{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,10]],"date-time":"2026-07-10T20:05:38Z","timestamp":1783713938899,"version":"3.55.0"},"reference-count":6,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,3,25]],"date-time":"2026-03-25T00:00:00Z","timestamp":1774396800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100018693","name":"Horizon Europe","doi-asserted-by":"publisher","award":["101135423"],"award-info":[{"award-number":["101135423"]}],"id":[{"id":"10.13039\/100018693","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Data in Brief"],"published-print":{"date-parts":[[2026,6]]},"DOI":"10.1016\/j.dib.2026.112734","type":"journal-article","created":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T00:48:19Z","timestamp":1774658899000},"page":"112734","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"special_numbering":"C","title":["A telemetry dataset on resource utilisation and power consumption in the edge-cloud continuum"],"prefix":"10.1016","volume":"66","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3456-2311","authenticated-orcid":false,"given":"Ioanna Angeliki","family":"Kapetanidou","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5178-3840","authenticated-orcid":false,"given":"Thanasis","family":"Kotsiopoulos","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-6698-6044","authenticated-orcid":false,"given":"Giorgos","family":"Thanasoulis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7659-2354","authenticated-orcid":false,"given":"Paschalis","family":"Bizopoulos","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8514-6636","authenticated-orcid":false,"given":"Athanasios","family":"Liatifis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-7905-9317","authenticated-orcid":false,"given":"Manolis","family":"Skoularikis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6954-4861","authenticated-orcid":false,"given":"Alexandros","family":"Nizamis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Panagiotis","family":"Sarigiannidis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6381-8326","authenticated-orcid":false,"given":"Konstantinos","family":"Votis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"key":"10.1016\/j.dib.2026.112734_bib0001","doi-asserted-by":"crossref","unstructured":"T. Kotsiopoulos et al., Optimizing task allocation in the cloud-edge continuum: a deep reinforcement learning and graph neural network approach, 2025 44th International Symposium on Reliable Distributed Systems (SRDS), IEEE, pp. 465\u2013470..","DOI":"10.1109\/SRDS69199.2025.00058"},{"key":"10.1016\/j.dib.2026.112734_bib0002","series-title":"Proc. 2024 IEEE Int. Conf. Eng. Technol. Innov. (ICE\/ITMC)","article-title":"Enact-a framework for adaptive scheduling and deployments of data intensive workloads on energy efficient edge to cloud continuum","author":"Nizamis","year":"2024"},{"issue":"3","key":"10.1016\/j.dib.2026.112734_bib0003","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1007\/s10723-025-09810-9","article-title":"Cognitive computing continuum: state-of-the-art review and ENACT vision & approach","volume":"23","author":"Kapetanidou","year":"2025","journal-title":"J. Grid Comput."},{"issue":"8","key":"10.1016\/j.dib.2026.112734_bib0004","first-page":"1","article-title":"Public datasets for cloud computing: a comprehensive survey","volume":"57","author":"Liu","year":"2025","journal-title":"ACM Comput. Surv."},{"key":"10.1016\/j.dib.2026.112734_bib0005","doi-asserted-by":"crossref","unstructured":"B.F. Jahnke, R. Schmook, F. Howar, (2025). GMB-ECC: guided measuring and benchmarking of the edge cloud continuum, arXiv preprint arXiv:2503.07183.","DOI":"10.1109\/ACCESS.2026.3685833"},{"key":"10.1016\/j.dib.2026.112734_bib0006","doi-asserted-by":"crossref","unstructured":"A.A.E. Elsayed, A.A. Al-Obaidi, H.E.Z. Farag, Characterization of high-resolution AI data center training workloads on single and multiple GPU nodes PREPRINT (Version 1) available at Research Square (2025).","DOI":"10.21203\/rs.3.rs-7943457\/v1"}],"container-title":["Data in Brief"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2352340926002878?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2352340926002878?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,8]],"date-time":"2026-06-08T11:35:50Z","timestamp":1780918550000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2352340926002878"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6]]},"references-count":6,"alternative-id":["S2352340926002878"],"URL":"https:\/\/doi.org\/10.1016\/j.dib.2026.112734","relation":{"is-supplemented-by":[{"id-type":"uri","id":"https:\/\/zenodo.org\/records\/18920397","asserted-by":"subject"}]},"ISSN":["2352-3409"],"issn-type":[{"value":"2352-3409","type":"print"}],"subject":[],"published":{"date-parts":[[2026,6]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A telemetry dataset on resource utilisation and power consumption in the edge-cloud continuum","name":"articletitle","label":"Article Title"},{"value":"Data in Brief","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.dib.2026.112734","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Authors. Published by Elsevier Inc.","name":"copyright","label":"Copyright"}],"article-number":"112734"}}