Resource management and scheduling model in grid computing based on an advanced genetic algorithm

Grid computing is one of the research hotspots in high performance computing area. Efficient scheduling of complex applications in a grid environment reveals several challenges due to its high heterogeneity, dynamic behavior, and space shared utilization. We studied the characteristics of gird tasks, analyzed several main grid resource management models, and built a common model of grid tasks, put forward a hierarchy grid resource management and scheduling model, expounded the ideas of designing the model and described the details of it. Moreover, we proposed an advanced genetic algorithm (GA) in its scheduling strategy, particularized the principle and the function of this algorithm as well as giving the concrete plan to put every step of the scheduling strategy into practice. Finally, the algorithm was simulated with the aid of SimGrid toolkit. The results indicate that the advanced genetic algorithm could more efficiently realize global scheduling and could be an effective measurement for grid scheduling.