A Hybrid QoS-Based Algorithm for Independent Tasks Scheduling in Grid

Author

Shen, Yin-yun ; Li, Xiao-ping ; Wang, Qian ; Yuan, Ying-chun

Author_Institution

Dept. of Comput. Sci. & Eng., Southeast Univ., Nanjing

fYear

2006

fDate

13-16 Aug. 2006

Firstpage

4511

Lastpage

4515

Abstract

According to QoS (quality of service) of computing resources in grid, a 2-tier hybrid algorithm is proposed for independent tasks scheduling with time-cost minimization. QGMM (QoS Guided Min-Min, presented by He Xiao Shan et al., Journal of Computer Science and Technology, 2003) is adopted in the first level to obtain a schedule with optimized completion time. A GA (genetic algorithm) only with mutation operator is used to optimize cost with the same obtained completion time in the second tier. The proposed approach is compared with Min-Min and QGMM, efficient existing heuristics for independent tasks scheduling with completion time minimization. Experimental results show that the proposed approach can get lower cost than the other two with the same completion time as QGMM, which is better than that of Min-Min

Keywords

genetic algorithms; grid computing; minimisation; quality of service; scheduling; 2-tier hybrid algorithm; QoS Guided Min-Min; genetic algorithm; grid computing; hybrid QoS-based algorithm; independent task scheduling; mutation operator; quality of service; time-cost minimization; Computer science; Cost function; Genetic algorithms; Genetic mutations; Grid computing; Helium; Minimization methods; Processor scheduling; Quality of service; Scheduling algorithm; GA; Grid; Quality of Service (QoS); independent task scheduling;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2006 International Conference on

Conference_Location

Dalian, China

Print_ISBN

1-4244-0061-9

Type

conf

DOI

10.1109/ICMLC.2006.259168

Filename

4028866