{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T15:39:35Z","timestamp":1780673975271,"version":"3.54.1"},"reference-count":41,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2021,7,7]],"date-time":"2021-07-07T00:00:00Z","timestamp":1625616000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,7,7]],"date-time":"2021-07-07T00:00:00Z","timestamp":1625616000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Supercomput"],"published-print":{"date-parts":[[2022,2]]},"DOI":"10.1007\/s11227-021-03977-0","type":"journal-article","created":{"date-parts":[[2021,7,7]],"date-time":"2021-07-07T09:19:55Z","timestamp":1625649595000},"page":"2793-2818","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":68,"title":["Elite learning Harris hawks optimizer for multi-objective task scheduling in cloud computing"],"prefix":"10.1007","volume":"78","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3954-9941","authenticated-orcid":false,"given":"Dina A.","family":"Amer","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gamal","family":"Attiya","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ibrahim","family":"Zeidan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aida A.","family":"Nasr","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2021,7,7]]},"reference":[{"key":"3977_CR1","volume-title":"Cloud computing: paradigms and technologies","author":"SMA Shawish","year":"2014","unstructured":"Shawish SMA (2014) Cloud computing: paradigms and technologies. Springer-Verlag, Berlin Heidelberg"},{"key":"3977_CR2","volume-title":"Business in the cloud: whatever business needs to know about cloud computing","author":"HDM Hugos","year":"2011","unstructured":"Hugos HDM (2011) Business in the cloud: whatever business needs to know about cloud computing. John Wiley Sons Inc, Hoboken"},{"key":"3977_CR3","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.jss.2015.11.023","volume":"113","author":"RMP Alkhanak","year":"2016","unstructured":"Alkhanak RMP, Nabiel E, Lee SP, Rezaei R (2016) \u2018Cost optimization approaches for scientific workflow scheduling in cloud and grid computing: a review, classifications, and open issues.\u2019 J Syst Softw 113:1\u201326","journal-title":"J Syst Softw"},{"key":"3977_CR4","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1016\/j.cosrev.2018.08.002","volume":"30","author":"LF Bittencourt","year":"2018","unstructured":"Bittencourt LF, Goldman A, Madeira ERM, Da Fonseca NLS, Sakellariou R (2018) Scheduling in distributed systems: A cloud computing perspective. Comput Sci Rev 30:31\u201354. https:\/\/doi.org\/10.1016\/j.cosrev.2018.08.002","journal-title":"Comput Sci Rev"},{"key":"3977_CR5","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1016\/j.jnca.2019.02.005","volume":"133","author":"SMM Abdullahi","year":"2019","unstructured":"Abdullahi SMM, Ngadi MA, Dishing SI, Abdulhamid BIA (2019) An efficient symbiotic organisms search algorithm with chaotic optimization strategy for multi-objective task scheduling problems in cloud computing environment. J Netw Comput Appl 133:60\u20137","journal-title":"J Netw Comput Appl"},{"key":"3977_CR6","unstructured":"EG T (2009) Metaheuristics: from Design to Implementation. Wiley"},{"issue":"March","key":"3977_CR7","doi-asserted-by":"publisher","first-page":"849","DOI":"10.1016\/j.future.2019.02.028","volume":"97","author":"AA Heidari","year":"2019","unstructured":"Heidari AA, Mirjalili S, Faris H, Aljarah I, Mafarja M, Chen H (2019) Harris hawks optimization: algorithm and applications. Futur Gener Comput Syst 97(March):849\u2013872. https:\/\/doi.org\/10.1016\/j.future.2019.02.028","journal-title":"Futur Gener Comput Syst"},{"key":"3977_CR8","doi-asserted-by":"publisher","first-page":"76529","DOI":"10.1109\/ACCESS.2019.2921545","volume":"7","author":"X Bao","year":"2019","unstructured":"Bao X, Jia H, Lang C (2019) A novel hybrid Harris hawks optimization for color image multilevel thresholding segmentation. IEEE Access 7:76529\u201376546. https:\/\/doi.org\/10.1109\/ACCESS.2019.2921545","journal-title":"IEEE Access"},{"key":"3977_CR9","doi-asserted-by":"publisher","DOI":"10.1016\/j.segan.2020.100352","author":"D Yousri","year":"2009","unstructured":"Yousri D, Babu TS, Fathy A (2009) Recent methodology based Harris Hawks optimizer for designing load frequency control incorporated in multi-interconnected renewable energy plants. Sustain Energy, Grids Netw. https:\/\/doi.org\/10.1016\/j.segan.2020.100352","journal-title":"Sustain Energy, Grids Netw"},{"issue":"10","key":"3977_CR10","doi-asserted-by":"publisher","first-page":"1","DOI":"10.3390\/electronics8101130","volume":"8","author":"J Too","year":"2019","unstructured":"Too J, Abdullah AR, Saad NM (2019) A new quadratic binary harris hawk optimization for feature selection. Electron 8(10):1\u201327. https:\/\/doi.org\/10.3390\/electronics8101130","journal-title":"Electron"},{"key":"3977_CR11","doi-asserted-by":"publisher","first-page":"118778","DOI":"10.1016\/j.jclepro.2019.118778","volume":"244","author":"XZH Chen","year":"2020","unstructured":"Chen XZH, Jiao S, Wang M, Heidari AA (2020) Parameters identification of photovoltaic cells and modules using diversification-enriched harris hawks optimization with chaotic drifts. J Clean Prod 244:118778","journal-title":"J Clean Prod"},{"key":"3977_CR12","doi-asserted-by":"publisher","unstructured":"Tizhoosh HR (2005) \u201cOpposition-based learning: a new scheme for machine intelligence,\u201d Proc Int Conf Comput Intell Model Control Autom CIMCA 2005 Int Conf Intell Agents, Web Technol Internet 1: 695\u2013701, https:\/\/doi.org\/10.1109\/cimca.2005.1631345.","DOI":"10.1109\/cimca.2005.1631345"},{"key":"3977_CR13","first-page":"836","volume":"2015","author":"W Yizhen","year":"2016","unstructured":"Yizhen W, Yongqiang S, Yi S (2016) \u201cTask scheduling algorithm in cloud computing based on fairness load balance and minimum completion time\u201d, no. Nceece 2015:836\u2013842","journal-title":"Nceece"},{"issue":"3","key":"3977_CR14","doi-asserted-by":"publisher","first-page":"275","DOI":"10.1016\/j.eij.2015.07.001","volume":"16","author":"M Kalra","year":"2015","unstructured":"Kalra M, Singh S (2015) A review of metaheuristic scheduling techniques in cloud computing. Egypt Inform J 16(3):275\u2013295. https:\/\/doi.org\/10.1016\/j.eij.2015.07.001","journal-title":"Egypt Inform J"},{"issue":"8","key":"3977_CR15","doi-asserted-by":"publisher","first-page":"6302","DOI":"10.1007\/s11227-019-02816-7","volume":"76","author":"SMG Kashikolaei","year":"2020","unstructured":"Kashikolaei SMG, Hosseinabadi AAR, Saemi B, Shareh MB, Sangaiah AK, Bian GB (2020) An enhancement of task scheduling in cloud computing based on imperialist competitive algorithm and firefly algorithm. J Supercomput 76(8):6302\u20136329. https:\/\/doi.org\/10.1007\/s11227-019-02816-7","journal-title":"J Supercomput"},{"key":"3977_CR16","doi-asserted-by":"publisher","first-page":"1219","DOI":"10.1016\/j.procs.2015.07.419","volume":"57","author":"RK Jena","year":"2015","unstructured":"Jena RK (2015) Multi objective task scheduling in cloud environment using nested PSO framework. Procedia Comput Sci 57:1219\u20131227. https:\/\/doi.org\/10.1016\/j.procs.2015.07.419","journal-title":"Procedia Comput Sci"},{"key":"3977_CR17","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1016\/j.procs.2015.04.158","volume":"48","author":"AV Lakra","year":"2015","unstructured":"Lakra AV, Yadav DK (2015) Multi-objective tasks scheduling algorithm for cloud computing throughput optimization. Procedia Comput Sci 48:107\u2013113. https:\/\/doi.org\/10.1016\/j.procs.2015.04.158","journal-title":"Procedia Comput Sci"},{"issue":"11","key":"3977_CR18","doi-asserted-by":"publisher","first-page":"6821","DOI":"10.1007\/s00521-019-04091-2","volume":"32","author":"AA Nasr","year":"2020","unstructured":"Nasr AA, Dubey K, El-Bahnasawy NA, Sharma SC, Attiya G, El-Sayed A (2020) HPFE: a new secure framework for serving multi-users with multi-tasks in public cloud without violating SLA. Neural Comput Appl 32(11):6821\u20136841. https:\/\/doi.org\/10.1007\/s00521-019-04091-2","journal-title":"Neural Comput Appl"},{"issue":"5","key":"3977_CR19","doi-asserted-by":"publisher","first-page":"384","DOI":"10.14569\/IJACSA.2018.090550","volume":"9","author":"BH Malik","year":"2018","unstructured":"Malik BH, Amir M, Mazhar B, Ali S, Jalil R, Khalid J (2018) Comparison of task scheduling algorithms in cloud environment. Int J Adv Comput Sci Appl 9(5):384\u2013390. https:\/\/doi.org\/10.14569\/IJACSA.2018.090550","journal-title":"Int J Adv Comput Sci Appl"},{"issue":"June","key":"3977_CR20","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 SC, Goel A, Singh SP (2019) A comprehensive survey for scheduling techniques in cloud computing. J Netw Comput Appl 143(June):1\u201333. https:\/\/doi.org\/10.1016\/j.jnca.2019.06.006","journal-title":"J Netw Comput Appl"},{"issue":"6","key":"3977_CR21","doi-asserted-by":"publisher","first-page":"403","DOI":"10.14257\/ijhit.2016.9.6.36","volume":"9","author":"X Liu","year":"2016","unstructured":"Liu X, Liu J (2016) A task scheduling based on simulated annealing algorithm in cloud computing. Int J Hybrid Inf Technol 9(6):403\u2013412. https:\/\/doi.org\/10.14257\/ijhit.2016.9.6.36","journal-title":"Int J Hybrid Inf Technol"},{"issue":"5","key":"3977_CR22","doi-asserted-by":"publisher","first-page":"1371","DOI":"10.3966\/160792642019092005005","volume":"20","author":"AA Nasr","year":"2019","unstructured":"Nasr AA, El-Bahnasawy NA, Attiya G, El-Sayed A (2019) Cloudlet scheduling based load balancing on virtual machines in cloud computing environment. J Internet Technol 20(5):1371\u20131378. https:\/\/doi.org\/10.3966\/160792642019092005005","journal-title":"J Internet Technol"},{"key":"3977_CR23","doi-asserted-by":"publisher","DOI":"10.1155\/2020\/3504642","author":"I Attiya","year":"2020","unstructured":"Attiya I, Elaziz MA, Xiong S (2020) Job scheduling in cloud computing using a modified harris hawks optimization and simulated annealing algorithm. Comput Intell Neurosci. https:\/\/doi.org\/10.1155\/2020\/3504642","journal-title":"Comput Intell Neurosci"},{"issue":"01","key":"3977_CR24","doi-asserted-by":"publisher","first-page":"1","DOI":"10.4236\/jsea.2013.61001","volume":"06","author":"Y Yang","year":"2013","unstructured":"Yang Y, Zhou Y, Sun Z, Cruickshank H (2013) Heuristic scheduling algorithms for allocation of virtualized network and computing resources. J Softw Eng Appl 06(01):1\u201313. https:\/\/doi.org\/10.4236\/jsea.2013.61001","journal-title":"J Softw Eng Appl"},{"key":"3977_CR25","doi-asserted-by":"publisher","first-page":"2687","DOI":"10.1109\/ACCESS.2015.2508940","volume":"3","author":"L Zuo","year":"2015","unstructured":"Zuo L, Shu L, Dong S, Zhu C, Hara T (2015) A multi-objective optimization scheduling method based on the ant colony algorithm in cloud computing. IEEE Access 3:2687\u20132699. https:\/\/doi.org\/10.1109\/ACCESS.2015.2508940","journal-title":"IEEE Access"},{"issue":"4","key":"3977_CR26","first-page":"550","volume":"7","author":"SA Hamad","year":"2016","unstructured":"Hamad SA, Omara FA (2016) Genetic-based task scheduling algorithm in cloud computing environment. Int J Adv Comput Sci Appl 7(4):550\u2013556","journal-title":"Int J Adv Comput Sci Appl"},{"issue":"4","key":"3977_CR27","first-page":"54","volume":"19","author":"HM El-Boghdadi","year":"2019","unstructured":"El-Boghdadi HM, Ramadan RA (2019) Resource scheduling for offline cloud computing using deep reinforcement learning. Int J Comput Sci Netw Secur 19(4):54\u201360","journal-title":"Int J Comput Sci Netw Secur"},{"key":"3977_CR28","first-page":"149","volume":"32","author":"BSPP Parida","year":"2018","unstructured":"Parida BSPP, Mishra SK (2018) Load balancing in cloud computing: a big picture. J King Saud Univ:Comput Inf Sci 32:149\u2013158","journal-title":"J King Saud Univ:Comput Inf Sci"},{"key":"3977_CR29","doi-asserted-by":"publisher","DOI":"10.3390\/jsan8030044","author":"I Strumberger","year":"2019","unstructured":"Strumberger I, Tuba M, Bacanin N, Tuba E (2019) Cloudlet scheduling by hybridized monarch butterfly optimization algorithm. J Sens Actuator Netw. https:\/\/doi.org\/10.3390\/jsan8030044","journal-title":"J Sens Actuator Netw"},{"issue":"3","key":"3977_CR30","doi-asserted-by":"publisher","first-page":"384","DOI":"10.1016\/S0022-0000(75)80008-0","volume":"10","author":"JD Ullman","year":"1975","unstructured":"Ullman JD (1975) NP-complete scheduling problems. J Comput Syst Sci 10(3):384\u2013393. https:\/\/doi.org\/10.1016\/S0022-0000(75)80008-0","journal-title":"J Comput Syst Sci"},{"issue":"3","key":"3977_CR31","doi-asserted-by":"publisher","first-page":"567","DOI":"10.1007\/s10922-014-9307-7","volume":"23","author":"R Stadler","year":"2015","unstructured":"Stadler R, Jennings B (2015) Resource management in clouds: survey challenges, and research. J Netw Sys Manag 23(3):567\u2013619","journal-title":"J Netw Sys Manag"},{"key":"3977_CR32","doi-asserted-by":"publisher","first-page":"66","DOI":"10.4028\/www.scientific.net\/AMR.490-495.66","volume":"490\u2013495","author":"Y Nan","year":"2012","unstructured":"Nan Y (2012) An improved ant colony optimization algorithm based on immunization strategy. Adv Mater Res 490\u2013495:66\u201370https:\/\/doi.org\/10.4028\/www.scientific.net\/AMR.490-495.66","journal-title":"Adv Mater Res"},{"issue":"20","key":"3977_CR33","doi-asserted-by":"publisher","first-page":"4699","DOI":"10.1016\/j.ins.2011.03.016","volume":"181","author":"H Wang","year":"2011","unstructured":"Wang H, Wu Z, Rahnamayan S, Liu Y, Ventresca M (2011) Enhancing particle swarm optimization using generalized opposition-based learning. Inf Sci (Ny) 181(20):4699\u20134714. https:\/\/doi.org\/10.1016\/j.ins.2011.03.016","journal-title":"Inf Sci (Ny)"},{"issue":"5","key":"3977_CR34","doi-asserted-by":"publisher","first-page":"e0176321","DOI":"10.1371\/journal.pone.0176321","volume":"12","author":"S Hamid","year":"2017","unstructured":"Hamid S et al (2017) Performance comparison of heuristic algorithms for task scheduling in IaaS cloud computing environment. PLoS ONE 12(5):e0176321","journal-title":"PLoS ONE"},{"issue":"1","key":"3977_CR35","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, De Rose CAF, Buyya R (2011) CloudSim: a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms. Softw Pract Exp 41(1):23\u201350. https:\/\/doi.org\/10.1002\/spe.995","journal-title":"Softw Pract Exp"},{"issue":"10","key":"3977_CR36","doi-asserted-by":"publisher","first-page":"2967","DOI":"10.1016\/j.jpdc.2014.06.013","volume":"74","author":"DK Dror","year":"2014","unstructured":"Dror DK, Feitelson G, Tsafrir D (2014) Experience with using the parallel workloads archive. J Parallel Dist Comput 74(10):2967\u20132982","journal-title":"J Parallel Dist Comput"},{"key":"3977_CR37","doi-asserted-by":"publisher","DOI":"10.1287\/moor.2019.1036","author":"K Jansen","year":"2020","unstructured":"Jansen K, Klein K-M, Verschae J (2020) Closing the gap for makespan scheduling via sparsification techniques. Math Oper Res. https:\/\/doi.org\/10.1287\/moor.2019.1036","journal-title":"Math Oper Res"},{"key":"3977_CR38","doi-asserted-by":"publisher","DOI":"10.1007\/s10586-020-03075-5","author":"L Abualigah","year":"2020","unstructured":"Abualigah L, Diabat A (2020) A novel hybrid antlion optimization algorithm for multi-objective task scheduling problems in cloud computing environments. Clust Comput. https:\/\/doi.org\/10.1007\/s10586-020-03075-5","journal-title":"Clust Comput"},{"key":"3977_CR39","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1016\/j.procs.2015.04.158","volume":"48","author":"AV Lakra","year":"2015","unstructured":"Lakra AV, Yadav DK (2015) Multi-objective tasks scheduling algorithm for cloud computing throughput optimization. Procedia Comput Sci 48:107\u2013113","journal-title":"Procedia Comput Sci"},{"issue":"4","key":"3977_CR40","first-page":"276","volume":"14","author":"M Kuma","year":"2018","unstructured":"Kuma M, Sharma SC (2018) Load balancing algorithm to minimize the makespan time in cloud environment. World J Model Simul 14(4):276\u2013288","journal-title":"World J Model Simul"},{"issue":"2","key":"3977_CR41","doi-asserted-by":"publisher","first-page":"601","DOI":"10.1007\/s10586-018-2867-7","volume":"22","author":"AA Nasr","year":"2018","unstructured":"Nasr AA, Chronopoulos AT, El-Bahnasawy NA, Attiyam G (2018) A novel water pressure change optimization technique for solving scheduling problem in cloud computing. J Clust Comput 22(2):601\u2013617","journal-title":"J Clust Comput"}],"container-title":["The Journal of Supercomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-021-03977-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11227-021-03977-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-021-03977-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,1,24]],"date-time":"2022-01-24T11:32:07Z","timestamp":1643023927000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11227-021-03977-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,7]]},"references-count":41,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2022,2]]}},"alternative-id":["3977"],"URL":"https:\/\/doi.org\/10.1007\/s11227-021-03977-0","relation":{},"ISSN":["0920-8542","1573-0484"],"issn-type":[{"value":"0920-8542","type":"print"},{"value":"1573-0484","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,7,7]]},"assertion":[{"value":"25 June 2021","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 July 2021","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}