A New Fog-Based Transmission Scheduler on the Internet of Multimedia Things Using a Fuzzy-Based Quantum Genetic Algorithm

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 article proposes a novel fog-based multimedia transmission scheme for the 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 the packet delivery ratio and throughput by reducing end-to-end latency and delay when compared to traditional algorithms like genetic algorithm, particle swarm optimization, heterogeneous earliest finish time, and ant colony optimization. Consequently, it provides a more efficient scheme for multimedia transmission in the IoMT.