Title :
An Improved Genetic Algorithm with Limited Iteration for Grid Scheduling
Author :
Yin, Hao ; Wu, Huilin ; Zhou, Jiliu
Author_Institution :
Sch. of Comput. Sci., Sichuan Univ., Chengdu
Abstract :
In grid environment the numbers of resources and tasks to be scheduled are usually variable. This kind of characteristics of grid makes the scheduling approach a complex optimization problem. Genetic algorithm (GA) has been widely used to solve these difficult NP-complete problems. However the conventional GA is too slow to be used in a realistic scheduling due to its time-consuming iteration. This paper presents an improved genetic algorithm for scheduling independent tasks in grid environment, which can increase search efficiency with limited number of iteration by improving the evolutionary process while meeting a feasible result.
Keywords :
computational complexity; genetic algorithms; grid computing; iterative methods; resource allocation; scheduling; NP-complete problem; genetic algorithm; grid resource scheduling; independent task scheduling; optimization problem; time-consuming iteration; Biological cells; Computer networks; Crystallography; Distributed computing; Genetic algorithms; Grid computing; Instruments; Pervasive computing; Portals; Processor scheduling;
Conference_Titel :
Grid and Cooperative Computing, 2007. GCC 2007. Sixth International Conference on
Conference_Location :
Los Alamitos, CA
Print_ISBN :
0-7695-2871-6
DOI :
10.1109/GCC.2007.42
