A Quality-driven Machine Learning Governance Architecture for Self-adaptive Edge Clouds Article Swipe
Claus Pahl
,
Shelernaz Azimi
,
Hamid R. Barzegar
,
Nabil El Ioini
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.5220/0011107000003200
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.5220/0011107000003200
Self-adaptive systems such as clouds and edge clouds are more and more using Machine Learning (ML) techniques if sufficient data is available to create respective ML models. Self-adaptive systems are built around a controller that, based on monitored system data as input, generate actions to maintain the system in question within expected quality ranges. Machine learning (ML) can help to create controllers for self-adaptive systems such as edge clouds. However, because ML-created controllers are created without a direct full control by expert software developers, quality needs to be specifically looked at, requiring a better understanding of the ML models. Here, we explore a quality-oriented management and governance architecture for self-adaptive edge controllers. The concrete objective here is the validation of a reference governance architecture for edge cloud systems that facilitates ML controller quality management in a feedback loop.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.5220/0011107000003200
- OA Status
- gold
- Cited By
- 7
- References
- 33
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4285309914
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4285309914Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.5220/0011107000003200Digital Object Identifier
- Title
-
A Quality-driven Machine Learning Governance Architecture for Self-adaptive Edge CloudsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-01-01Full publication date if available
- Authors
-
Claus Pahl, Shelernaz Azimi, Hamid R. Barzegar, Nabil El IoiniList of authors in order
- Landing page
-
https://doi.org/10.5220/0011107000003200Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.5220/0011107000003200Direct OA link when available
- Concepts
-
Computer science, Architecture, Enhanced Data Rates for GSM Evolution, Quality (philosophy), Computer architecture, Artificial intelligence, Epistemology, Art, Philosophy, Visual artsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
7Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 3, 2023: 1, 2022: 3Per-year citation counts (last 5 years)
- References (count)
-
33Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4285309914 |
|---|---|
| doi | https://doi.org/10.5220/0011107000003200 |
| ids.doi | https://doi.org/10.5220/0011107000003200 |
| ids.openalex | https://openalex.org/W4285309914 |
| fwci | 2.01797279 |
| type | article |
| title | A Quality-driven Machine Learning Governance Architecture for Self-adaptive Edge Clouds |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | 312 |
| biblio.first_page | 305 |
| topics[0].id | https://openalex.org/T11891 |
| topics[0].field.id | https://openalex.org/fields/14 |
| topics[0].field.display_name | Business, Management and Accounting |
| topics[0].score | 0.9835000038146973 |
| topics[0].domain.id | https://openalex.org/domains/2 |
| topics[0].domain.display_name | Social Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1404 |
| topics[0].subfield.display_name | Management Information Systems |
| topics[0].display_name | Big Data and Business Intelligence |
| topics[1].id | https://openalex.org/T10101 |
| topics[1].field.id | https://openalex.org/fields/17 |
| topics[1].field.display_name | Computer Science |
| topics[1].score | 0.9775999784469604 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1710 |
| topics[1].subfield.display_name | Information Systems |
| topics[1].display_name | Cloud Computing and Resource Management |
| topics[2].id | https://openalex.org/T10273 |
| topics[2].field.id | https://openalex.org/fields/17 |
| topics[2].field.display_name | Computer Science |
| topics[2].score | 0.9365000128746033 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1705 |
| topics[2].subfield.display_name | Computer Networks and Communications |
| topics[2].display_name | IoT and Edge/Fog Computing |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C41008148 |
| concepts[0].level | 0 |
| concepts[0].score | 0.701134443283081 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[0].display_name | Computer science |
| concepts[1].id | https://openalex.org/C123657996 |
| concepts[1].level | 2 |
| concepts[1].score | 0.5996305346488953 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q12271 |
| concepts[1].display_name | Architecture |
| concepts[2].id | https://openalex.org/C162307627 |
| concepts[2].level | 2 |
| concepts[2].score | 0.5430828928947449 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q204833 |
| concepts[2].display_name | Enhanced Data Rates for GSM Evolution |
| concepts[3].id | https://openalex.org/C2779530757 |
| concepts[3].level | 2 |
| concepts[3].score | 0.5022268295288086 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q1207505 |
| concepts[3].display_name | Quality (philosophy) |
| concepts[4].id | https://openalex.org/C118524514 |
| concepts[4].level | 1 |
| concepts[4].score | 0.3921165466308594 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q173212 |
| concepts[4].display_name | Computer architecture |
| concepts[5].id | https://openalex.org/C154945302 |
| concepts[5].level | 1 |
| concepts[5].score | 0.36016571521759033 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[5].display_name | Artificial intelligence |
| concepts[6].id | https://openalex.org/C111472728 |
| concepts[6].level | 1 |
| concepts[6].score | 0.0 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q9471 |
| concepts[6].display_name | Epistemology |
| concepts[7].id | https://openalex.org/C142362112 |
| concepts[7].level | 0 |
| concepts[7].score | 0.0 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q735 |
| concepts[7].display_name | Art |
| concepts[8].id | https://openalex.org/C138885662 |
| concepts[8].level | 0 |
| concepts[8].score | 0.0 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q5891 |
| concepts[8].display_name | Philosophy |
| concepts[9].id | https://openalex.org/C153349607 |
| concepts[9].level | 1 |
| concepts[9].score | 0.0 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q36649 |
| concepts[9].display_name | Visual arts |
| keywords[0].id | https://openalex.org/keywords/computer-science |
| keywords[0].score | 0.701134443283081 |
| keywords[0].display_name | Computer science |
| keywords[1].id | https://openalex.org/keywords/architecture |
| keywords[1].score | 0.5996305346488953 |
| keywords[1].display_name | Architecture |
| keywords[2].id | https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution |
| keywords[2].score | 0.5430828928947449 |
| keywords[2].display_name | Enhanced Data Rates for GSM Evolution |
| keywords[3].id | https://openalex.org/keywords/quality |
| keywords[3].score | 0.5022268295288086 |
| keywords[3].display_name | Quality (philosophy) |
| keywords[4].id | https://openalex.org/keywords/computer-architecture |
| keywords[4].score | 0.3921165466308594 |
| keywords[4].display_name | Computer architecture |
| keywords[5].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[5].score | 0.36016571521759033 |
| keywords[5].display_name | Artificial intelligence |
| language | en |
| locations[0].id | doi:10.5220/0011107000003200 |
| locations[0].is_oa | True |
| locations[0].source | |
| locations[0].license | cc-by-nc-nd |
| locations[0].pdf_url | |
| locations[0].version | publishedVersion |
| locations[0].raw_type | proceedings-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by-nc-nd |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Proceedings of the 12th International Conference on Cloud Computing and Services Science |
| locations[0].landing_page_url | https://doi.org/10.5220/0011107000003200 |
| locations[1].id | pmh:oai:unibz.it:11316896790001241 |
| locations[1].is_oa | True |
| locations[1].source | |
| locations[1].license | cc-by-nc-nd |
| locations[1].pdf_url | |
| locations[1].version | submittedVersion |
| locations[1].raw_type | text |
| locations[1].license_id | https://openalex.org/licenses/cc-by-nc-nd |
| locations[1].is_accepted | False |
| locations[1].is_published | False |
| locations[1].raw_source_name | |
| locations[1].landing_page_url | https://bia.unibz.it/esploro/outputs/conferenceProceeding/A-Quality-driven-Machine-Learning-Governance-Architecture/991006785591701241 |
| indexed_in | crossref |
| authorships[0].author.id | https://openalex.org/A5003596976 |
| authorships[0].author.orcid | https://orcid.org/0000-0002-9049-212X |
| authorships[0].author.display_name | Claus Pahl |
| authorships[0].countries | IT |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I171543936 |
| authorships[0].affiliations[0].raw_affiliation_string | Free University of Bozen-Bolzano, Bolzano, Italy, --- Select a Country --- |
| authorships[0].institutions[0].id | https://openalex.org/I171543936 |
| authorships[0].institutions[0].ror | https://ror.org/012ajp527 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I171543936 |
| authorships[0].institutions[0].country_code | IT |
| authorships[0].institutions[0].display_name | Free University of Bozen-Bolzano |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Claus Pahl |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Free University of Bozen-Bolzano, Bolzano, Italy, --- Select a Country --- |
| authorships[1].author.id | https://openalex.org/A5083811163 |
| authorships[1].author.orcid | |
| authorships[1].author.display_name | Shelernaz Azimi |
| authorships[1].countries | IT |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I171543936 |
| authorships[1].affiliations[0].raw_affiliation_string | Free University of Bozen-Bolzano, Bolzano, Italy, --- Select a Country --- |
| authorships[1].institutions[0].id | https://openalex.org/I171543936 |
| authorships[1].institutions[0].ror | https://ror.org/012ajp527 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I171543936 |
| authorships[1].institutions[0].country_code | IT |
| authorships[1].institutions[0].display_name | Free University of Bozen-Bolzano |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Shelernaz Azimi |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Free University of Bozen-Bolzano, Bolzano, Italy, --- Select a Country --- |
| authorships[2].author.id | https://openalex.org/A5032833756 |
| authorships[2].author.orcid | https://orcid.org/0000-0003-2784-3537 |
| authorships[2].author.display_name | Hamid R. Barzegar |
| authorships[2].countries | IT |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I171543936 |
| authorships[2].affiliations[0].raw_affiliation_string | Free University of Bozen-Bolzano, Bolzano, Italy, --- Select a Country --- |
| authorships[2].institutions[0].id | https://openalex.org/I171543936 |
| authorships[2].institutions[0].ror | https://ror.org/012ajp527 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I171543936 |
| authorships[2].institutions[0].country_code | IT |
| authorships[2].institutions[0].display_name | Free University of Bozen-Bolzano |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Hamid Barzegar |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Free University of Bozen-Bolzano, Bolzano, Italy, --- Select a Country --- |
| authorships[3].author.id | https://openalex.org/A5024294410 |
| authorships[3].author.orcid | https://orcid.org/0000-0002-1288-1082 |
| authorships[3].author.display_name | Nabil El Ioini |
| authorships[3].countries | IT |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I171543936 |
| authorships[3].affiliations[0].raw_affiliation_string | Free University of Bozen-Bolzano, Bolzano, Italy, --- Select a Country --- |
| authorships[3].institutions[0].id | https://openalex.org/I171543936 |
| authorships[3].institutions[0].ror | https://ror.org/012ajp527 |
| authorships[3].institutions[0].type | education |
| authorships[3].institutions[0].lineage | https://openalex.org/I171543936 |
| authorships[3].institutions[0].country_code | IT |
| authorships[3].institutions[0].display_name | Free University of Bozen-Bolzano |
| authorships[3].author_position | last |
| authorships[3].raw_author_name | Nabil El Ioini |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Free University of Bozen-Bolzano, Bolzano, Italy, --- Select a Country --- |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://doi.org/10.5220/0011107000003200 |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | A Quality-driven Machine Learning Governance Architecture for Self-adaptive Edge Clouds |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T11891 |
| primary_topic.field.id | https://openalex.org/fields/14 |
| primary_topic.field.display_name | Business, Management and Accounting |
| primary_topic.score | 0.9835000038146973 |
| primary_topic.domain.id | https://openalex.org/domains/2 |
| primary_topic.domain.display_name | Social Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1404 |
| primary_topic.subfield.display_name | Management Information Systems |
| primary_topic.display_name | Big Data and Business Intelligence |
| related_works | https://openalex.org/W2588198209, https://openalex.org/W1909006023, https://openalex.org/W4205824991, https://openalex.org/W3200723557, https://openalex.org/W4312713546, https://openalex.org/W2362195430, https://openalex.org/W2347494122, https://openalex.org/W2567983276, https://openalex.org/W2802298219, https://openalex.org/W2038503502 |
| cited_by_count | 7 |
| counts_by_year[0].year | 2024 |
| counts_by_year[0].cited_by_count | 3 |
| counts_by_year[1].year | 2023 |
| counts_by_year[1].cited_by_count | 1 |
| counts_by_year[2].year | 2022 |
| counts_by_year[2].cited_by_count | 3 |
| locations_count | 2 |
| best_oa_location.id | doi:10.5220/0011107000003200 |
| best_oa_location.is_oa | True |
| best_oa_location.source | |
| best_oa_location.license | cc-by-nc-nd |
| best_oa_location.pdf_url | |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | proceedings-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by-nc-nd |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Proceedings of the 12th International Conference on Cloud Computing and Services Science |
| best_oa_location.landing_page_url | https://doi.org/10.5220/0011107000003200 |
| primary_location.id | doi:10.5220/0011107000003200 |
| primary_location.is_oa | True |
| primary_location.source | |
| primary_location.license | cc-by-nc-nd |
| primary_location.pdf_url | |
| primary_location.version | publishedVersion |
| primary_location.raw_type | proceedings-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by-nc-nd |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Proceedings of the 12th International Conference on Cloud Computing and Services Science |
| primary_location.landing_page_url | https://doi.org/10.5220/0011107000003200 |
| publication_date | 2022-01-01 |
| publication_year | 2022 |
| referenced_works | https://openalex.org/W1949046322, https://openalex.org/W3045802826, https://openalex.org/W2967037938, https://openalex.org/W2887389695, https://openalex.org/W3045785412, https://openalex.org/W2991413563, https://openalex.org/W2951760215, https://openalex.org/W2944264045, https://openalex.org/W3197222028, https://openalex.org/W2090572500, https://openalex.org/W2514218946, https://openalex.org/W3115549779, https://openalex.org/W3125976728, https://openalex.org/W2968778390, https://openalex.org/W3139521209, https://openalex.org/W2277678732, https://openalex.org/W2620387295, https://openalex.org/W3139060629, https://openalex.org/W2793142602, https://openalex.org/W3137689784, https://openalex.org/W2990874346, https://openalex.org/W2909966399, https://openalex.org/W3027751536, https://openalex.org/W2945931380, https://openalex.org/W3027880393, https://openalex.org/W3128244739, https://openalex.org/W2481159763, https://openalex.org/W3016137453, https://openalex.org/W2962723569, https://openalex.org/W3013557734, https://openalex.org/W2976720084, https://openalex.org/W2922234936, https://openalex.org/W2125943921 |
| referenced_works_count | 33 |
| abstract_inverted_index.a | 32, 76, 92, 102, 120, 135 |
| abstract_inverted_index.ML | 25, 97, 130 |
| abstract_inverted_index.as | 3, 40, 66 |
| abstract_inverted_index.be | 87 |
| abstract_inverted_index.by | 80 |
| abstract_inverted_index.if | 17 |
| abstract_inverted_index.in | 48, 134 |
| abstract_inverted_index.is | 20, 116 |
| abstract_inverted_index.of | 95, 119 |
| abstract_inverted_index.on | 36 |
| abstract_inverted_index.to | 22, 44, 59, 86 |
| abstract_inverted_index.we | 100 |
| abstract_inverted_index.The | 112 |
| abstract_inverted_index.and | 5, 10, 105 |
| abstract_inverted_index.are | 8, 29, 73 |
| abstract_inverted_index.at, | 90 |
| abstract_inverted_index.can | 57 |
| abstract_inverted_index.for | 62, 108, 124 |
| abstract_inverted_index.the | 46, 96, 117 |
| abstract_inverted_index.(ML) | 15, 56 |
| abstract_inverted_index.data | 19, 39 |
| abstract_inverted_index.edge | 6, 67, 110, 125 |
| abstract_inverted_index.full | 78 |
| abstract_inverted_index.help | 58 |
| abstract_inverted_index.here | 115 |
| abstract_inverted_index.more | 9, 11 |
| abstract_inverted_index.such | 2, 65 |
| abstract_inverted_index.that | 128 |
| abstract_inverted_index.Here, | 99 |
| abstract_inverted_index.based | 35 |
| abstract_inverted_index.built | 30 |
| abstract_inverted_index.cloud | 126 |
| abstract_inverted_index.loop. | 137 |
| abstract_inverted_index.needs | 85 |
| abstract_inverted_index.that, | 34 |
| abstract_inverted_index.using | 12 |
| abstract_inverted_index.around | 31 |
| abstract_inverted_index.better | 93 |
| abstract_inverted_index.clouds | 4, 7 |
| abstract_inverted_index.create | 23, 60 |
| abstract_inverted_index.direct | 77 |
| abstract_inverted_index.expert | 81 |
| abstract_inverted_index.input, | 41 |
| abstract_inverted_index.looked | 89 |
| abstract_inverted_index.system | 38, 47 |
| abstract_inverted_index.within | 50 |
| abstract_inverted_index.Machine | 13, 54 |
| abstract_inverted_index.actions | 43 |
| abstract_inverted_index.because | 70 |
| abstract_inverted_index.clouds. | 68 |
| abstract_inverted_index.control | 79 |
| abstract_inverted_index.created | 74 |
| abstract_inverted_index.explore | 101 |
| abstract_inverted_index.models. | 26, 98 |
| abstract_inverted_index.quality | 52, 84, 132 |
| abstract_inverted_index.ranges. | 53 |
| abstract_inverted_index.systems | 1, 28, 64, 127 |
| abstract_inverted_index.without | 75 |
| abstract_inverted_index.However, | 69 |
| abstract_inverted_index.Learning | 14 |
| abstract_inverted_index.concrete | 113 |
| abstract_inverted_index.expected | 51 |
| abstract_inverted_index.feedback | 136 |
| abstract_inverted_index.generate | 42 |
| abstract_inverted_index.learning | 55 |
| abstract_inverted_index.maintain | 45 |
| abstract_inverted_index.question | 49 |
| abstract_inverted_index.software | 82 |
| abstract_inverted_index.available | 21 |
| abstract_inverted_index.monitored | 37 |
| abstract_inverted_index.objective | 114 |
| abstract_inverted_index.reference | 121 |
| abstract_inverted_index.requiring | 91 |
| abstract_inverted_index.ML-created | 71 |
| abstract_inverted_index.controller | 33, 131 |
| abstract_inverted_index.governance | 106, 122 |
| abstract_inverted_index.management | 104, 133 |
| abstract_inverted_index.respective | 24 |
| abstract_inverted_index.sufficient | 18 |
| abstract_inverted_index.techniques | 16 |
| abstract_inverted_index.validation | 118 |
| abstract_inverted_index.controllers | 61, 72 |
| abstract_inverted_index.developers, | 83 |
| abstract_inverted_index.facilitates | 129 |
| abstract_inverted_index.architecture | 107, 123 |
| abstract_inverted_index.controllers. | 111 |
| abstract_inverted_index.specifically | 88 |
| abstract_inverted_index.Self-adaptive | 0, 27 |
| abstract_inverted_index.self-adaptive | 63, 109 |
| abstract_inverted_index.understanding | 94 |
| abstract_inverted_index.quality-oriented | 103 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 89 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| citation_normalized_percentile.value | 0.84514055 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |