A new fog-based transmission scheduler on the Internet of multimedia things using a fuzzy-based quantum genetic algorithm
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Date
2023
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IEEE Computer Society
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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
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Keywords
Cloud computing, Genetic algorithms, Internet of Things, Multimedia systems, Optimization, Quantum computing, Task analysis, Codes (symbols), Fuzzy inference, Genetic algorithms, Internet of things, Multimedia services, Multimedia systems, Particle swarm optimization (PSO), Quantum entanglement, Cloud-computing, Massive data, Multimedia transmissions, Optimisations, Quality challenges, Quantum Computing, Quantum genetic algorithm, Service Quality, Task analysis, Transmission schemes, Ant colony optimization
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Q1
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IEEE Multimedia
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1
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12