{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T11:07:52Z","timestamp":1768043272820,"version":"3.49.0"},"reference-count":71,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T00:00:00Z","timestamp":1768003200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T00:00:00Z","timestamp":1768003200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100003593","name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","doi-asserted-by":"publisher","award":["302948\/2021"],"award-info":[{"award-number":["302948\/2021"]}],"id":[{"id":"10.13039\/501100003593","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003593","name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico","doi-asserted-by":"publisher","award":["311898\/2021-1"],"award-info":[{"award-number":["311898\/2021-1"]}],"id":[{"id":"10.13039\/501100003593","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004586","name":"Funda\u00e7 Carlos Chagas Filho de Amparo \u00e0 Pesquisa do Estado do Rio de Janeiro","doi-asserted-by":"publisher","award":["E-26\/202.806\/2019"],"award-info":[{"award-number":["E-26\/202.806\/2019"]}],"id":[{"id":"10.13039\/501100004586","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100002322","name":"Coordena\u00e7 de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","doi-asserted-by":"publisher","award":["E-26\/202.806\/2019"],"award-info":[{"award-number":["E-26\/202.806\/2019"]}],"id":[{"id":"10.13039\/501100002322","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["SN COMPUT. SCI."],"DOI":"10.1007\/s42979-025-04582-1","type":"journal-article","created":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T07:25:47Z","timestamp":1768029947000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Greedy Constructive Heuristic for Executing Cloud-Based Workflows with Data Confidentiality Restrictions"],"prefix":"10.1007","volume":"7","author":[{"given":"Rodrigo A. P.","family":"Silva","sequence":"first","affiliation":[]},{"given":"Wesley","family":"Ferreira","sequence":"additional","affiliation":[]},{"given":"Esther","family":"Pacitti","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3434-3074","authenticated-orcid":false,"given":"Yuri","family":"Frota","sequence":"additional","affiliation":[]},{"given":"Daniel","family":"de Oliveira","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,1,10]]},"reference":[{"issue":"1","key":"4582_CR1","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1177\/1094342017704893","volume":"32","author":"E Deelman","year":"2018","unstructured":"Deelman E, Peterka T, Altintas I, et al. The future of scientific workflows. Int J High Perform Comput Appl. 2018;32(1):159\u201375. https:\/\/doi.org\/10.1177\/1094342017704893.","journal-title":"Int J High Perform Comput Appl"},{"key":"4582_CR2","doi-asserted-by":"publisher","unstructured":"Oliveira DCM, Liu J, Pacitti E. Data-intensive workflow management: for clouds and data-intensive and scalable computing environments. synthesis lectures on data management. San Rafael: Morgan & Claypool Publishers; 2019. https:\/\/doi.org\/10.2200\/S00915ED1V01Y201904DTM060 .","DOI":"10.2200\/S00915ED1V01Y201904DTM060"},{"key":"4582_CR3","doi-asserted-by":"publisher","unstructured":"Krawczuk P, Papadimitriou G, Tanaka R, Do TMA, Subramanya S, Nagarkar S, Jain A, Lam K, Mandal A, Pottier L, Deelman E. A performance characterization of scientific machine learning workflows. In: 2021 IEEE workshop on workflows in support of large-scale science (WORKS), St. Louis, MO, USA, November 15, 2021, pp 58\u201365. IEEE. 2021. https:\/\/doi.org\/10.1109\/WORKS54523.2021.00013 .","DOI":"10.1109\/WORKS54523.2021.00013"},{"issue":"12","key":"4582_CR4","doi-asserted-by":"publisher","first-page":"1328","DOI":"10.14778\/3402755.3402766","volume":"4","author":"E Ogasawara","year":"2011","unstructured":"Ogasawara E, Dias J, Oliveira D, Porto F, Valduriez P, Mattoso M. An algebraic approach for data-centric scientific workflows. Proc VLDB Endow. 2011;4(12):1328\u201339.","journal-title":"Proc VLDB Endow"},{"issue":"13","key":"4582_CR5","doi-asserted-by":"publisher","first-page":"1531","DOI":"10.1002\/CPE.1880","volume":"24","author":"D Oliveira","year":"2012","unstructured":"Oliveira D, Ogasawara ES, Oca\u00f1a KACS, Bai\u00e3o FA, Mattoso M. An adaptive parallel execution strategy for cloud-based scientific workflows. Concurr Comput Pract Exp. 2012;24(13):1531\u201350. https:\/\/doi.org\/10.1002\/CPE.1880.","journal-title":"Concurr Comput Pract Exp"},{"key":"4582_CR6","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1016\/j.future.2014.10.008","volume":"46","author":"E Deelman","year":"2015","unstructured":"Deelman E, Vahi K, Juve G, et al. Pegasus, a workflow management system for science automation. Fut Gen Comp Syst. 2015;46:17\u201335. https:\/\/doi.org\/10.1016\/j.future.2014.10.008.","journal-title":"Fut Gen Comp Syst"},{"key":"4582_CR7","doi-asserted-by":"publisher","unstructured":"Mofrad S, Ahmed I, Lu S, et al Secdataview: a secure big data workflow management system for heterogeneous computing environments. In: Proc. of the ACSAC 2019, pp. 390\u2013403. New York: ACM; 2019. https:\/\/doi.org\/10.1145\/3359789.3359845 .","DOI":"10.1145\/3359789.3359845"},{"key":"4582_CR8","doi-asserted-by":"publisher","DOI":"10.1016\/J.SOFTX.2024.101927","volume":"28","author":"T Guedes","year":"2024","unstructured":"Guedes T, Mattoso M, Bedo MVN, Oliveira D. Version [1.0]- [samba-rap is music to scientists\u2019 ears: adding provenance support to spark-based scientific workflows]. SoftwareX. 2024;28:101927. https:\/\/doi.org\/10.1016\/J.SOFTX.2024.101927.","journal-title":"SoftwareX"},{"issue":"3","key":"4582_CR9","doi-asserted-by":"publisher","first-page":"521","DOI":"10.1007\/S10723-012-9227-2","volume":"10","author":"D Oliveira","year":"2012","unstructured":"Oliveira D, Oca\u00f1a KACS, Bai\u00e3o FA, Mattoso M. A provenance-based adaptive scheduling heuristic for parallel scientific workflows in clouds. J Grid Comput. 2012;10(3):521\u201352. https:\/\/doi.org\/10.1007\/S10723-012-9227-2.","journal-title":"J Grid Comput"},{"key":"4582_CR10","doi-asserted-by":"publisher","unstructured":"Silva RF, Bard D, Chard K, Witt SD, Foster IT, Gibbs T, Goble CA, Godoy WF, Gustafsson J, Haus U, Hudson S, Jha S, Los L, Paine D, Suter F, Ward LT, Wilkinson SR, Amaris M, Babuji YN, Bader J, Balin R, Balouek D, Beecroft SJ, Belhajjame K, Bhattarai R, Brewer W, Brunk P, Ca\u00edno-Lores S, Casanova H, Cassol D, Coleman J, Coleman T, Colonnelli I, Silva AAD, Oliveira D, Elahi P, Elfaramawy N, Elwasif WR, Etz B, Fahringer T, Ferreira W, Filgueira R, Tande JF, Gadelha L, Gallo A, Garijo D, Georgiou Y, Gritsch P, Grubel P, Gueroudji A, Guilloteau Q, Hamalainen C, Enriquez RPH, Huet L, Kesling KH, Iborra P, Jahangiri S, Janssen J, Jordan J, Kanwal S, Kunstmann LNO, Lehmann, F, Leser, U, Li, C, Liu, P, L\u00fcttgau, J, Lupat, R, Fern\u00e1ndez JM, Maheshwari K, Malik T, Marquez J, Matsuda M, Medic D, Mohammadi S, Mulone A, Navarro J, Ng KW, N\u00f6lp K, Paula\u00a0Kinoshita B, Prout R, Crusoe MR, Ristov S, Robila SA, Rosendo D, Rowell B, Rybicki J, Sanchez H, Saurabh N, Saurav SK, Scogland T, Senanayake D, Shin W, Sirvent R, Skluzacek TJ, Sly-Delgado B, Soiland-Reyes S, Souza A, Souza R, Talia D, Tallent NR. Workflows community summit 2024: Future trends and challenges in scientific workflows. CoRR arXiv: 2410.14943 2024. https:\/\/doi.org\/10.48550\/ARXIV.2410.14943","DOI":"10.48550\/ARXIV.2410.14943"},{"key":"4582_CR11","doi-asserted-by":"publisher","first-page":"658","DOI":"10.1016\/J.FUTURE.2020.05.031","volume":"112","author":"T Guedes","year":"2020","unstructured":"Guedes T, Martins LB, Falci MLF, Silva V, Oca\u00f1a KACS, Mattoso M, et al. Capturing and analyzing provenance from spark-based scientific workflows with samba-rap. Future Gener Comput Syst. 2020;112:658\u201369. https:\/\/doi.org\/10.1016\/J.FUTURE.2020.05.031.","journal-title":"Future Gener Comput Syst"},{"key":"4582_CR12","doi-asserted-by":"publisher","unstructured":"Babuji Y, Woodard A, Li Z, et al. Parsl: Pervasive parallel programming in python. In: Proc. of the HPDC \u201919, New York, NY, USA, 2019. pp. 25\u201336. https:\/\/doi.org\/10.1145\/3307681.3325400 .","DOI":"10.1145\/3307681.3325400"},{"issue":"4","key":"4582_CR13","doi-asserted-by":"publisher","first-page":"316","DOI":"10.1038\/nbt.3820","volume":"35","author":"P Di Tommaso","year":"2017","unstructured":"Di Tommaso P, et al. Nextflow enables reproducible computational workflows. Nat Biotechnol. 2017;35(4):316\u20139. https:\/\/doi.org\/10.1038\/nbt.3820.","journal-title":"Nat Biotechnol"},{"key":"4582_CR14","unstructured":"Zaharia M, et al. Resilient distributed datasets: a fault-tolerant abstraction for in-memory cluster computing. In: NSDI\u201912, p. 2. USENIX, USA 2012."},{"key":"4582_CR15","doi-asserted-by":"publisher","unstructured":"Oliveira D, Ogasawara ES, Bai\u00e3o FA, Mattoso M. Scicumulus: a lightweight cloud middleware to explore many task computing paradigm in scientific workflows. In: CLOUD\u201910, 2010;378\u2013385. https:\/\/doi.org\/10.1109\/CLOUD.2010.64.","DOI":"10.1109\/CLOUD.2010.64"},{"key":"4582_CR16","unstructured":"Garey MR, Johnson DS. Computers and Intractability: A Guide to the Theory of NP-completeness. Mathematical Sciences Series. Freeman, 1979. https:\/\/books.google.com.br\/books?id=fjxGAQAAIAAJ"},{"key":"4582_CR17","doi-asserted-by":"publisher","unstructured":"Zamfiroiu A, Petre I, Boncea R. Cloud computing vulnerabilities analysis. In: Proc. of the CCIOT \u201919, 2019;48\u201353. https:\/\/doi.org\/10.1145\/3361821.3361830.","DOI":"10.1145\/3361821.3361830"},{"key":"4582_CR18","doi-asserted-by":"publisher","unstructured":"Ristenpart T, Tromer E, Shacham H, Savage S. Hey, you, get off of my cloud: Exploring information leakage in third-party compute clouds. In: Proc. of the CCS \u201909, 2009;199\u2013212. https:\/\/doi.org\/10.1145\/1653662.1653687.","DOI":"10.1145\/1653662.1653687"},{"key":"4582_CR19","unstructured":"European Union: Regulation (EU) 2016\/679 of the European Parliament and of the council of 27 april 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data (general data protection regulation). 2016. https:\/\/eur-lex.europa.eu\/eli\/reg\/2016\/679\/oj. Official Journal of the European Union, L 119, 4 May 2016."},{"key":"4582_CR20","unstructured":"Presid\u00eancia da Rep\u00fablica Federativa do Brasil: Lei $${\\rm n}^{\\circ }$$ 13.709, de 14 de agosto de 2018 \u2013 Lei Geral de Prote\u00e7\u00e3o de Dados Pessoais (LGPD). https:\/\/www.planalto.gov.br\/ccivil_03\/_ato2015-2018\/2018\/lei\/l13709.htm. Publicado no Di\u00e1rio Oficial da Uni\u00e3o em 15 de agosto de 2018 2018."},{"issue":"3","key":"4582_CR21","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 AL, Deelman E, Bharathi S, Mehta G, Vahi K. Characterizing and profiling scientific workflows. FGCS. 2013;29(3):682\u201392. https:\/\/doi.org\/10.1016\/J.FUTURE.2012.08.015.","journal-title":"FGCS"},{"key":"4582_CR22","doi-asserted-by":"publisher","unstructured":"Branco-Jr, EC, Monteiro JM, Reis R, Machado JC. A new mechanism to preserving data confidentiality in cloud database scenarios. In: ICEIS, vol. 291, pp. 261\u2013283. Berlin: Springer; 2016. https:\/\/doi.org\/10.1007\/978-3-319-62386-3_13 .","DOI":"10.1007\/978-3-319-62386-3_13"},{"key":"4582_CR23","doi-asserted-by":"publisher","first-page":"697","DOI":"10.1016\/J.FUTURE.2019.01.051","volume":"97","author":"MA Guerine","year":"2019","unstructured":"Guerine MA, Stockinger MB, Rosseti I, Simonetti LG, Oca\u00f1a KACS, Plastino A, et al. A provenance-based heuristic for preserving results confidentiality in cloud-based scientific workflows. Future Gener Comput Syst. 2019;97:697\u2013713. https:\/\/doi.org\/10.1016\/J.FUTURE.2019.01.051.","journal-title":"Future Gener Comput Syst"},{"key":"4582_CR24","doi-asserted-by":"publisher","unstructured":"Rosseti I, Oca\u00f1a KACS, Oliveira D. Towards preserving results confidentiality in cloud-based scientific workflows. In: Montagnat J, Taylor IJ, Gesing S, Sakellariou R, editors. Proceedings of the 12th Workshop on Workflows in Support of Large-Scale Science, WORKS@SC 2017, Denver, CO, USA, November 12 - 17, 2017. New York: ACM; 2017. pp. 6\u2013169. https:\/\/doi.org\/10.1145\/3150994.3151002.","DOI":"10.1145\/3150994.3151002"},{"key":"4582_CR25","doi-asserted-by":"publisher","unstructured":"Dwork C. Differential privacy. In: Bugliesi M, Preneel B, Sassone V, Wegener I (Eds) Automata, Languages and Programming, 33rd International Colloquium, ICALP 2006, Venice, Italy, July 10-14, 2006, Proceedings, Part II. Lecture notes in computer science. Berlin: Springer; 2006. vol. 4052, pp. 1\u201312. https:\/\/doi.org\/10.1007\/11787006_1.","DOI":"10.1007\/11787006_1"},{"key":"4582_CR26","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.120401","volume":"228","author":"Z Sun","year":"2023","unstructured":"Sun Z, Huang H, Li Z, Gu C, Xie R, Qian B. Efficient, economical and energy-saving multi-workflow scheduling in hybrid cloud. Expert Syst Appl. 2023;228:120401. https:\/\/doi.org\/10.1016\/j.eswa.2023.120401.","journal-title":"Expert Syst Appl"},{"issue":"5","key":"4582_CR27","doi-asserted-by":"publisher","first-page":"1887","DOI":"10.1109\/TSC.2024.3407595","volume":"17","author":"X Shu","year":"2024","unstructured":"Shu X, Wu Q, Zhou M, Wen J. A communication-contention-aware privacy-preserving workflow scheduling method for geo-distributed datacenters. IEEE Trans Serv Comput. 2024;17(5):1887\u201398. https:\/\/doi.org\/10.1109\/TSC.2024.3407595.","journal-title":"IEEE Trans Serv Comput"},{"key":"4582_CR28","unstructured":"Wang Y, Kanwal N, Engan K, Rong C, Grosso P, Zhao Z. Towards privacy-, budget-, and deadline-aware service optimization for large medical image processing across hybrid clouds; 2024. arXiv:2401.12597."},{"key":"4582_CR29","doi-asserted-by":"publisher","unstructured":"Wohlin C. Guidelines for snowballing in systematic literature studies and a replication in software engineering. In: Proceedings of the 18th international conference on evaluation and assessment in software engineering. EASE \u201914. Association for computing machinery, New York, NY, USA; 2014. https:\/\/doi.org\/10.1145\/2601248.2601268.","DOI":"10.1145\/2601248.2601268"},{"key":"4582_CR30","doi-asserted-by":"publisher","first-page":"140","DOI":"10.1016\/j.future.2015.12.014","volume":"65","author":"Z Li","year":"2016","unstructured":"Li Z, Ge J, Yang H, Huang L, Hu H, Hu H, et al. A security and cost aware scheduling algorithm for heterogeneous tasks of scientific workflow in clouds. Futur Gener Comput Syst. 2016;65:140\u201352.","journal-title":"Futur Gener Comput Syst"},{"issue":"4","key":"4582_CR31","first-page":"1176","volume":"28","author":"S Sharif","year":"2016","unstructured":"Sharif S, Watson P, et al. Privacy-aware scheduling SAAS in high performance computing environments. IEEE TPDS. 2016;28(4):1176\u201388.","journal-title":"IEEE TPDS"},{"key":"4582_CR32","doi-asserted-by":"crossref","unstructured":"Shishido H, Estrella JC, et al. Multi-objective optimization for workflow scheduling under task selection policies in clouds. In: CEC; 2018. pp. 1\u20138.","DOI":"10.1109\/CEC.2018.8477799"},{"key":"4582_CR33","doi-asserted-by":"crossref","unstructured":"Tawfeek MA, AbdulHamed AA. Service flow management with multi-objective constraints in heterogeneous computing. In: ICCES; 2018. pp. 258\u2013263.","DOI":"10.1109\/ICCES.2018.8639482"},{"issue":"5","key":"4582_CR34","doi-asserted-by":"publisher","first-page":"1745","DOI":"10.1007\/s00500-017-2897-8","volume":"23","author":"JAJ Sujana","year":"2019","unstructured":"Sujana JAJ, Revathi T, Priya TS, Muneeswaran K. Smart PSO-based secured scheduling approaches for scientific workflows in cloud computing. Soft Comp. 2019;23(5):1745\u201365.","journal-title":"Soft Comp"},{"key":"4582_CR35","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1016\/j.simpat.2018.10.004","volume":"93","author":"F Abazari","year":"2019","unstructured":"Abazari F, Analoui M, Takabi H, Fu S. Mows: multi-objective workflow scheduling in cloud computing based on heuristic algorithm. Simul Model Pract Theory. 2019;93:119\u201332.","journal-title":"Simul Model Pract Theory"},{"issue":"8","key":"4582_CR36","first-page":"1872","volume":"30","author":"AC Zhou","year":"2019","unstructured":"Zhou AC, Xiao Y, Gong Y, He B, Zhai J, Mao R. Privacy regulation aware process mapping in geo-distributed cloud data centers. IEEE TPDS. 2019;30(8):1872\u201388.","journal-title":"IEEE TPDS"},{"key":"4582_CR37","doi-asserted-by":"publisher","first-page":"697","DOI":"10.1016\/j.future.2019.01.051","volume":"97","author":"M Guerine","year":"2019","unstructured":"Guerine M, Stockinger MB, et al. A provenance-based heuristic for preserving results confidentiality in cloud-based scientific workflows. Fut Gen Comp Sys. 2019;97:697\u2013713. https:\/\/doi.org\/10.1016\/j.future.2019.01.051.","journal-title":"Fut Gen Comp Sys"},{"key":"4582_CR38","doi-asserted-by":"publisher","first-page":"1084","DOI":"10.1016\/j.future.2018.03.028","volume":"108","author":"Y Wen","year":"2020","unstructured":"Wen Y, Liu J, Dou W, Xu X, Cao B, Chen J. Scheduling workflows with privacy protection constraints for big data applications on cloud. Future Gener Comput Syst. 2020;108:1084\u201391. https:\/\/doi.org\/10.1016\/j.future.2018.03.028.","journal-title":"Future Gener Comput Syst"},{"issue":"4","key":"4582_CR39","doi-asserted-by":"publisher","first-page":"476","DOI":"10.1504\/IJIE.2021.117991","volume":"8","author":"SS Hammed","year":"2021","unstructured":"Hammed SS, Arunkumar B. Multi-level security model for privacy preserving in the cloud workflow scheduling. Int J Intell Enterp. 2021;8(4):476\u201391. https:\/\/doi.org\/10.1504\/IJIE.2021.117991.","journal-title":"Int J Intell Enterp"},{"key":"4582_CR40","doi-asserted-by":"publisher","first-page":"269","DOI":"10.1016\/j.future.2022.01.018","volume":"131","author":"J Lei","year":"2022","unstructured":"Lei J, Wu Q, Xu J. Privacy and security-aware workflow scheduling in a hybrid cloud. Futur Gener Comput Syst. 2022;131:269\u201378.","journal-title":"Futur Gener Comput Syst"},{"key":"4582_CR41","doi-asserted-by":"publisher","unstructured":"Wang Y, Kanwal N, Engan K, Rong C, Zhao Z. Towards a privacy-preserving distributed cloud service for preprocessing very large medical images. In: 2023 IEEE international conference on digital health (ICDH); 2023. pp. 325\u2013327. https:\/\/doi.org\/10.1109\/ICDH60066.2023.00055.","DOI":"10.1109\/ICDH60066.2023.00055"},{"key":"4582_CR42","doi-asserted-by":"crossref","unstructured":"Soveizi N, Turkmen F. Secflow: adaptive security-aware workflow management system in multi-cloud environments. In: Sales TP, Kinderen S, Proper HA, Pufahl L, Karastoyanova D, Sinderen M (Eds). Enterprise Design, Operations, and Computing. EDOC 2023 Workshops. Cham: Springer 2024. pp. 281\u2013297.","DOI":"10.1007\/978-3-031-54712-6_17"},{"key":"4582_CR43","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1016\/j.future.2024.05.002","volume":"159","author":"S Wang","year":"2024","unstructured":"Wang S, Wu J, Yuan Z, Gao A, Chen WT. Makespan minimization for workflows with multiple privacy levels. Future Gener Comput Syst. 2024;159:39\u201350. https:\/\/doi.org\/10.1016\/j.future.2024.05.002.","journal-title":"Future Gener Comput Syst"},{"key":"4582_CR44","doi-asserted-by":"publisher","DOI":"10.1016\/j.jpdc.2024.104882","volume":"189","author":"S Wang","year":"2024","unstructured":"Wang S, Yuan Z, Zhang X, Wu J, Wang Y. Cloud-edge-end workflow scheduling with multiple privacy levels. J Parallel Distrib Comput. 2024;189:104882. https:\/\/doi.org\/10.1016\/j.jpdc.2024.104882.","journal-title":"J Parallel Distrib Comput"},{"issue":"2","key":"4582_CR45","doi-asserted-by":"publisher","first-page":"721","DOI":"10.1007\/s41870-023-01523-0","volume":"16","author":"M Alam","year":"2024","unstructured":"Alam M, Shahid M, Mustajab S, Ahmad F. Security driven dynamic level scheduling under precedence constrained tasks in IAAS cloud. Int J Inf Technol. 2024;16(2):721\u20139. https:\/\/doi.org\/10.1007\/s41870-023-01523-0.","journal-title":"Int J Inf Technol"},{"issue":"1","key":"4582_CR46","doi-asserted-by":"publisher","first-page":"3607","DOI":"10.1038\/s41598-025-86814-1","volume":"15","author":"R Rateb","year":"2025","unstructured":"Rateb R, Hadi AA, Tamanampudi VM, Abualigah L, Ezugwu AE, Alzahrani AI, et al. An optimal workflow scheduling in IoT-fog-cloud system for minimizing time and energy. Sci Rep. 2025;15(1):3607.","journal-title":"Sci Rep"},{"key":"4582_CR47","doi-asserted-by":"publisher","DOI":"10.1016\/j.cma.2024.117588","volume":"434","author":"S Biswas","year":"2025","unstructured":"Biswas S, Singh G, Maiti B, Ezugwu AE-S, Saleem K, Smerat A, et al. Integrating differential evolution into gazelle optimization for advanced global optimization and engineering applications. Comput Methods Appl Mech Eng. 2025;434:117588.","journal-title":"Comput Methods Appl Mech Eng"},{"key":"4582_CR48","doi-asserted-by":"publisher","DOI":"10.1016\/j.cam.2024.116475","volume":"462","author":"M Varshney","year":"2025","unstructured":"Varshney M, Kumar P, Abualigah L. Hybridizing remora and aquila optimizer with dynamic oppositional learning for structural engineering design problems. J Comput Appl Math. 2025;462:116475.","journal-title":"J Comput Appl Math"},{"key":"4582_CR49","doi-asserted-by":"publisher","DOI":"10.1016\/j.fss.2024.109135","volume":"498","author":"Z Liu","year":"2025","unstructured":"Liu Z, Qiu H, Letchmunan S, Deveci M, Abualigah L. Multi-view evidential c-means clustering with view-weight and feature-weight learning. Fuzzy Sets Syst. 2025;498:109135.","journal-title":"Fuzzy Sets Syst"},{"key":"4582_CR50","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1007\/978-981-99-3569-7_7","volume-title":"Security, privacy and data analytics","author":"S Hammouti","year":"2023","unstructured":"Hammouti S, Yagoubi B, Makhlouf SA. Secured workflow scheduling techniques in cloud: a survey. In: Rao UP, Alazab M, Gohil BN, Chelliah PR, editors. Security, privacy and data analytics. Singapore: Springer; 2023. p. 85\u2013104."},{"key":"4582_CR51","doi-asserted-by":"publisher","first-page":"184","DOI":"10.1016\/j.future.2023.05.015","volume":"148","author":"N Soveizi","year":"2023","unstructured":"Soveizi N, Turkmen F, Karastoyanova D. Security and privacy concerns in cloud-based scientific and business workflows: a systematic review. Future Gener Comput Syst. 2023;148:184\u2013200. https:\/\/doi.org\/10.1016\/j.future.2023.05.015.","journal-title":"Future Gener Comput Syst"},{"issue":"1","key":"4582_CR52","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1002\/SPE.995","volume":"41","author":"RN Calheiros","year":"2011","unstructured":"Calheiros RN, Ranjan R, Beloglazov A, Rose CAFD, Buyya R. Cloudsim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms. Softw Pract Exp. 2011;41(1):23\u201350. https:\/\/doi.org\/10.1002\/SPE.995.","journal-title":"Softw Pract Exp"},{"key":"4582_CR53","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.future.2017.05.017","volume":"76","author":"L Teylo","year":"2017","unstructured":"Teylo L, Paula U Jr., et al. A hybrid evolutionary algorithm for task scheduling and data assignment of data-intensive scientific workflows on clouds. FGCS. 2017;76:1\u201317. https:\/\/doi.org\/10.1016\/j.future.2017.05.017.","journal-title":"FGCS"},{"key":"4582_CR54","doi-asserted-by":"publisher","unstructured":"Gentry C. Fully homomorphic encryption using ideal lattices. In: Proceedings of the Forty-First Annual ACM Symposium on Theory of Computing. STOC \u201909, pp. 169\u2013178. Association for Computing Machinery, New York, NY, USA; 2009. https:\/\/doi.org\/10.1145\/1536414.1536440.","DOI":"10.1145\/1536414.1536440"},{"key":"4582_CR55","doi-asserted-by":"publisher","unstructured":"McSherry F, Talwar K. Mechanism design via differential privacy. In: Proceedings of the 48th Annual IEEE Symposium on Foundations of Computer Science. FOCS \u201907, pp. 94\u2013103. IEEE Computer Society, USA; 2007. https:\/\/doi.org\/10.1109\/FOCS.2007.41.","DOI":"10.1109\/FOCS.2007.41"},{"issue":"3\u20134","key":"4582_CR56","doi-asserted-by":"publisher","first-page":"211","DOI":"10.1561\/0400000042","volume":"9","author":"C Dwork","year":"2014","unstructured":"Dwork C, Roth A. The algorithmic foundations of differential privacy. Found Trends Theor Comput Sci. 2014;9(3\u20134):211\u2013407. https:\/\/doi.org\/10.1561\/0400000042.","journal-title":"Found Trends Theor Comput Sci"},{"issue":"6","key":"4582_CR57","doi-asserted-by":"publisher","first-page":"1191","DOI":"10.1007\/s00778-022-00774-w","volume":"32","author":"VAE Farias","year":"2023","unstructured":"Farias VAE, Brito FT, Flynn C, Machado JC, Majumdar S, Srivastava D. Local dampening: differential privacy for non-numeric queries via local sensitivity. VLDB J. 2023;32(6):1191\u2013214. https:\/\/doi.org\/10.1007\/s00778-022-00774-w.","journal-title":"VLDB J"},{"key":"4582_CR58","unstructured":"McKenna R, Sheldon D. Permute-and-flip: a new mechanism for differentially private selection. In: Proceedings of the 34th international conference on neural information processing systems. NIPS \u201920. Curran Associates Inc., Red Hook, NY, USA; 2020."},{"key":"4582_CR59","doi-asserted-by":"publisher","unstructured":"Ramon J. In: Dubitzky W, Wolkenhauer O, Cho K-H, Yokota H (Eds). Graph Mining. New York, NY: Springer; 2013. p. 865\u20137. https:\/\/doi.org\/10.1007\/978-1-4419-9863-7_615.","DOI":"10.1007\/978-1-4419-9863-7_615"},{"key":"4582_CR60","doi-asserted-by":"crossref","unstructured":"Oca\u00f1a KA, Oliveira D, Ogasawara E, D\u00e1vila AM, Lima AA, Mattoso M. Sciphy: a cloud-based workflow for phylogenetic analysis of drug targets in protozoan genomes. In: BSB11, Berlin; Springer; 2011. pp. 66\u201370.","DOI":"10.1007\/978-3-642-22825-4_9"},{"key":"4582_CR61","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4419-1665-5","volume-title":"Handbook of metaheuristics","author":"M Gendreau","year":"2010","unstructured":"Gendreau M, Potvin J-Y, et al. Handbook of metaheuristics, vol. 2. Berlin: Springer; 2010."},{"key":"4582_CR62","doi-asserted-by":"publisher","first-page":"727","DOI":"10.1007\/s10696-022-09453-y","volume":"35","author":"A Amirteimoori","year":"2022","unstructured":"Amirteimoori A, Kia R. Concurrent scheduling of jobs and AGVs in a flexible job shop system: a parallel hybrid PSO-GA meta-heuristic. Flex Serv Manuf J. 2022;35:727\u201353.","journal-title":"Flex Serv Manuf J"},{"issue":"2","key":"4582_CR63","doi-asserted-by":"publisher","first-page":"629","DOI":"10.1016\/j.ejor.2020.09.042","volume":"291","author":"M de Weerdt","year":"2021","unstructured":"de Weerdt M, Baart R, He L. Single-machine scheduling with release times, deadlines, setup times, and rejection. Eur J Oper Res. 2021;291(2):629\u201339. https:\/\/doi.org\/10.1016\/j.ejor.2020.09.042.","journal-title":"Eur J Oper Res"},{"key":"4582_CR64","doi-asserted-by":"publisher","first-page":"29204","DOI":"10.1109\/ACCESS.2024.3369177","volume":"12","author":"W You","year":"2024","unstructured":"You W, Xu Z, Zhao S. A two-layer approach for the decentralized multi-project scheduling problem sharing multi-skilled staff. IEEE Access. 2024;12:29204\u201321. https:\/\/doi.org\/10.1109\/ACCESS.2024.3369177.","journal-title":"IEEE Access"},{"issue":"6","key":"4582_CR65","doi-asserted-by":"publisher","first-page":"810","DOI":"10.1006\/jpdc.2000.1714","volume":"61","author":"TD Braun","year":"2001","unstructured":"Braun TD, Siegel HJ, Beck N, B\u00f6l\u00f6ni LL, Maheswaran M, Reuther AI, et al. A comparison of eleven static heuristics for mapping a class of independent tasks onto heterogeneous distributed computing systems. J Parallel Distrib Comput. 2001;61(6):810\u201337. https:\/\/doi.org\/10.1006\/jpdc.2000.1714.","journal-title":"J Parallel Distrib Comput"},{"issue":"3","key":"4582_CR66","doi-asserted-by":"publisher","first-page":"260","DOI":"10.1109\/71.993206","volume":"13","author":"H Topcuoglu","year":"2002","unstructured":"Topcuoglu H, Hariri S, Wu M. Performance-effective and low-complexity task scheduling for heterogeneous computing. IEEE TPDS. 2002;13(3):260\u201374. https:\/\/doi.org\/10.1109\/71.993206.","journal-title":"IEEE TPDS"},{"key":"4582_CR67","doi-asserted-by":"publisher","unstructured":"Ferreira W, Kunstmann L, Paes A, Bedo M, Oliveira D. Ak\u00f4flow: um middleware para execu\u00e7\u00e3o de workflows cient\u00edficos em m\u00faltiplos ambientes conteinerizados. In: Anais do XXXIX Simp\u00f3sio Brasileiro de Bancos de Dados, pp. 27\u201339. SBC, Porto Alegre, RS, Brasil; 2024. https:\/\/doi.org\/10.5753\/sbbd.2024.241126. https:\/\/sol.sbc.org.br\/index.php\/sbbd\/article\/view\/30680.","DOI":"10.5753\/sbbd.2024.241126"},{"key":"4582_CR68","doi-asserted-by":"publisher","unstructured":"Sakellariou R, et al. Mapping workflows on grid resources: Experiments with the montage workflow. In: ERCIM W. Group on Grids; 2009. pp. 119\u2013132. https:\/\/doi.org\/10.1007\/978-1-4419-6794-7_10.","DOI":"10.1007\/978-1-4419-6794-7_10"},{"issue":"7","key":"4582_CR69","doi-asserted-by":"publisher","first-page":"1816","DOI":"10.1016\/J.FUTURE.2012.12.019","volume":"29","author":"D Oliveira","year":"2013","unstructured":"Oliveira D, Oca\u00f1a KACS, Ogasawara ES, Dias J, A. R. Gon\u00e7alves JC, Bai\u00e3o FA, et al. Performance evaluation of parallel strategies in public clouds: a study with phylogenomic workflows. Future Gener Comput Syst. 2013;29(7):1816\u201325. https:\/\/doi.org\/10.1016\/J.FUTURE.2012.12.019.","journal-title":"Future Gener Comput Syst"},{"key":"4582_CR70","volume-title":"Reinforcement learning: an introduction","author":"RS Sutton","year":"1998","unstructured":"Sutton RS, Barto AG. Reinforcement learning: an introduction, vol. 1. Cambridge: MIT press Cambridge; 1998."},{"key":"4582_CR71","doi-asserted-by":"publisher","DOI":"10.1002\/CPE.6193","author":"A Nascimento","year":"2021","unstructured":"Nascimento A, Silva V, Paes A, Oliveira D. An incremental reinforcement learning scheduling strategy for data-intensive scientific workflows in the cloud. Concurr Comput Pract Exp. 2021. https:\/\/doi.org\/10.1002\/CPE.6193.","journal-title":"Concurr Comput Pract Exp"}],"container-title":["SN Computer Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s42979-025-04582-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s42979-025-04582-1","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s42979-025-04582-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T07:25:50Z","timestamp":1768029950000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s42979-025-04582-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,10]]},"references-count":71,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,1]]}},"alternative-id":["4582"],"URL":"https:\/\/doi.org\/10.1007\/s42979-025-04582-1","relation":{},"ISSN":["2661-8907"],"issn-type":[{"value":"2661-8907","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,10]]},"assertion":[{"value":"7 March 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 November 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 January 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"On behalf of all authors, the corresponding author states that there is no Conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This manuscript does not contain any studies with human participants or animals performed by any of the authors.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Research Involving Human and\/or Animals"}},{"value":"Not Applicable.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed Consent"}}],"article-number":"92"}}