{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,17]],"date-time":"2026-08-17T15:34:49Z","timestamp":1786980889374,"version":"build-2736575974"},"reference-count":44,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2022,7,4]],"date-time":"2022-07-04T00:00:00Z","timestamp":1656892800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,7,4]],"date-time":"2022-07-04T00:00:00Z","timestamp":1656892800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100006261","name":"Taif University","doi-asserted-by":"publisher","award":["TURSP-2020\/300"],"award-info":[{"award-number":["TURSP-2020\/300"]}],"id":[{"id":"10.13039\/501100006261","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Cluster Comput"],"published-print":{"date-parts":[[2022,12]]},"DOI":"10.1007\/s10586-022-03650-y","type":"journal-article","created":{"date-parts":[[2022,7,4]],"date-time":"2022-07-04T04:03:12Z","timestamp":1656907392000},"page":"4221-4232","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["Optimized task scheduling in cloud computing using improved multi-verse optimizer"],"prefix":"10.1007","volume":"25","author":[{"given":"Mohammed","family":"Otair","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Areej","family":"Alhmoud","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Heming","family":"Jia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maryam","family":"Altalhi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ahmad MohdAziz","family":"Hussein","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2203-4549","authenticated-orcid":false,"given":"Laith","family":"Abualigah","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,7,4]]},"reference":[{"issue":"9","key":"3650_CR1","doi-asserted-by":"publisher","first-page":"3308","DOI":"10.1007\/s10489-019-01448-x","volume":"49","author":"JPB Mapetu","year":"2019","unstructured":"Mapetu, J.P.B., Chen, Z., Kong, L.: Low-time complexity and low-cost binary particle swarm optimization algorithm for task scheduling and load balancing in cloud computing. Appl. Intell. 49(9), 3308\u20133330 (2019)","journal-title":"Appl. Intell."},{"issue":"1","key":"3650_CR2","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1007\/s10586-020-03075-5","volume":"24","author":"L Abualigah","year":"2021","unstructured":"Abualigah, L., Diabat, A.: A novel hybrid antlion optimization algorithm for multiobjective task scheduling problems in cloud computing environments. Clust. Comput. 24(1), 205\u2013223 (2021)","journal-title":"Clust. Comput."},{"key":"3650_CR3","doi-asserted-by":"publisher","first-page":"114570","DOI":"10.1016\/j.cma.2022.114570","volume":"391","author":"JO Agushaka","year":"2022","unstructured":"Agushaka, J.O., Ezugwu, A.E., Abualigah, L.: Dwarf mongoose optimization algorithm. Comput. Methods Appl. Mech. Eng. 391, 114570 (2022)","journal-title":"Comput. Methods Appl. Mech. Eng."},{"issue":"1","key":"3650_CR4","doi-asserted-by":"publisher","first-page":"2179","DOI":"10.1007\/s10586-018-2515-2","volume":"22","author":"AS Kumar","year":"2019","unstructured":"Kumar, A.S., Venkatesan, M.: Task scheduling in a cloud computing environment using HGPSO algorithm. Clust. Comput. 22(1), 2179\u20132185 (2019)","journal-title":"Clust. Comput."},{"key":"3650_CR5","doi-asserted-by":"publisher","first-page":"16150","DOI":"10.1109\/ACCESS.2022.3147821","volume":"10","author":"ON Oyelade","year":"2022","unstructured":"Oyelade, O.N., et al.: Ebola optimization search algorithm: a new nature-inspired metaheuristic optimization algorithm. IEEE Access 10, 16150\u201316177 (2022)","journal-title":"IEEE Access"},{"issue":"1","key":"3650_CR6","doi-asserted-by":"publisher","first-page":"1087","DOI":"10.1007\/s10586-017-1055-5","volume":"22","author":"K Sreenu","year":"2019","unstructured":"Sreenu, K., Sreelatha, M.: W-Scheduler: whale optimization for task scheduling in cloud computing. Clust. Comput. 22(1), 1087\u20131098 (2019)","journal-title":"Clust. Comput."},{"issue":"3","key":"3650_CR7","doi-asserted-by":"publisher","first-page":"3117","DOI":"10.1109\/JSYST.2019.2960088","volume":"14","author":"X Chen","year":"2020","unstructured":"Chen, X., et al.: A woa-based optimization approach for task scheduling in cloud computing systems. IEEE Syst. J. 14(3), 3117\u20133128 (2020)","journal-title":"IEEE Syst. J."},{"key":"3650_CR8","doi-asserted-by":"publisher","first-page":"113609","DOI":"10.1016\/j.cma.2020.113609","volume":"376","author":"L Abualigah","year":"2021","unstructured":"Abualigah, L., et al.: The arithmetic optimization algorithm. Comput. Methods Appl. Mech. Eng. 376, 113609 (2021)","journal-title":"Comput. Methods Appl. Mech. Eng."},{"key":"3650_CR9","doi-asserted-by":"publisher","first-page":"107250","DOI":"10.1016\/j.cie.2021.107250","volume":"157","author":"L Abualigah","year":"2021","unstructured":"Abualigah, L., et al.: Aquila optimizer: a novel meta-heuristic optimization Algorithm. Comput. Ind. Eng. 157, 107250 (2021)","journal-title":"Comput. Ind. Eng."},{"key":"3650_CR10","doi-asserted-by":"publisher","first-page":"116158","DOI":"10.1016\/j.eswa.2021.116158","volume":"191","author":"L Abualigah","year":"2022","unstructured":"Abualigah, L., et al.: Reptile Search Algorithm (RSA): a nature-inspired meta-heuristic optimizer. Expert Syst. Appl. 191, 116158 (2022)","journal-title":"Expert Syst. Appl."},{"key":"3650_CR11","doi-asserted-by":"publisher","first-page":"8103","DOI":"10.1007\/s00521-022-06899-x","volume":"34","author":"MS Turgut","year":"2022","unstructured":"Turgut, M.S., Turgut, O.E., Abualigah, L.: Chaotic quasi-oppositional arithmetic optimization algorithm for thermo-economic design of a shell and tube condenser running with different refrigerant mixture pairs. Neural Comput. Appl. 34, 8103\u20138135 (2022)","journal-title":"Neural Comput. Appl."},{"key":"3650_CR12","doi-asserted-by":"publisher","DOI":"10.1007\/s11831-021-09693-5","author":"B Alsalibi","year":"2022","unstructured":"Alsalibi, B., et al.: A comprehensive survey on the recent variants and applications of membrane-inspired evolutionary algorithms. Arch. Comput. Methods Eng. (2022). https:\/\/doi.org\/10.1007\/s11831-021-09693-5","journal-title":"Arch. Comput. Methods Eng."},{"key":"3650_CR13","doi-asserted-by":"publisher","first-page":"728","DOI":"10.1016\/j.asoc.2018.07.033","volume":"71","author":"H Shayanfar","year":"2018","unstructured":"Shayanfar, H., Gharehchopogh, F.S.: Farmland fertility: a new metaheuristic algorithm for solving continuous optimization problems. Appl. Soft Comput. 71, 728\u2013746 (2018)","journal-title":"Appl. Soft Comput."},{"issue":"1","key":"3650_CR14","doi-asserted-by":"publisher","first-page":"473","DOI":"10.3934\/mbe.2022023","volume":"19","author":"R Zheng","year":"2022","unstructured":"Zheng, R., et al.: An improved arithmetic optimization algorithm with forced switching mechanism for global optimization problems. Math. Biosci. Eng. 19(1), 473\u2013512 (2022)","journal-title":"Math. Biosci. Eng."},{"issue":"8","key":"3650_CR15","doi-asserted-by":"publisher","first-page":"4385","DOI":"10.1007\/s00521-018-3343-2","volume":"31","author":"S Arora","year":"2019","unstructured":"Arora, S., Anand, P.: Chaotic grasshopper optimization algorithm for global optimization. Neural Comput. Appl. 31(8), 4385\u20134405 (2019)","journal-title":"Neural Comput. Appl."},{"key":"3650_CR16","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2021\/9114113","volume":"2021","author":"M Abd Elaziz","year":"2021","unstructured":"Abd Elaziz, M., et al.: IoT workflow scheduling using intelligent arithmetic optimization algorithm in fog computing. Comput. Intell. Neurosci. 2021, 1\u201314 (2021)","journal-title":"Comput. Intell. Neurosci."},{"key":"3650_CR17","doi-asserted-by":"publisher","DOI":"10.1007\/s12652-021-03602-1","author":"RA Zitar","year":"2021","unstructured":"Zitar, R.A., Abualigah, L., Al-Dmour, N.A.: Review and analysis for the Red Deer Algorithm. J. Ambient Intell. Hum. Comput. (2021). https:\/\/doi.org\/10.1007\/s12652-021-03602-1","journal-title":"J. Ambient Intell. Hum. Comput."},{"issue":"3","key":"3650_CR18","doi-asserted-by":"publisher","first-page":"195","DOI":"10.1007\/s40747-018-0066-z","volume":"4","author":"GI Sayed","year":"2018","unstructured":"Sayed, G.I., Hassanien, A.E.: A hybrid SA-MFO algorithm for function optimization and engineering design problems. Complex Intell. Syst. 4(3), 195\u2013212 (2018)","journal-title":"Complex Intell. Syst."},{"key":"3650_CR19","doi-asserted-by":"publisher","first-page":"818","DOI":"10.1016\/j.engappai.2019.08.009","volume":"85","author":"MG Omran","year":"2019","unstructured":"Omran, M.G., Al-Sharhan, S.: Improved continuous Ant Colony Optimization algorithms for real-world engineering optimization problems. Eng. Appl. Artif. Intell. 85, 818\u2013829 (2019)","journal-title":"Eng. Appl. Artif. Intell."},{"issue":"1","key":"3650_CR20","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s12046-019-1258-y","volume":"45","author":"MB Patil","year":"2020","unstructured":"Patil, M.B., et al.: Water distribution system design using multiobjective particle swarm optimisation. S\u0101dhan\u0101 45(1), 1\u201315 (2020)","journal-title":"S\u0101dhan\u0101"},{"key":"3650_CR21","doi-asserted-by":"publisher","first-page":"25532","DOI":"10.1109\/JSEN.2021.3114266","volume":"31","author":"L Abualigah","year":"2021","unstructured":"Abualigah, L., et al.: Applications, deployments, and integration of internet of drones (iod): a review. IEEE Sens. J. 31, 25532\u201325546 (2021)","journal-title":"IEEE Sens. J."},{"key":"3650_CR22","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1016\/j.comcom.2016.12.010","volume":"102","author":"E Baccarelli","year":"2017","unstructured":"Baccarelli, E., et al.: Q*: Energy and delay-efficient dynamic queue management in TCP\/IP virtualized data centers. Comput. Commun. 102, 89\u2013106 (2017)","journal-title":"Comput. Commun."},{"issue":"4","key":"3650_CR23","doi-asserted-by":"publisher","first-page":"1797","DOI":"10.1007\/s10586-018-2811-x","volume":"21","author":"HB Alla","year":"2018","unstructured":"Alla, H.B., et al.: A novel task scheduling approach based on dynamic queues and hybrid meta-heuristic algorithms for cloud computing environment. Clust. Comput. 21(4), 1797\u20131820 (2018)","journal-title":"Clust. Comput."},{"key":"3650_CR24","first-page":"1","volume":"2021","author":"M Abd Elaziz","year":"2021","unstructured":"Abd Elaziz, M., Abualigah, L., Attiya, I.: Advanced optimization technique for scheduling IoT tasks in cloud-fog computing environments. Future Gener. Comput. Syst. 2021, 1\u201314 (2021)","journal-title":"Future Gener. Comput. Syst."},{"key":"3650_CR25","first-page":"1","volume":"2021","author":"L Abualigah","year":"2021","unstructured":"Abualigah, L., Diabat, A., Abd Elaziz, M.: Intelligent workflow scheduling for Big Data applications in IoT cloud computing environments. Cluster Comput. 2021, 1\u201320 (2021)","journal-title":"Cluster Comput."},{"key":"3650_CR26","doi-asserted-by":"publisher","first-page":"407","DOI":"10.1016\/j.future.2018.09.014","volume":"91","author":"A Arunarani","year":"2019","unstructured":"Arunarani, A., Manjula, D., Sugumaran, V.: Task scheduling techniques in cloud computing: a literature survey. Futur. Gener. Comput. Syst. 91, 407\u2013415 (2019)","journal-title":"Futur. Gener. Comput. Syst."},{"key":"3650_CR27","doi-asserted-by":"publisher","first-page":"114230","DOI":"10.1016\/j.eswa.2020.114230","volume":"168","author":"SE Shukri","year":"2021","unstructured":"Shukri, S.E., et al.: Enhanced multiverse optimizer for task scheduling in cloud computing environments. Expert Syst. Appl. 168, 114230 (2021)","journal-title":"Expert Syst. Appl."},{"key":"3650_CR28","first-page":"102853","volume":"60","author":"S Javanmardi","year":"2021","unstructured":"Javanmardi, S., et al.: FUPE: a security driven task scheduling approach for SDN-based IoT\u2013Fog networks. J. Inf. Secur. Appl. 60, 102853 (2021)","journal-title":"J. Inf. Secur. Appl."},{"issue":"4","key":"3650_CR29","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3418501","volume":"21","author":"F Hoseiny","year":"2021","unstructured":"Hoseiny, F., et al.: Joint QoS-aware and cost-efficient task scheduling for fog-cloud resources in a volunteer computing system. ACM Trans. Internet Technol. (TOIT) 21(4), 1\u201321 (2021)","journal-title":"ACM Trans. Internet Technol. (TOIT)"},{"key":"3650_CR30","doi-asserted-by":"publisher","first-page":"103333","DOI":"10.1016\/j.jnca.2022.103333","volume":"201","author":"S Azizi","year":"2022","unstructured":"Azizi, S., et al.: Deadline-aware and energy-efficient IoT task scheduling in fog computing systems: a semi-greedy approach. J. Netw. Comput. Appl. 201, 103333 (2022)","journal-title":"J. Netw. Comput. Appl."},{"key":"3650_CR31","unstructured":"Coello, C.C., Lechuga, M.S.: MOPSO: a proposal for multiple objective particle swarm optimization. In: Proceedings of the 2002 Congress on Evolutionary Computation. CEC\u201902 (Cat. No. 02TH8600). IEEE (2002)"},{"key":"3650_CR32","volume-title":"International Conference on Service-oriented computing","author":"F Ramezani","year":"2013","unstructured":"Ramezani, F., Lu, J., Hussain, F.: Task scheduling optimization in cloud computing applying multiobjective particle swarm optimization. In: International Conference on Service-oriented computing. Springer, Berlin (2013)"},{"key":"3650_CR33","volume-title":"International Conference on Intelligent Computing","author":"Y Liu","year":"2013","unstructured":"Liu, Y., Niu, B.: A multiobjective particle swarm optimization based on decomposition. In: International Conference on Intelligent Computing. Springer, Berlin (2013)"},{"issue":"5","key":"3650_CR34","doi-asserted-by":"publisher","first-page":"11975","DOI":"10.1007\/s10586-017-1534-8","volume":"22","author":"R Valarmathi","year":"2019","unstructured":"Valarmathi, R., Sheela, T.: Ranging and tuning based particle swarm optimization with bat algorithm for task scheduling in cloud computing. Clust. Comput. 22(5), 11975\u201311988 (2019)","journal-title":"Clust. Comput."},{"key":"3650_CR35","doi-asserted-by":"crossref","unstructured":"Wu, D.: Cloud computing task scheduling policy based on improved particle swarm optimization. In: 2018 International Conference on Virtual Reality and Intelligent Systems (ICVRIS). IEEE (2018)","DOI":"10.1109\/ICVRIS.2018.00032"},{"key":"3650_CR36","doi-asserted-by":"crossref","unstructured":"Li, J., et al.: Task scheduling algorithm for heterogeneous real-time systems based on deadline constraints. In: 2019 IEEE 9th International Conference on Electronics Information and Emergency Communication (ICEIEC). IEEE (2019)","DOI":"10.1109\/ICEIEC.2019.8784641"},{"key":"3650_CR37","doi-asserted-by":"crossref","unstructured":"Cui, D., et al.: Cloud workflow task and virtualized resource collaborative adaptive scheduling algorithm based on distributed deep learning. In: 2020 IEEE International Conference on Advances in Electrical Engineering and Computer Applications (AEECA). IEEE (2020)","DOI":"10.1109\/AEECA49918.2020.9213622"},{"issue":"3","key":"3650_CR38","doi-asserted-by":"crossref","first-page":"e12124","DOI":"10.1002\/eng2.12124","volume":"2","author":"I Benmessahel","year":"2020","unstructured":"Benmessahel, I., Xie, K., Chellal, M.: A new competitive multiverse optimization technique for solving single-objective and multiobjective problems. Eng. Rep. 2(3), e12124 (2020)","journal-title":"Eng. Rep."},{"key":"3650_CR39","doi-asserted-by":"crossref","unstructured":"Jui, J.J., Ahmad, M.A., Rashid, M.I.M.: Modified multi-verse optimizer for solving numerical optimization problems. In: 2020 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS). IEEE (2020)","DOI":"10.1109\/I2CACIS49202.2020.9140097"},{"issue":"4","key":"3650_CR40","doi-asserted-by":"publisher","first-page":"2453","DOI":"10.1007\/s10586-019-03018-9","volume":"23","author":"A Souri","year":"2020","unstructured":"Souri, A., et al.: A hybrid formal verification approach for QoS-aware multi-cloud service composition. Clust. Comput. 23(4), 2453\u20132470 (2020)","journal-title":"Clust. Comput."},{"key":"3650_CR41","doi-asserted-by":"publisher","first-page":"102090","DOI":"10.1016\/j.simpat.2020.102090","volume":"103","author":"M Yaghoubi","year":"2020","unstructured":"Yaghoubi, M., Maroosi, A.: Simulation and modeling of an improved multiverse optimization algorithm for QoS-aware web service composition with service level agreements in the cloud environments. Simul. Model. Pract. Theory 103, 102090 (2020)","journal-title":"Simul. Model. Pract. Theory"},{"issue":"2","key":"3650_CR42","doi-asserted-by":"crossref","first-page":"e3770","DOI":"10.1002\/ett.3770","volume":"31","author":"M Ghobaei-Arani","year":"2020","unstructured":"Ghobaei-Arani, M., et al.: An efficient task scheduling approach using moth-flame optimization algorithm for cyber-physical system applications in fog computing. Trans. Emerg. Telecommun. Technol. 31(2), e3770 (2020)","journal-title":"Trans. Emerg. Telecommun. Technol."},{"issue":"2","key":"3650_CR43","doi-asserted-by":"publisher","first-page":"495","DOI":"10.1007\/s00521-015-1870-7","volume":"27","author":"S Mirjalili","year":"2016","unstructured":"Mirjalili, S., Mirjalili, S.M., Hatamlou, A.: Multiverse optimizer: a nature-inspired algorithm for global optimization. Neural Comput. Appl. 27(2), 495\u2013513 (2016)","journal-title":"Neural Comput. Appl."},{"issue":"1","key":"3650_CR44","doi-asserted-by":"publisher","first-page":"740","DOI":"10.1007\/s11227-021-03915-0","volume":"78","author":"L Abualigah","year":"2022","unstructured":"Abualigah, L., Alkhrabsheh, M.: Amended hybrid multiverse optimizer with genetic algorithm for solving task scheduling problem in cloud computing. J. Supercomput. 78(1), 740\u2013765 (2022)","journal-title":"J. Supercomput."}],"container-title":["Cluster Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-022-03650-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10586-022-03650-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-022-03650-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,23]],"date-time":"2023-11-23T22:58:44Z","timestamp":1700780324000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10586-022-03650-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,4]]},"references-count":44,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2022,12]]}},"alternative-id":["3650"],"URL":"https:\/\/doi.org\/10.1007\/s10586-022-03650-y","relation":{},"ISSN":["1386-7857","1573-7543"],"issn-type":[{"value":"1386-7857","type":"print"},{"value":"1573-7543","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,7,4]]},"assertion":[{"value":"13 February 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 June 2022","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 June 2022","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 July 2022","order":4,"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 that there is no conflict of interest regarding the publication of this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This article does not contain any studies with human participants or animals performed by any of the authors.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"Informed consent was obtained from all individual participants included in the study.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}}]}}