A cloud service composition method using a fuzzy-based particle swarm optimization algorithm
dc.authorid | Al-Khafaji, Hamza Mohammed Ridha/0000-0003-3620-581X | |
dc.authorid | Unal, Mehmet/0000-0003-1243-153X | |
dc.authorscopusid | 34973317500 | |
dc.authorscopusid | 57370210100 | |
dc.authorscopusid | 57205482293 | |
dc.authorscopusid | 55897274300 | |
dc.authorscopusid | 57254381700 | |
dc.authorwosid | Al-Khafaji, Hamza Mohammed Ridha/D-6335-2019 | |
dc.authorwosid | Unal, Mehmet/W-2804-2018 | |
dc.contributor.author | Jafari Navimipour, Nima | |
dc.contributor.author | Nassr, Mohammad | |
dc.contributor.author | Al-Khafaji, Hamza Mohammed Ridha | |
dc.contributor.author | Navimipour, Nima Jafari | |
dc.contributor.author | Unal, Mehmet | |
dc.date.accessioned | 2024-06-23T21:36:57Z | |
dc.date.available | 2024-06-23T21:36:57Z | |
dc.date.issued | 2023 | |
dc.department | Kadir Has University | en_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, Turkiye | en_US |
dc.description | Al-Khafaji, Hamza Mohammed Ridha/0000-0003-3620-581X; Unal, Mehmet/0000-0003-1243-153X | en_US |
dc.description.abstract | In 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.citation | 1 | |
dc.identifier.doi | 10.1007/s11042-023-17719-2 | |
dc.identifier.issn | 1380-7501 | |
dc.identifier.issn | 1573-7721 | |
dc.identifier.scopus | 2-s2.0-85179336452 | |
dc.identifier.scopusquality | Q1 | |
dc.identifier.uri | https://doi.org/10.1007/s11042-023-17719-2 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12469/5675 | |
dc.identifier.wos | WOS:001122190800008 | |
dc.identifier.wosquality | N/A | |
dc.language.iso | en | en_US |
dc.publisher | Springer | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Service composition | en_US |
dc.subject | Cloud computing | en_US |
dc.subject | Particle swarm optimization | en_US |
dc.subject | Fuzzy | en_US |
dc.title | A cloud service composition method using a fuzzy-based particle swarm optimization algorithm | en_US |
dc.type | Article | en_US |
dspace.entity.type | Publication | |
relation.isAuthorOfPublication | 0fb3c7a0-c005-4e5f-a9ae-bb163df2df8e | |
relation.isAuthorOfPublication.latestForDiscovery | 0fb3c7a0-c005-4e5f-a9ae-bb163df2df8e |