{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,24]],"date-time":"2026-07-24T06:19:04Z","timestamp":1784873944964,"version":"3.55.0"},"reference-count":44,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2023,2,15]],"date-time":"2023-02-15T00:00:00Z","timestamp":1676419200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Qassim University"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Recently, the concept of the internet of things and its services has emerged with cloud computing. Cloud computing is a modern technology for dealing with big data to perform specified operations. The cloud addresses the problem of selecting and placing iterations across nodes in fog computing. Previous studies focused on original swarm intelligent and mathematical models; thus, we proposed a novel hybrid method based on two modern metaheuristic algorithms. This paper combined the Aquila Optimizer (AO) algorithm with the elephant herding optimization (EHO) for solving dynamic data replication problems in the fog computing environment. In the proposed method, we present a set of objectives that determine data transmission paths, choose the least cost path, reduce network bottlenecks, bandwidth, balance, and speed data transfer rates between nodes in cloud computing. A hybrid method, AOEHO, addresses the optimal and least expensive path, determines the best replication via cloud computing, and determines optimal nodes to select and place data replication near users. Moreover, we developed a multi-objective optimization based on the proposed AOEHO to decrease the bandwidth and enhance load balancing and cloud throughput. The proposed method is evaluated based on data replication using seven criteria. These criteria are data replication access, distance, costs, availability, SBER, popularity, and the Floyd algorithm. The experimental results show the superiority of the proposed AOEHO strategy performance over other algorithms, such as bandwidth, distance, load balancing, data transmission, and least cost path.<\/jats:p>","DOI":"10.3390\/s23042189","type":"journal-article","created":{"date-parts":[[2023,2,15]],"date-time":"2023-02-15T04:47:24Z","timestamp":1676436444000},"page":"2189","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["AOEHO: A New Hybrid Data Replication Method in Fog Computing for IoT Application"],"prefix":"10.3390","volume":"23","author":[{"given":"Ahmed awad","family":"Mohamed","sequence":"first","affiliation":[{"name":"Information System Department, Cairo Higher Institute for Languages and Simultaneous Interpretation, and Administrative Science, Cairo 11765, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2203-4549","authenticated-orcid":false,"given":"Laith","family":"Abualigah","sequence":"additional","affiliation":[{"name":"Computer Science Department, Prince Hussein Bin Abdullah Faculty for Information Technology, Al Al-Bayt University, Mafraq 25113, Jordan"},{"name":"Hourani Center for Applied Scientific Research, Al-Ahliyya Amman University, Amman 19328, Jordan"},{"name":"Faculty of Information Technology, Middle East University, Amman 11831, Jordan"},{"name":"Applied Science Research Center, Applied Science Private University, Amman 11931, Jordan"},{"name":"School of Computer Sciences, Universiti Sains Malaysia, Pulau Pinang 11800, Malaysia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alhanouf","family":"Alburaikan","sequence":"additional","affiliation":[{"name":"Department of Mathematics, College of Science and Arts, Qassim University, Al-Badaya 51951, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hamiden Abd El-Wahed","family":"Khalifa","sequence":"additional","affiliation":[{"name":"Department of Mathematics, College of Science and Arts, Qassim University, Al-Badaya 51951, Saudi Arabia"},{"name":"Department of Operations and Management Research, Faculty of Graduate Studies for Statistical Research, Cairo University, Giza 12613, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,2,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1002\/spe.995","article-title":"CloudSim: A toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms","volume":"41","author":"Calheiros","year":"2011","journal-title":"Softw. Pract. Exp."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Long, S., and Zhao, Y. (2012, January 7\u20139). A toolkit for modeling and simulating cloud data storage: An extension to CloudSim. Proceedings of the 2012 International Conference on Control Engineering and Communication Technology, Washington, DC, USA.","DOI":"10.1109\/ICCECT.2012.160"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1016\/j.jnca.2016.08.029","article-title":"To move or not to move: Cost optimization in a dual cloud-based storage architecture","volume":"75","author":"Mansouri","year":"2016","journal-title":"J. Netw. Comput. Appl."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Rajeshirke, N., Sawant, R., Sawant, S., and Shaikh, H. (2017). Load balancing in cloud computing. Int. J. Recent Trends Eng. Res., 3.","DOI":"10.23883\/IJRTER.2017.3076.UIMCU"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1016\/j.jnca.2016.06.003","article-title":"Load balancing mechanisms and techniques in the cloud environments: Systematic literature review an future trends","volume":"71","author":"Milani","year":"2016","journal-title":"J. Netw. Comput. Appl."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.jnca.2017.04.007","article-title":"Load-balancing algorithms in cloud computing: A survey","volume":"88","author":"Ghomi","year":"2017","journal-title":"J. Netw. Comput. Appl."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/j.jnca.2016.08.018","article-title":"Cost-aware service brokering and performance sentient load balancing algorithms in the cloud","volume":"75","author":"Naha","year":"2016","journal-title":"J. Netw. Comput. Appl."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1312","DOI":"10.1007\/s11227-016-1661-7","article-title":"Dynamic erasure coding decision for modern block-oriented distributed storage systems","volume":"72","author":"Ahn","year":"2016","journal-title":"J. Supercomput."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1016\/j.jnca.2017.07.013","article-title":"A congestion-aware and robust multicast protocol in SDN-based datacenter networks","volume":"95","author":"Zhu","year":"2017","journal-title":"J. Netw. Comput. Appl."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Nguyen, B., Binh, H., and Son, B. (2019). Evolutionary algorithms to optimize task scheduling problem for the IoT based bag-of-tasks application in cloud-fog computing environment. Appl. Sci., 9.","DOI":"10.3390\/app9091730"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Ghasempour, A. (2019). Internet of things in smart grid: Architecture, applications, services, key technologies, and challenges. Inventions, 4.","DOI":"10.3390\/inventions4010022"},{"key":"ref_12","first-page":"2479","article-title":"On replication strategies for data intensive cloud applications","volume":"6","author":"Ranjana","year":"2017","journal-title":"Int. J. Comput. Sci. Inf. Technol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"4519","DOI":"10.1109\/TII.2018.2793350","article-title":"Secure data storage and searching for industrial IoT by integrating fog computing and cloud computing","volume":"14","author":"Fu","year":"2018","journal-title":"IEEE Trans. Ind. Inf."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"581","DOI":"10.1109\/TNSM.2016.2554143","article-title":"A pretreatment workflow scheduling approach for big data applications in multicloud environments","volume":"13","author":"Lin","year":"2016","journal-title":"IEEE Trans. Netw. Serv. Manag."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1109\/TEVC.2016.2623803","article-title":"An energy efficient ant colony system for virtual machine placement in cloud computing","volume":"22","author":"Liu","year":"2016","journal-title":"IEEE Trans. Evol. Comput."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"488","DOI":"10.14445\/22315381\/IJETT-V45P292","article-title":"Data replication in current generation computing environment","volume":"45","author":"Kumar","year":"2017","journal-title":"Int. J. Eng. Trends Technol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1007\/s10586-020-03075-5","article-title":"A novel hybrid antlion optimization algorithm for multi-objective task scheduling problems in cloud computing environments","volume":"24","author":"Abualigah","year":"2020","journal-title":"Clust. Comput."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2734219","DOI":"10.1155\/2018\/2734219","article-title":"Immune scheduling network based method for task scheduling in decentralized fog computing","volume":"2018","author":"Wang","year":"2018","journal-title":"Wirel. Commun. Mob. Comput."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"65085","DOI":"10.1109\/ACCESS.2020.2983742","article-title":"A multi-objective task scheduling method for fog computing in cyber-physical-social services","volume":"8","author":"Yang","year":"2020","journal-title":"IEEE Access"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1007\/s10257-019-00422-x","article-title":"A novel dynamic data replication strategy to improve access efficiency of cloud storage","volume":"18","author":"John","year":"2020","journal-title":"Inf. Syst. e-Bus. Manag."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1016\/j.future.2022.01.012","article-title":"QoS-aware placement of microservices-based IoT applications in Fog computing environments","volume":"131","author":"Pallewatta","year":"2022","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1016\/j.jnca.2016.02.005","article-title":"A comprehensive review of the data replication techniques in the cloud environments: Major trends and future directions","volume":"64","author":"Milani","year":"2016","journal-title":"J. Netw. Comput. Appl."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1002","DOI":"10.1109\/COMST.2016.2626384","article-title":"A survey replica server placement algorithms for content delivery networks","volume":"19","author":"Sahoo","year":"2017","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1016\/j.comcom.2020.04.023","article-title":"Optimized data storage algorithm of IoT based on cloud computing in distributed system","volume":"157","author":"Wang","year":"2020","journal-title":"Comput. Commun."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"482","DOI":"10.1002\/spe.3032","article-title":"A metaheuristic-based data replica placement approach for data-intensive IoT applications in the fog computing environment","volume":"52","author":"Taghizadeh","year":"2021","journal-title":"Softw. Pract. Exp."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"3561","DOI":"10.1007\/s10586-022-03575-6","article-title":"Data replica placement approaches in fog computing: A review","volume":"25","author":"Torabi","year":"2022","journal-title":"Clust. Comput."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"3847","DOI":"10.1007\/s40747-022-00659-z","article-title":"Decision-making of IoT device operation based on intelligent-task offloading for improving environmental optimization","volume":"8","author":"Jin","year":"2022","journal-title":"Complex Intell. Syst."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"51841","DOI":"10.1109\/ACCESS.2019.2957436","article-title":"An Artificial Bee Colony Algorithm for Data Replication Optimization in Cloud Environments","volume":"8","author":"Salem","year":"2020","journal-title":"IEEE Access"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"40240","DOI":"10.1109\/ACCESS.2021.3064917","article-title":"A Novel Intelligent Approach for Dynamic Data Replication in Cloud Environment","volume":"9","author":"Awad","year":"2021","journal-title":"IEEE Access"},{"key":"ref_30","first-page":"271","article-title":"A Swarm Intelligence-based Approach for Dynamic Data Replication in a Cloud Environment","volume":"14","author":"Awad","year":"2021","journal-title":"Int. J. Intell. Eng. Syst."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"538","DOI":"10.1016\/j.future.2021.10.024","article-title":"Efficient privacy-preserving data replication in fog-enabled IoT","volume":"128","author":"Sarwar","year":"2022","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"786","DOI":"10.1109\/TPDS.2020.3030063","article-title":"BOSSA: A Decentralized System for Proofs of Data Retrievability and Replication","volume":"32","author":"Chen","year":"2021","journal-title":"IEEE Trans. Parallel Distrib. Syst."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"111227","DOI":"10.1016\/j.jss.2022.111227","article-title":"Fault-tolerant scheduling and data placement for scientific workflow processing in geo-distributed clouds","volume":"187","author":"Li","year":"2022","journal-title":"J. Syst. Softw."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1982","DOI":"10.1109\/TPDS.2021.3133884","article-title":"Cost-Effective Web Application Replication and Deployment in Multi-Cloud Environment","volume":"33","author":"Shi","year":"2022","journal-title":"IEEE Trans. Parallel Distrib. Syst."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1007\/s10586-021-03395-0","article-title":"Replication management in peer-to-peer cloud storage systems","volume":"25","author":"Majed","year":"2022","journal-title":"Clust. Comput."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1016\/j.future.2021.08.014","article-title":"Optimal data placement strategy considering capacity limitation and load balancing in geographically distributed cloud","volume":"127","author":"Li","year":"2022","journal-title":"Future Gener. Comput. Syst."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"102428","DOI":"10.1016\/j.simpat.2021.102428","article-title":"Data correlation and fuzzy inference system-based data replication in federated cloud systems","volume":"115","author":"Khelifa","year":"2022","journal-title":"Simul. Model. Pract. Theory"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"981","DOI":"10.1007\/s11277-021-08936-9","article-title":"A Fuzzy Logic-Based Method for Replica Placement in the Peer to Peer Cloud Using an Optimization Algorithm","volume":"122","author":"Mohammadi","year":"2022","journal-title":"Wirel. Pers. Commun."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"22487","DOI":"10.1109\/ACCESS.2022.3153727","article-title":"The Simplified Aquila Optimization Algorithm","volume":"10","author":"Zhao","year":"2022","journal-title":"IEEE Access"},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Li, J., Lei, H., Alavi, A.H., and Wang, G.G. (2020). Elephant Herding Optimization: Variants, Hybrids, and Applications. Mathematics, 8.","DOI":"10.3390\/math8091415"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Agushaka, J.O., Ezugwu, A.E., Abualigah, L., Alharbi, S.K., and Khalifa, H.A.E.W. (2022). Efficient Initialization Methods for Population-Based Metaheuristic Algorithms: A Comparative Study. Arch. Comput. Methods Eng., 1\u201361.","DOI":"10.1007\/s11831-022-09850-4"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s10618-011-0242-x","article-title":"A single pass algorithm for clustering evolving data streams based on swarm intelligence","volume":"26","author":"Forestiero","year":"2013","journal-title":"Data Min. Knowl. Discov."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"126871","DOI":"10.1109\/ACCESS.2022.3218653","article-title":"A Centralized Strategy for Multi-Agent Exploration","volume":"10","author":"Gul","year":"2022","journal-title":"IEEE Access"},{"key":"ref_44","unstructured":"Abualigah, L., Elaziz, M.A., Khodadadi, N., Forestiero, A., Jia, H., and Gandomi, A.H. (2022). Integrating Meta-Heuristics and Machine Learning for Real-World Optimization Problems, Springer."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/4\/2189\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T18:36:20Z","timestamp":1760121380000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/23\/4\/2189"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,2,15]]},"references-count":44,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2023,2]]}},"alternative-id":["s23042189"],"URL":"https:\/\/doi.org\/10.3390\/s23042189","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,2,15]]}}}