Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: This article concerns an efficient real-time task scheduling assisted by Hybrid Quantum-Inspired Genetic Algorithm (HQIGA) in multiprocessor environment. Relying on concepts and the principles of quantum mechanics, HQIGA explores the computing por of quantum computation. To drive schedule toward better convergence, HQIGA operates using rotation gate for exploration of variable chromosomes described by  qubits  in Hilbert hyperspace. A fitness function associated with popularly known heuristic earliest deadline first (EDF) is employed and random key distribution is adopted to convert the  qubits  chromosomes to valid schedule solutions. In addition to this, permutation based trimming technique is applied to diversify the population which yields good quality schedules. To establish the effectiveness of the suggested HQIGA, it demonstrates using various number of real-time tasks and processors along with arbitrary processing time. Simulation result shows that HQIGA outperforms the classical genetic algorithm (CGA) and Hybrid Particle Swarm Optimization (HPSO) in terms of fitness values obtained using less number of generations and also it improves the scheduling time significantly. HQIGA is also tested separately with the heuristic Shortest Computation Time First (SCTF) technique to show the superiority of EDF over SCTF.
['Debanjan Konar', 'Siddhartha Bhattacharyya', 'Kalpana Sharma', 'Sital Sharma', 'Sri Raj Pradhan']
I am writing a research paper on a idea An improved Hybrid Quantum-Inspired Genetic Algorithm (HQIGA) for scheduling of real-time task in multiprocessor system
[{"from": "human", "value": "I am writing a research paper on a idea An improved Hybrid Quantum-Inspired Genetic Algorithm (HQIGA) for scheduling of real-time task in multiprocessor system"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: This article concerns an efficient real-time task scheduling assisted by Hybrid Quantum-Inspired Genetic Algorithm (HQIGA) in multiprocessor environment. Relying on concepts and the principles of quantum mechanics, HQIGA explores the computing por of quantum computation. To drive schedule toward better convergence, HQIGA operates using rotation gate for exploration of variable chromosomes described by  qubits  in Hilbert hyperspace. A fitness function associated with popularly known heuristic earliest deadline first (EDF) is employed and random key distribution is adopted to convert the  qubits  chromosomes to valid schedule solutions. In addition to this, permutation based trimming technique is applied to diversify the population which yields good quality schedules. To establish the effectiveness of the suggested HQIGA, it demonstrates using various number of real-time tasks and processors along with arbitrary processing time. Simulation result shows that HQIGA outperforms the classical genetic algorithm (CGA) and Hybrid Particle Swarm Optimization (HPSO) in terms of fitness values obtained using less number of generations and also it improves the scheduling time significantly. HQIGA is also tested separately with the heuristic Shortest Computation Time First (SCTF) technique to show the superiority of EDF over SCTF."}]