Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Job scheduling in computational grid is a complex problem and various heuristics and meta-heuristics have been proposed for the same. These approaches usually optimize specific characteristic parameters while allocating the jobs on the grid resources. Many a times, it is desired to optimize multiple parameters during job scheduling. Non-dominated sorting genetic algorithm (NSGA-II) has been observed to be the best meta-heuristic to solve such multi-objective optimization problem. The proposed work applies NSGA-II for job scheduling in computational grid with three conflicting objectives: maximizing reliability of the system for job allocation, minimizing energy consumption and balancing the load on the system. Performance study of the proposed model is done by simulating it on some real data. The result indicates that the proposed model performs ll with multiple objectives.
['Achal Kaushik', 'Deo Prakash Vidyarthi']
I am writing a research paper on a idea An energy-efficient reliable grid scheduling model using NSGA-II
[{"from": "human", "value": "I am writing a research paper on a idea An energy-efficient reliable grid scheduling model using NSGA-II"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Job scheduling in computational grid is a complex problem and various heuristics and meta-heuristics have been proposed for the same. These approaches usually optimize specific characteristic parameters while allocating the jobs on the grid resources. Many a times, it is desired to optimize multiple parameters during job scheduling. Non-dominated sorting genetic algorithm (NSGA-II) has been observed to be the best meta-heuristic to solve such multi-objective optimization problem. The proposed work applies NSGA-II for job scheduling in computational grid with three conflicting objectives: maximizing reliability of the system for job allocation, minimizing energy consumption and balancing the load on the system. Performance study of the proposed model is done by simulating it on some real data. The result indicates that the proposed model performs ll with multiple objectives."}]