Title :
Grid Workflow Scheduling based on improved genetic algorithm
Author :
Zhang, Xue ; Zeng, Wenhua
Author_Institution :
Cognitive Sci. Dept., Xiamen Univ., Xiamen, China
Abstract :
Grid Workflow Scheduling represented by DAG(Directed Acyclic Graph) is a typical NP-complete problem, and thus a scheduling algorithm of high efficiency is required. So an improved genetic algorithm is proposed to solve this problem. In the algorithm, chromosomes of poor fitness make secondary preferential hybridization and mutation with the overall best individual. It not only guarantees the population diversity but increases the convergence rate of population. Experiment results based on Gridsim prove it available and better than standard genetic algorithm.
Keywords :
directed graphs; genetic algorithms; grid computing; scheduling; Gridsim; NP-complete problem; directed acyclic graph; grid workflow scheduling; improved genetic algorithm; Convergence; Costs; Genetic algorithms; Genetic mutations; Grid computing; Intelligent systems; Laboratories; Processor scheduling; Resource management; Scheduling algorithm; Grid workflow; Gridsim; improved genetic algorithm; scheduling problem; secondary preferential hybridization and mutation;
Conference_Titel :
Computer Design and Applications (ICCDA), 2010 International Conference on
Conference_Location :
Qinhuangdao
Print_ISBN :
978-1-4244-7164-5
Electronic_ISBN :
978-1-4244-7164-5
DOI :
10.1109/ICCDA.2010.5541161