A new fog-based transmission scheduler on the Internet of multimedia things using a fuzzy-based quantum genetic algorithm

dc.authorscopusid57212168473
dc.authorscopusid57205482293
dc.authorscopusid55897274300
dc.authorscopusid57780713800
dc.contributor.authorJafari Navimipour, Nima
dc.contributor.authorAl-Khafaji, H.M.R.
dc.contributor.authorJafari Navimipour, N.
dc.contributor.authorYalcin, S.
dc.date.accessioned2023-10-19T15:05:28Z
dc.date.available2023-10-19T15:05:28Z
dc.date.issued2023
dc.department-tempZanbouri, K., Department of Computer Engineering, Tabriz Branch, Islamic Azad University, Tabriz, Iran; Al-Khafaji, H.M.R., Biomedical Engineering Department, Al-Mustaqbal University College, Hillah, Iraq; Jafari Navimipour, N., Department of Computer Engineering, Kadir Has University, Istanbul, Turkey; Yalcin, S., Department of Computer Engineering, Nisantasi University, Istanbul, Turkeyen_US
dc.description.abstractThe Internet of Multimedia Things (IoMT) has recently experienced a considerable surge in multimedia-based services. Due to the fast proliferation and transfer of massive data, the IoMT has service quality challenges. This paper proposes a novel fog-based multimedia transmission scheme for IoMT using the Sugano interference system with a quantum genetic optimization algorithm. The fuzzy system devises a mathematically organized strategy for generating fuzzy rules from input and output variables. The Quantum Genetic Algorithm (QGA) is a metaheuristic algorithm that combines genetic algorithms and quantum computing theory. It combines many critical elements of quantum computing, such as quantum superposition and entanglement. This provides a robust representation of population diversity and the capacity to achieve rapid convergence and high accuracy. As a result of the simulations and computational analysis, the proposed fuzzy-based QGA scheme improves packet delivery ratio and throughput by reducing end-to-end latency and delay when compared to traditional algorithms like Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Heterogeneous Earliest-Finish-Time (HEFT) and Ant Colony Optimization (ACO). Consequently, it provides a more efficient scheme for multimedia transmission in IoMT. IEEEen_US
dc.identifier.citation4
dc.identifier.doi10.1109/MMUL.2023.3247522en_US
dc.identifier.endpage12en_US
dc.identifier.issn1070-986X
dc.identifier.scopus2-s2.0-85149369843en_US
dc.identifier.scopusqualityQ1
dc.identifier.startpage1en_US
dc.identifier.urihttps://doi.org/10.1109/MMUL.2023.3247522
dc.identifier.urihttps://hdl.handle.net/20.500.12469/4907
dc.identifier.wosqualityQ1
dc.khas20231019-Scopusen_US
dc.language.isoenen_US
dc.publisherIEEE Computer Societyen_US
dc.relation.ispartofIEEE Multimediaen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectCloud computingen_US
dc.subjectGenetic algorithmsen_US
dc.subjectInternet of Thingsen_US
dc.subjectMultimedia systemsen_US
dc.subjectOptimizationen_US
dc.subjectQuantum computingen_US
dc.subjectTask analysisen_US
dc.subjectCodes (symbols)en_US
dc.subjectFuzzy inferenceen_US
dc.subjectGenetic algorithmsen_US
dc.subjectInternet of thingsen_US
dc.subjectMultimedia servicesen_US
dc.subjectMultimedia systemsen_US
dc.subjectParticle swarm optimization (PSO)en_US
dc.subjectQuantum entanglementen_US
dc.subjectCloud-computingen_US
dc.subjectMassive dataen_US
dc.subjectMultimedia transmissionsen_US
dc.subjectOptimisationsen_US
dc.subjectQuality challengesen_US
dc.subjectQuantum Computingen_US
dc.subjectQuantum genetic algorithmen_US
dc.subjectService Qualityen_US
dc.subjectTask analysisen_US
dc.subjectTransmission schemesen_US
dc.subjectAnt colony optimizationen_US
dc.titleA new fog-based transmission scheduler on the Internet of multimedia things using a fuzzy-based quantum genetic algorithmen_US
dc.typeArticleen_US
dspace.entity.typePublication
relation.isAuthorOfPublication0fb3c7a0-c005-4e5f-a9ae-bb163df2df8e
relation.isAuthorOfPublication.latestForDiscovery0fb3c7a0-c005-4e5f-a9ae-bb163df2df8e

Files

Original bundle

Now showing 1 - 1 of 1
No Thumbnail Available
Name:
4907.pdf
Size:
1.35 MB
Format:
Adobe Portable Document Format
Description:
Tam Metin / Full Text