Grid Resource Scheduling Strategy Based On Elite DNA Genetic Algorithm

Traditional resource scheduling algorithm, in grid environment, exist some defects, for example it can not well meet the quality requirements and can not get the optimal solution. This article gives an new resource scheduling method based on Improved genetic algorithm. It achieves grid resource scheduling by using real number encoding and activities point crossover. Experiments show that genetic algorithm can reduce executing time and task completion time, and further improve the scalability of resource scheduling model. This algorithm has stability and high efficiency in grid environment.Grid computing core of the problem is that most grid resource scheduling, grid resource scheduling objective is through the rational allocation of resources to different treatment unit, leaving the implementation of the general task of optimal according to the user's requirements, so resources scheduling for grid resource utilization is very important. Grid resource scheduling problem is an NP problem, and genetic algorithms to solve NP has been shown to be an effective algorithm for the problem.This paper describes the biological principles of genetic algorithms, characteristics, and basic operation, the advantages of scheduling problems and their solutions are given basic operation method code. DNA was proposed based on genetic algorithm elite grid resource scheduling strategy. By improving the policy, the introduction of hybrid crossover operator, single genetic operator and successive approximation of the strategy so that a better scheduling strategy of convergence, can quickly find the optimal solution.The article first briefly look at grid computing, genetic algorithm theory, and analysis of the genetic algorithm to solve the problem of grid resource scheduling advantages, disadvantages and feasibility.Secondly, the article to the basic idea of genetic algorithm based on the common genetic algorithm was improved. Grid resources scheduling problem for the model analysis. Improved genetic algorithm to solve the problem of grid resource scheduling.At last, the article shows the system running processes, algorithms, and the core idea. NET platform with a grid resource scheduling system, through experimental analysis proved that the improved algorithm has a good effect.