showing the capability of offering accurate results in a short amount of time. Furthermore, thanks to AIF and its causal structures, our method guarantees full transparency on the decision making, making the interpretation of the results and the troubleshooting effortless.
en
dc.description.sponsorship
European Commission
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dc.description.sponsorship
European Commission
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dc.language.iso
en
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dc.publisher
SPRINGER HEIDELBERG
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dc.relation.ispartof
Evolving Systems
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dc.subject
Active Inference
en
dc.subject
Machine learning
en
dc.subject
Edge intelligence
en
dc.subject
Service Level Objectives
en
dc.subject
Markov blanket
en
dc.title
Adaptive stream processing on edge devices through active inference
en
dc.type
Article
en
dc.type
Artikel
de
dc.contributor.affiliation
Universitat Pompeu Fabra, Spain
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dc.contributor.affiliation
Stockholm University, Sweden
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dc.relation.grantno
101135576
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dc.relation.grantno
101070186
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dc.type.category
Original Research Article
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tuw.container.volume
16
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tuw.container.issue
4
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tuw.journal.peerreviewed
true
-
tuw.peerreviewed
true
-
wb.publication.intCoWork
International Co-publication
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tuw.project.title
Intent-based data operation in the computing continuum
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tuw.project.title
Trustworthy, Energy-Aware federated DAta Lakes along the Computing Continuum
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tuw.researchTopic.id
I4
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tuw.researchTopic.name
Information Systems Engineering
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tuw.researchTopic.value
100
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dcterms.isPartOf.title
Evolving Systems
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tuw.publication.orgunit
E194-02 - Forschungsbereich Distributed Systems
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tuw.publisher.doi
10.1007/s12530-025-09753-2
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dc.date.onlinefirst
2025-11-11
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dc.identifier.articleid
130
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dc.identifier.eissn
1868-6486
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dc.description.numberOfPages
16
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tuw.author.orcid
0009-0001-2365-8265
-
tuw.author.orcid
0000-0003-2830-8368
-
tuw.author.orcid
0000-0003-3765-3067
-
tuw.author.orcid
0000-0002-8233-6071
-
tuw.author.orcid
0000-0001-6872-8821
-
wb.sci
true
-
wb.sciencebranch
Informatik
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wb.sciencebranch.oefos
1020
-
wb.sciencebranch.value
100
-
item.openairecristype
http://purl.org/coar/resource_type/c_2df8fbb1
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item.cerifentitytype
Publications
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item.openairetype
research article
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item.fulltext
no Fulltext
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item.languageiso639-1
en
-
item.grantfulltext
restricted
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crisitem.author.dept
E194-02 - Forschungsbereich Distributed Systems
-
crisitem.author.dept
Universitat Pompeu Fabra
-
crisitem.author.dept
E194-02 - Forschungsbereich Distributed Systems
-
crisitem.author.dept
E194-02 - Forschungsbereich Distributed Systems
-
crisitem.author.dept
E194-02 - Forschungsbereich Distributed Systems
-
crisitem.author.orcid
0009-0001-2365-8265
-
crisitem.author.orcid
0000-0003-3765-3067
-
crisitem.author.orcid
0000-0002-8233-6071
-
crisitem.author.orcid
0000-0001-6872-8821
-
crisitem.author.parentorg
E194 - Institut für Information Systems Engineering
-
crisitem.author.parentorg
E194 - Institut für Information Systems Engineering
-
crisitem.author.parentorg
E194 - Institut für Information Systems Engineering
-
crisitem.author.parentorg
E194 - Institut für Information Systems Engineering