A cloud service composition method using a fuzzy-based particle swarm optimization algorithm

dc.authoridAl-Khafaji, Hamza Mohammed Ridha/0000-0003-3620-581X
dc.authoridUnal, Mehmet/0000-0003-1243-153X
dc.authorscopusid34973317500
dc.authorscopusid57370210100
dc.authorscopusid57205482293
dc.authorscopusid55897274300
dc.authorscopusid57254381700
dc.authorwosidAl-Khafaji, Hamza Mohammed Ridha/D-6335-2019
dc.authorwosidUnal, Mehmet/W-2804-2018
dc.contributor.authorJafari Navimipour, Nima
dc.contributor.authorNassr, Mohammad
dc.contributor.authorAl-Khafaji, Hamza Mohammed Ridha
dc.contributor.authorNavimipour, Nima Jafari
dc.contributor.authorUnal, Mehmet
dc.date.accessioned2024-06-23T21:36:57Z
dc.date.available2024-06-23T21:36:57Z
dc.date.issued2023
dc.departmentKadir Has Universityen_US
dc.department-temp[Nazif, Habibeh] Payame Noor Univ, Dept Math, Tehran, Iran; [Nassr, Mohammad] Tartous Univ, Commun Technol Engn Dept, Tartus, Syria; [Nassr, Mohammad] Gulf Univ Sci & Technol, Dept Math & Nat Sci, Mishref Campus, Mubarak Al Abdullah, Kuwait; [Al-Khafaji, Hamza Mohammed Ridha] Al Mustaqbal Univ, Coll Engn & Technol, Biomed Engn Dept, Hillah 51001, Babil, Iraq; [Navimipour, Nima Jafari] Kadir Has Univ, Fac Engn & Nat Sci, Dept Comp Engn, Istanbul, Turkiye; [Navimipour, Nima Jafari] Natl Yunlin Univ Sci & Technol, Future Technol Res Ctr, Touliu 64002, Taiwan; [Unal, Mehmet] Nisantasi Univ, Dept Comp Engn, Istanbul, Turkiyeen_US
dc.descriptionAl-Khafaji, Hamza Mohammed Ridha/0000-0003-3620-581X; Unal, Mehmet/0000-0003-1243-153Xen_US
dc.description.abstractIn today's dynamic business landscape, organizations heavily rely on cloud computing to leverage the power of virtualization and resource sharing. Service composition plays a vital role in cloud computing, combining multiple cloud services to fulfill complex user requests. Service composition in cloud computing presents several challenges. These include service heterogeneity, dynamic service availability, QoS (Quality of Service) constraints, and scalability issues. Traditional approaches often struggle to handle these challenges efficiently, leading to suboptimal resource utilization and poor service performance. This work presents a fuzzy-based strategy for composing cloud services to overcome these obstacles. The fact that service composition is NP-hard has prompted the use of a range of metaheuristic algorithms in numerous papers. Therefore, Particle Swarm Optimization (PSO) has been applied in this paper to solve the problem. Implementing a fuzzy-based PSO for service composition requires defining the fuzzy membership functions and rules based on the specific service domain. Once the fuzzy logic components are established, they can be integrated into the PSO algorithm. The simulation results have shown the high efficiency of the proposed method in decreasing the latency, cost, and response time.en_US
dc.identifier.citation1
dc.identifier.doi10.1007/s11042-023-17719-2
dc.identifier.issn1380-7501
dc.identifier.issn1573-7721
dc.identifier.scopus2-s2.0-85179336452
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1007/s11042-023-17719-2
dc.identifier.urihttps://hdl.handle.net/20.500.12469/5675
dc.identifier.wosWOS:001122190800008
dc.identifier.wosqualityN/A
dc.language.isoenen_US
dc.publisherSpringeren_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectService compositionen_US
dc.subjectCloud computingen_US
dc.subjectParticle swarm optimizationen_US
dc.subjectFuzzyen_US
dc.titleA cloud service composition method using a fuzzy-based particle swarm optimization algorithmen_US
dc.typeArticleen_US
dspace.entity.typePublication
relation.isAuthorOfPublication0fb3c7a0-c005-4e5f-a9ae-bb163df2df8e
relation.isAuthorOfPublication.latestForDiscovery0fb3c7a0-c005-4e5f-a9ae-bb163df2df8e

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