{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T19:15:15Z","timestamp":1769886915465,"version":"3.49.0"},"reference-count":42,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Computing"],"published-print":{"date-parts":[[2026,1]]},"DOI":"10.1007\/s00607-025-01614-9","type":"journal-article","created":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T07:00:55Z","timestamp":1768287655000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["FSMA: a Fuzzy-enhanced SMA for enhanced multi-objective task scheduling in IoT cloud-edge systems"],"prefix":"10.1007","volume":"108","author":[{"given":"Hossein Azadi","family":"Kheirabadi","sequence":"first","affiliation":[]},{"given":"Pedram","family":"Salehpour","sequence":"additional","affiliation":[]},{"given":"Sepehr Ebrahimi","family":"Mood","sequence":"additional","affiliation":[]},{"given":"Alireza","family":"Souri","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,1,13]]},"reference":[{"issue":"1","key":"1614_CR1","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1007\/s00607-024-01352-4","volume":"107","author":"TE Ali","year":"2025","unstructured":"Ali TE et al (2025) Trends, prospects, challenges, and security in the healthcare internet of things. Computing 107(1):28","journal-title":"Computing"},{"key":"1614_CR2","unstructured":"Tyagi AK et al (2025) Applications and Use Cases of 6G Technology."},{"issue":"7","key":"1614_CR3","doi-asserted-by":"publisher","first-page":"2107","DOI":"10.1007\/s00607-023-01199-1","volume":"106","author":"F Faraji","year":"2024","unstructured":"Faraji F et al (2024) A solution for resource allocation through complex systems in fog computing for the internet of things. Computing 106(7):2107\u20132131","journal-title":"Computing"},{"issue":"5","key":"1614_CR4","doi-asserted-by":"publisher","first-page":"4037","DOI":"10.1007\/s00500-023-09381-5","volume":"28","author":"F BahraniPour","year":"2024","unstructured":"BahraniPour F, Ebrahimi S, Mood, Farshi M (2024) Energy-delay aware request scheduling in hybrid cloud and fog computing using improved multi-objective CS algorithm. Soft Comput 28(5):4037\u20134050","journal-title":"Soft Comput"},{"issue":"1","key":"1614_CR5","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1007\/s00607-024-01388-6","volume":"107","author":"H Larian","year":"2025","unstructured":"Larian H, Safi-Esfahani F (2025) InTec: integrated things-edge computing: a framework for distributing machine learning pipelines in edge AI systems. Computing 107(1):41","journal-title":"Computing"},{"issue":"3","key":"1614_CR6","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1007\/s10723-024-09776-0","volume":"22","author":"A Narwal","year":"2024","unstructured":"Narwal A (2024) Resource utilization based on hybrid WOA-LOA optimization with credit based resource aware load balancing and scheduling algorithm for cloud computing. J Grid Comput 22(3):61","journal-title":"J Grid Comput"},{"issue":"2","key":"1614_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10586-024-04878-6","volume":"28","author":"A Satouf","year":"2025","unstructured":"Satouf A et al (2025) Metaheuristic-based task scheduling for latency-sensitive IoT applications in edge computing. Cluster Comput 28(2):1\u201317","journal-title":"Cluster Comput"},{"issue":"22","key":"1614_CR8","doi-asserted-by":"publisher","first-page":"15557","DOI":"10.1007\/s00521-021-06178-1","volume":"33","author":"S Ebrahimi Mood","year":"2021","unstructured":"Ebrahimi Mood S et al (2021) Performance optimization of UAV-based IoT communications using a novel constrained gravitational search algorithm. Neural Comput Appl 33(22):15557\u201315568","journal-title":"Neural Comput Appl"},{"issue":"9","key":"1614_CR9","doi-asserted-by":"publisher","first-page":"186","DOI":"10.1007\/s00607-025-01538-4","volume":"107","author":"R Vijay","year":"2025","unstructured":"Vijay R, Sree TR (2025) Secured trust and reputation management framework for cloud service in cloud computing. Computing 107(9):186","journal-title":"Computing"},{"key":"1614_CR10","doi-asserted-by":"crossref","unstructured":"Cao F, Zhu MM Energy-aware workflow job scheduling for green clouds. in (2013) IEEE international conference on green computing and communications and IEEE internet of things and IEEE cyber, physical and social computing. 2013. IEEE","DOI":"10.1109\/GreenCom-iThings-CPSCom.2013.58"},{"key":"1614_CR11","first-page":"100948","volume":"41","author":"S Ghafir","year":"2024","unstructured":"Ghafir S et al (2024) Load balancing in cloud computing via intelligent PSO-based feedback controller. Sustainable Computing: Inf Syst 41:100948","journal-title":"Sustainable Computing: Inf Syst"},{"key":"1614_CR12","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2025.3529839","author":"OL Abraham","year":"2025","unstructured":"Abraham OL et al (2025) Multi-objective optimization techniques in cloud task scheduling: a systematic literature review. IEEE Access. https:\/\/doi.org\/10.1109\/ACCESS.2025.3529839","journal-title":"IEEE Access"},{"key":"1614_CR13","doi-asserted-by":"publisher","first-page":"123554","DOI":"10.1016\/j.eswa.2024.123554","volume":"249","author":"S Gurusamy","year":"2024","unstructured":"Gurusamy S, Selvaraj R (2024) Resource allocation with efficient task scheduling in cloud computing using hierarchical auto-associative polynomial convolutional neural network. Expert Syst Appl 249:123554","journal-title":"Expert Syst Appl"},{"issue":"6","key":"1614_CR14","doi-asserted-by":"publisher","first-page":"7812","DOI":"10.1007\/s11227-023-05725-y","volume":"80","author":"S Rostami","year":"2024","unstructured":"Rostami S, Broumandnia A, Khademzadeh A (2024) An energy-efficient task scheduling method for heterogeneous cloud computing systems using capuchin search and inverted ant colony optimization algorithm. J Supercomput 80(6):7812\u20137848","journal-title":"J Supercomput"},{"key":"1614_CR15","unstructured":"Sun X (2025) Dynamic distributed scheduling for data stream computing: balancing task delay and load efficiency. J Comput Technol Softw 4(1):1\u20137"},{"issue":"17","key":"1614_CR16","doi-asserted-by":"publisher","first-page":"28649","DOI":"10.1109\/JIOT.2024.3402257","volume":"11","author":"Y Hu","year":"2024","unstructured":"Hu Y et al (2024) CoRaiS: lightweight Real-Time scheduler for multiedge cooperative computing. IEEE Internet Things J 11(17):28649\u201328666","journal-title":"IEEE Internet Things J"},{"key":"1614_CR17","doi-asserted-by":"publisher","DOI":"10.1109\/TPDS.2025.3553922","author":"Y Yao","year":"2025","unstructured":"Yao Y et al (2025) Workload-aware performance model based soft preemptive real-time scheduling for neural processing units. IEEE Trans Parallel Distrib Syst. https:\/\/doi.org\/10.1109\/TPDS.2025.3553922","journal-title":"IEEE Trans Parallel Distrib Syst"},{"key":"1614_CR18","unstructured":"Jia Q et al (2024) Deterministic computing power networking: Architecture, technologies and prospects. arXiv preprint arXiv:2401.17812"},{"issue":"2","key":"1614_CR19","doi-asserted-by":"publisher","first-page":"65","DOI":"10.20998\/2522-9052.2024.2.08","volume":"8","author":"H Kuchuk","year":"2024","unstructured":"Kuchuk H, Malokhvii E (2024) Integration of IoT with cloud, fog, and edge computing: a review. Adv Inform Syst 8(2):65\u201378","journal-title":"Adv Inform Syst"},{"issue":"4","key":"1614_CR20","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1007\/s10723-022-09630-1","volume":"20","author":"W Shi","year":"2022","unstructured":"Shi W, Li H, Zeng H (2022) Drl-based and bsld-aware job scheduling for Apache spark cluster in hybrid cloud computing environments. J Grid Comput 20(4):44","journal-title":"J Grid Comput"},{"issue":"6","key":"1614_CR21","doi-asserted-by":"publisher","first-page":"4051","DOI":"10.1007\/s10586-022-03809-7","volume":"26","author":"H Li","year":"2023","unstructured":"Li H et al (2023) A multi-objective task offloading based on BBO algorithm under deadline constrain in mobile edge computing. Cluster Comput 26(6):4051\u20134067","journal-title":"Cluster Comput"},{"key":"1614_CR22","doi-asserted-by":"publisher","DOI":"10.1007\/s00521-024-10929-1","author":"S Ebrahimi Mood","year":"2024","unstructured":"Ebrahimi Mood S, Rouhbakhsh A, Souri A (2024) Evolutionary recurrent neural network based on equilibrium optimization method for cloud-edge resource management in internet of things. Neural Comput Appl. https:\/\/doi.org\/10.1007\/s00521-024-10929-1","journal-title":"Neural Comput Appl"},{"issue":"2","key":"1614_CR23","doi-asserted-by":"publisher","first-page":"104","DOI":"10.1007\/s10586-024-04794-9","volume":"28","author":"M Mohammadi","year":"2025","unstructured":"Mohammadi M et al (2025) Security-aware resource allocation in fog computing using a meta-heuristic algorithm. Cluster Comput 28(2):104","journal-title":"Cluster Comput"},{"issue":"20","key":"1614_CR24","doi-asserted-by":"publisher","first-page":"4334","DOI":"10.3390\/math11204334","volume":"11","author":"MI Khaleel","year":"2023","unstructured":"Khaleel MI et al (2023) Workflow scheduling scheme for optimized reliability and end-to-end delay control in cloud computing using AI-based modeling. Mathematics 11(20):4334","journal-title":"Mathematics"},{"key":"1614_CR25","doi-asserted-by":"publisher","first-page":"458","DOI":"10.1016\/j.aej.2023.11.074","volume":"86","author":"MI Khaleel","year":"2024","unstructured":"Khaleel MI et al (2024) Combinatorial metaheuristic methods to optimize the scheduling of scientific workflows in green DVFS-enabled edge-cloud computing. Alexandria Eng J 86:458\u2013470","journal-title":"Alexandria Eng J"},{"key":"1614_CR26","first-page":"101611","volume":"50","author":"MI Khaleel","year":"2024","unstructured":"Khaleel MI et al (2024) Energy-latency trade-off analysis for scientific workflow in cloud environments: the role of processor utilization ratio and mean grey Wolf optimizer. Eng Sci Technol Int J 50:101611","journal-title":"Eng Sci Technol Int J"},{"issue":"16","key":"1614_CR27","doi-asserted-by":"publisher","first-page":"3563","DOI":"10.3390\/math11163563","volume":"11","author":"MI Khaleel","year":"2023","unstructured":"Khaleel MI et al (2023) A hybrid Many-Objective optimization algorithm for job scheduling in cloud computing based on Merge-and-Split theory. Mathematics 11(16):3563","journal-title":"Mathematics"},{"key":"1614_CR28","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1016\/j.future.2016.12.017","volume":"73","author":"Z Li","year":"2017","unstructured":"Li Z et al (2017) Energy cost minimization with job security guarantee in internet data center. Future Generation Comput Syst 73:63\u201378","journal-title":"Future Generation Comput Syst"},{"issue":"5","key":"1614_CR29","doi-asserted-by":"publisher","first-page":"637","DOI":"10.1109\/JIOT.2016.2579198","volume":"3","author":"W Shi","year":"2016","unstructured":"Shi W et al (2016) Edge computing: vision and challenges. IEEE Internet Things J 3(5):637\u2013646","journal-title":"IEEE Internet Things J"},{"issue":"2","key":"1614_CR30","doi-asserted-by":"publisher","first-page":"2144","DOI":"10.1109\/TCC.2022.3188926","volume":"11","author":"S Mousavi","year":"2022","unstructured":"Mousavi S et al (2022) Directed search: a new operator in NSGA-II for task scheduling in IoT based on cloud-fog computing. IEEE Trans Cloud Comput 11(2):2144\u20132157","journal-title":"IEEE Trans Cloud Comput"},{"issue":"1","key":"1614_CR31","doi-asserted-by":"publisher","first-page":"112","DOI":"10.1186\/s13677-023-00461-3","volume":"12","author":"I Ullah","year":"2023","unstructured":"Ullah I et al (2023) Optimizing task offloading and resource allocation in edge-cloud networks: a DRL approach. J Cloud Comput 12(1):112","journal-title":"J Cloud Comput"},{"issue":"3","key":"1614_CR32","doi-asserted-by":"publisher","first-page":"155","DOI":"10.1007\/s10586-024-04833-5","volume":"28","author":"BB Naik","year":"2025","unstructured":"Naik BB, Priyanka B, Ansari SA (2025) Energy-efficient task offloading and efficient resource allocation for edge computing: a quantum inspired particle swarm optimization approach. Cluster Comput 28(3):155","journal-title":"Cluster Comput"},{"issue":"1","key":"1614_CR33","doi-asserted-by":"publisher","first-page":"204","DOI":"10.1080\/00207721.2022.2153635","volume":"54","author":"H Chen","year":"2023","unstructured":"Chen H et al (2023) Slime mould algorithm: a comprehensive review of recent variants and applications. Int J Syst Sci 54(1):204\u2013235","journal-title":"Int J Syst Sci"},{"issue":"4","key":"1614_CR34","doi-asserted-by":"publisher","first-page":"2683","DOI":"10.1007\/s11831-023-09883-3","volume":"30","author":"FS Gharehchopogh","year":"2023","unstructured":"Gharehchopogh FS et al (2023) Slime mould algorithm: A comprehensive survey of its variants and applications. Arch Comput Methods Eng 30(4):2683\u20132723","journal-title":"Arch Comput Methods Eng"},{"key":"1614_CR35","doi-asserted-by":"publisher","first-page":"300","DOI":"10.1016\/j.future.2020.03.055","volume":"111","author":"S Li","year":"2020","unstructured":"Li S et al (2020) Slime mould algorithm: A new method for stochastic optimization. Future Generation Comput Syst 111:300\u2013323","journal-title":"Future Generation Comput Syst"},{"key":"1614_CR36","volume-title":"2019 IEEE Congress on Evolutionary Computation (CEC)","author":"P Bujok","year":"2019","unstructured":"Bujok P, Zamuda A (2019) Cooperative model of evolutionary algorithms applied to CEC 2019 single objective numerical optimization. 2019 IEEE Congress on Evolutionary Computation (CEC). IEEE"},{"key":"1614_CR37","doi-asserted-by":"publisher","first-page":"105190","DOI":"10.1016\/j.knosys.2019.105190","volume":"191","author":"A Faramarzi","year":"2020","unstructured":"Faramarzi A et al (2020) Equilibrium optimizer: A novel optimization algorithm. Knowl Based Syst 191:105190","journal-title":"Knowl Based Syst"},{"key":"1614_CR38","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1016\/j.advengsoft.2013.12.007","volume":"69","author":"S Mirjalili","year":"2014","unstructured":"Mirjalili S, Mirjalili SM, Lewis A (2014) Grey wolf optimizer. Adv Eng Softw 69:46\u201361","journal-title":"Adv Eng Softw"},{"key":"1614_CR39","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 et al (2019) Harris Hawks optimization: algorithm and applications. Future Generation Comput Syst 97:849\u2013872","journal-title":"Future Generation Comput Syst"},{"key":"1614_CR40","unstructured":"Rahimi A, Farshi M, Ebrahimi MS (2025) Punishment: A new operator to control selection pressure and improve the efficiency of the slime mold algorithm."},{"issue":"1","key":"1614_CR41","doi-asserted-by":"publisher","first-page":"75","DOI":"10.1080\/00220973.1993.9943832","volume":"62","author":"DW Zimmerman","year":"1993","unstructured":"Zimmerman DW, Zumbo BD (1993) Relative power of the Wilcoxon test, the Friedman test, and repeated-measures ANOVA on ranks. J Exp Educ 62(1):75\u201386","journal-title":"J Exp Educ"},{"key":"1614_CR42","doi-asserted-by":"crossref","unstructured":"Rodr\u00edguez-Fdez I et al (2015) STAC: a web platform for the comparison of algorithms using statistical tests. in. IEEE international conference on fuzzy systems (FUZZ-IEEE). 2015. IEEE","DOI":"10.1109\/FUZZ-IEEE.2015.7337889"}],"container-title":["Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00607-025-01614-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00607-025-01614-9","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00607-025-01614-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T05:19:06Z","timestamp":1769836746000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00607-025-01614-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1]]},"references-count":42,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,1]]}},"alternative-id":["1614"],"URL":"https:\/\/doi.org\/10.1007\/s00607-025-01614-9","relation":{},"ISSN":["0010-485X","1436-5057"],"issn-type":[{"value":"0010-485X","type":"print"},{"value":"1436-5057","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1]]},"assertion":[{"value":"25 September 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 December 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 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":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"23"}}