dc.contributor.author | Zanbouri, K. | |
dc.contributor.author | Al-Khafaji, H.M.R. | |
dc.contributor.author | Jafari Navimipour, N. | |
dc.contributor.author | Yalcin, S. | |
dc.date.accessioned | 2023-10-19T15:05:28Z | |
dc.date.available | 2023-10-19T15:05:28Z | |
dc.date.issued | 2023 | |
dc.identifier.issn | 1070-986X | |
dc.identifier.uri | https://doi.org/10.1109/MMUL.2023.3247522 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12469/4907 | |
dc.description.abstract | The 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. IEEE | en_US |
dc.language.iso | eng | en_US |
dc.publisher | IEEE Computer Society | en_US |
dc.relation.ispartof | IEEE Multimedia | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Cloud computing | en_US |
dc.subject | Genetic algorithms | en_US |
dc.subject | Internet of Things | en_US |
dc.subject | Multimedia systems | en_US |
dc.subject | Optimization | en_US |
dc.subject | Quantum computing | en_US |
dc.subject | Task analysis | en_US |
dc.subject | Codes (symbols) | en_US |
dc.subject | Fuzzy inference | en_US |
dc.subject | Genetic algorithms | en_US |
dc.subject | Internet of things | en_US |
dc.subject | Multimedia services | en_US |
dc.subject | Multimedia systems | en_US |
dc.subject | Particle swarm optimization (PSO) | en_US |
dc.subject | Quantum entanglement | en_US |
dc.subject | Cloud-computing | en_US |
dc.subject | Massive data | en_US |
dc.subject | Multimedia transmissions | en_US |
dc.subject | Optimisations | en_US |
dc.subject | Quality challenges | en_US |
dc.subject | Quantum Computing | en_US |
dc.subject | Quantum genetic algorithm | en_US |
dc.subject | Service Quality | en_US |
dc.subject | Task analysis | en_US |
dc.subject | Transmission schemes | en_US |
dc.subject | Ant colony optimization | en_US |
dc.title | A new fog-based transmission scheduler on the Internet of multimedia things using a fuzzy-based quantum genetic algorithm | en_US |
dc.type | article | en_US |
dc.identifier.startpage | 1 | en_US |
dc.identifier.endpage | 12 | en_US |
dc.department | N/A | en_US |
dc.identifier.doi | 10.1109/MMUL.2023.3247522 | en_US |
dc.identifier.scopus | 2-s2.0-85149369843 | en_US |
dc.institutionauthor | N/A | |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.authorscopusid | 57212168473 | |
dc.authorscopusid | 57205482293 | |
dc.authorscopusid | 55897274300 | |
dc.authorscopusid | 57780713800 | |
dc.khas | 20231019-Scopus | en_US |