Title :
Grid resource scheduling algorithm based on QoS guided GA
Author :
Shi, Lei ; Xu, Hui-Hui
Author_Institution :
Sch. of Inf. Sci. & Eng., Shandong Normal Univ., Ji´´nan, China
Abstract :
Application of genetic algorithm (GA) for distribution and grid tasks scheduling has caused more and more academic concern. In this paper, the limitations of the existing genetic algorithm are analyzed. On the basis a grid resource scheduling algorithm based on QoS Guided GA is proposed, which takes these QoS factors into consideration including the priority of tasks, deadlines and budget constraints, etc; also, the encoding mechanism, fitness function, selection operator, crossover operator and mutation operator has been redesigned. Finally, the performance of the improved algorithm is simulated and compared with the original algorithm. The experimental results indicate that the improved algorithm can significantly reduce execution time consumption, and achieve high resource utilization.
Keywords :
genetic algorithms; grid computing; quality of service; resource allocation; QoS guided GA; crossover operator; distribution scheduling; encoding mechanism; execution time consumption reduction; fitness function; genetic algorithm; grid resource scheduling algorithm; grid task scheduling; mutation operator; resource utilization; selection operator; Bandwidth; Costs; Encoding; Genetic algorithms; Genetic engineering; Genetic mutations; Information science; Processor scheduling; Resource management; Scheduling algorithm;
Conference_Titel :
IT in Medicine & Education, 2009. ITIME '09. IEEE International Symposium on
Conference_Location :
Jinan
Print_ISBN :
978-1-4244-3928-7
Electronic_ISBN :
978-1-4244-3930-0
DOI :
10.1109/ITIME.2009.5236264