A novel scheduling model for computational grid using quantum genetic algorithm
The Computational Grid (CG) provides a wide distributed platform for high end computing intensive applications. Scheduling on Computational grid is known to be NP-Hard problem and requires an efficient solution. Recently, quantum inspired computing has been introduced in the literature to solve such a complex combinatorial optimization problem efficiently. Combination of Genetic Algorithm (GA) and quantum concept evolves a new meta-heuristic technique known as Quantum Genetic Algorithms (QGA). QGA is a search procedure based on evolutionary computation and Quantum Computing (QC). This paper proposes a novel technique of scheduling in computational grid using QGA. The work simulates the model to study its performance. It also makes a comparative study with a GA-based scheduling model. Simulation results reveal the effectiveness of the model.
scheduling computational grid quantum genetic algorithms quantum computing arrival rate makespan