{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T14:45:44Z","timestamp":1740149144368,"version":"3.37.3"},"reference-count":21,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2023,5,3]],"date-time":"2023-05-03T00:00:00Z","timestamp":1683072000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2023,5,3]],"date-time":"2023-05-03T00:00:00Z","timestamp":1683072000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100004837","name":"Ministerio de Ciencia e Innovaci\u00f3n","doi-asserted-by":"publisher","award":["PID 2019-104263RB-C433"],"award-info":[{"award-number":["PID 2019-104263RB-C433"]}],"id":[{"id":"10.13039\/501100004837","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100010067","name":"Gobierno de Arag\u00f3n","doi-asserted-by":"crossref","award":["E41-20R"],"award-info":[{"award-number":["E41-20R"]}],"id":[{"id":"10.13039\/501100010067","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100007041","name":"Universidad de Zaragoza","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100007041","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Oper Res Int J"],"published-print":{"date-parts":[[2023,6]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Private and public clouds are good means for getting on-demand intensive computing resources. In such a context, selecting the most appropriate clouds and virtual machines (VMs) is a complex task. From the user\u2019s point of view, the challenge consists in efficiently managing cloud resources while integrating prices and performance criteria. This paper focuses on the problem of selecting the appropriate clouds and VMs to run bags-of-tasks (BoT): big sets of identical and independent tasks. More precisely, we define new mathematical optimization models to deal with the time of use of each VMs and to jointly integrate the execution makespan and the cost into the objective function through a bi-objective problem. In order to provide trade-off solutions to the problem, we propose a lexicographic approach. In addition, we introduce, in two different ways, capacity constraints or bounds on the number of VMs available in the clouds. A global limit on the number of VMs or resource constraints at each time period can be defined. Computational experiments are performed on a synthetic dataset. Sensitivity analysis highlights the effect of the resource limits on the minimum makespan, the effect of the deadline in the total operation cost, the impact of considering instantaneous capacity constraints instead of a global limit and the trade-off between the cost and the execution makespan.<\/jats:p>","DOI":"10.1007\/s12351-023-00773-x","type":"journal-article","created":{"date-parts":[[2023,5,3]],"date-time":"2023-05-03T07:02:25Z","timestamp":1683097345000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A biobjective model for resource provisioning in multi-cloud environments with capacity constraints"],"prefix":"10.1007","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0906-7709","authenticated-orcid":false,"given":"Luce","family":"Brotcorne","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9622-8186","authenticated-orcid":false,"given":"Joaqu\u00edn","family":"Ezpeleta","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5630-3719","authenticated-orcid":false,"given":"Carmen","family":"Gal\u00e9","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,5,3]]},"reference":[{"key":"773_CR1","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1016\/j.future.2017.01.036","volume":"71","author":"S Abdi","year":"2017","unstructured":"Abdi S, PourKarimi L, Ahmadi M et\u00a0al. (2017) Cost minimization for deadline-constrained bag-of-tasks applications in federated hybrid clouds. Future Generat Comput Syst 71:113\u2013128. https:\/\/doi.org\/10.1016\/j.future.2017.01.036","journal-title":"Future Generat Comput Syst"},{"issue":"6","key":"773_CR2","doi-asserted-by":"publisher","first-page":"2801","DOI":"10.1007\/s11227-018-2322-9","volume":"74","author":"S Abdi","year":"2018","unstructured":"Abdi S, PourKarimi L, Ahmadi M et\u00a0al. (2018) Cost minimization for bag-of-tasks workflows in a federation of clouds. The J Supercomput 74(6):2801\u20132822. https:\/\/doi.org\/10.1007\/s11227-018-2322-9","journal-title":"The J Supercomput"},{"issue":"107","key":"773_CR3","doi-asserted-by":"publisher","first-page":"113","DOI":"10.1016\/j.asoc.2021.107113","volume":"102","author":"BH Abed-alguni","year":"2021","unstructured":"Abed-alguni BH, Alawad NA (2021) Distributed grey wolf optimizer for scheduling of workflow applications in cloud environments. Appl Soft Comput 102(107):113. https:\/\/doi.org\/10.1016\/j.asoc.2021.107113","journal-title":"Appl Soft Comput"},{"key":"773_CR4","doi-asserted-by":"publisher","unstructured":"Alkhanak EN, Lee SP, Khan SUR (2015) Cost-aware challenges for workflow scheduling approaches in cloud computing environments 50(C):3-21. https:\/\/doi.org\/10.1016\/j.future.2015.01.007,","DOI":"10.1016\/j.future.2015.01.007"},{"issue":"6","key":"773_CR5","doi-asserted-by":"publisher","first-page":"599","DOI":"10.1016\/j.future.2008.12.001","volume":"25","author":"R Buyya","year":"2009","unstructured":"Buyya R, Yeo CS, Venugopal S et\u00a0al. (2009) Cloud computing and emerging it platforms: vision, hype, and reality for delivering computing as the 5th utility. Future Generat Comput Syst 25(6):599\u2013616. https:\/\/doi.org\/10.1016\/j.future.2008.12.001","journal-title":"Future Generat Comput Syst"},{"key":"773_CR6","doi-asserted-by":"publisher","DOI":"10.1007\/s11227-021-04199-0","author":"A Chhabra","year":"2022","unstructured":"Chhabra A, Huang KC, Bacanin N et\u00a0al. (2022) Optimizing bag-of-tasks scheduling on cloud data centers using hybrid swarm-intelligence meta-heuristic. The J Supercomput. https:\/\/doi.org\/10.1007\/s11227-021-04199-0","journal-title":"The J Supercomput"},{"key":"773_CR7","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1016\/j.future.2017.02.004","volume":"71","author":"J D\u00edaz","year":"2017","unstructured":"D\u00edaz J, Entrialgo J, Garc\u00eda M et\u00a0al. (2017) Optimal allocation of virtual machines in multi-cloud environments with reserved and on-demand pricing. Future Generat Comput Syst 71:129\u2013144. https:\/\/doi.org\/10.1016\/j.future.2017.02.004","journal-title":"Future Generat Comput Syst"},{"key":"773_CR8","volume-title":"Multi Opt","author":"M Ehrgott","year":"2005","unstructured":"Ehrgott M (2005) Multi Opt, 2nd edn. Springer, Berlin, Heidelberg","edition":"2"},{"key":"773_CR9","doi-asserted-by":"publisher","unstructured":"Foster I, Zhao Y, Raicu I, et\u00a0al. (2008) Cloud computing and grid computing 360-degree compared. in: 2008 grid computing environments workshop, pp 1\u201310, https:\/\/doi.org\/10.1109\/GCE.2008.4738445","DOI":"10.1109\/GCE.2008.4738445"},{"key":"773_CR10","doi-asserted-by":"publisher","first-page":"1116","DOI":"10.1016\/j.future.2017.07.061","volume":"107","author":"T Genez","year":"2020","unstructured":"Genez T, Bittencourt L, Madeira E (2020) Time-discretization for speeding-up scheduling of deadline-constrained workflows in clouds. Future Generat Comput Syst 107:1116\u20131129. https:\/\/doi.org\/10.1016\/j.future.2017.07.061","journal-title":"Future Generat Comput Syst"},{"issue":"3","key":"773_CR11","doi-asserted-by":"publisher","first-page":"682","DOI":"10.1016\/j.future.2012.08.015","volume":"29","author":"G Juve","year":"2013","unstructured":"Juve G, Chervenak A, Deelman E et\u00a0al. (2013) Characterizing and profiling scientific workflows. Future Generat Comput Syst 29(3):682\u2013692. https:\/\/doi.org\/10.1016\/j.future.2012.08.015","journal-title":"Future Generat Comput Syst"},{"key":"773_CR12","doi-asserted-by":"publisher","DOI":"10.1007\/s10489-022-03942-1","author":"CAAASLM Karaja","year":"2022","unstructured":"Karaja CAAASLM (2022) Efficient bi-level multi objective approach for budget-constrained dynamic bag-of-tasks scheduling problem in heterogeneous multi-cloud environment. Appl Intell. https:\/\/doi.org\/10.1007\/s10489-022-03942-1","journal-title":"Appl Intell"},{"key":"773_CR13","doi-asserted-by":"publisher","unstructured":"Keivani A, Tapamo JR (2019) Task scheduling in cloud computing: A review. in: 2019 International conference on advances in big data, computing and data communication systems (icABCD), pp 1\u20136, https:\/\/doi.org\/10.1109\/ICABCD.2019.8851045","DOI":"10.1109\/ICABCD.2019.8851045"},{"key":"773_CR14","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.jnca.2019.06.006","volume":"143","author":"M Kumar","year":"2019","unstructured":"Kumar M, Sharma S, Goel A et\u00a0al. (2019) A comprehensive survey for scheduling techniques in cloud computing. J Netw Comput Appl 143:1\u201333","journal-title":"J Netw Comput Appl"},{"key":"773_CR15","doi-asserted-by":"publisher","DOI":"10.1145\/2797211","author":"ZA Mann","year":"2015","unstructured":"Mann ZA (2015) Allocation of virtual machines in cloud data centers-a survey of problem models and optimization algorithms. ACM Comput Surv. https:\/\/doi.org\/10.1145\/2797211","journal-title":"ACM Comput Surv"},{"issue":"1","key":"773_CR16","doi-asserted-by":"publisher","first-page":"256","DOI":"10.1109\/TCC.2017.2732344","volume":"8","author":"TP Pham","year":"2020","unstructured":"Pham TP, Durillo JJ, Fahringer T (2020) Predicting workflow task execution time in the cloud using a two-stage machine learning approach. IEEE Transact Cloud Comput 8(1):256\u2013268. https:\/\/doi.org\/10.1109\/TCC.2017.2732344","journal-title":"IEEE Transact Cloud Comput"},{"key":"773_CR17","doi-asserted-by":"publisher","DOI":"10.1109\/TCC.2021.3125426","author":"L Teylo","year":"2021","unstructured":"Teylo L, Arantes L, Sens P et\u00a0al. (2021) Scheduling bag-of-tasks in clouds using spot and burstable virtual machines. IEEE Transact Cloud Comput. https:\/\/doi.org\/10.1109\/TCC.2021.3125426","journal-title":"IEEE Transact Cloud Comput"},{"key":"773_CR18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.future.2017.11.038","volume":"82","author":"L Thai","year":"2018","unstructured":"Thai L, Varghese B, Barker A (2018) A survey and taxonomy of resource optimisation for executing bag-of-task applications on public clouds. Future Generat Comput Syst 82:1\u201311","journal-title":"Future Generat Comput Syst"},{"issue":"7","key":"773_CR19","doi-asserted-by":"publisher","first-page":"2952","DOI":"10.3837\/tiis.2016.07.005","volume":"10","author":"B Wang","year":"2016","unstructured":"Wang B, Song Y, Sun Y et\u00a0al. (2016) Managing deadline-constrained bag-of-tasks jobs on hybrid clouds with closest deadline first scheduling. KSII Transact Int Inform Syst 10(7):2952\u20132971. https:\/\/doi.org\/10.3837\/tiis.2016.07.005","journal-title":"KSII Transact Int Inform Syst"},{"key":"773_CR20","doi-asserted-by":"publisher","first-page":"419","DOI":"10.1016\/j.future.2018.11.012","volume":"94","author":"B Wang","year":"2019","unstructured":"Wang B, Song Y, Cao J et\u00a0al. (2019) Improving task scheduling with parallelism awareness in heterogeneous computational environments. Future Generat Comput Syst 94:419\u2013429. https:\/\/doi.org\/10.1016\/j.future.2018.11.012","journal-title":"Future Generat Comput Syst"},{"issue":"111","key":"773_CR21","first-page":"123","volume":"184","author":"L Yin","year":"2022","unstructured":"Yin L, Zhou J, Sun J (2022) A stochastic algorithm for scheduling bag-of-tasks applications on hybrid clouds under task duration variations. J Syst Softw 184(111):123","journal-title":"J Syst Softw"}],"container-title":["Operational Research"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12351-023-00773-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12351-023-00773-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12351-023-00773-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,8]],"date-time":"2023-06-08T11:28:49Z","timestamp":1686223729000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12351-023-00773-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5,3]]},"references-count":21,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2023,6]]}},"alternative-id":["773"],"URL":"https:\/\/doi.org\/10.1007\/s12351-023-00773-x","relation":{},"ISSN":["1109-2858","1866-1505"],"issn-type":[{"type":"print","value":"1109-2858"},{"type":"electronic","value":"1866-1505"}],"subject":[],"published":{"date-parts":[[2023,5,3]]},"assertion":[{"value":"5 May 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 February 2023","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 March 2023","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 May 2023","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"31"}}