DocumentCode :
2900705
Title :
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
Link To Document :
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