An improved ant algorithm for job scheduling in grid computing

Author

Yan, Hui ; Shen, Xue-Qin ; Li, Xing ; Wu, Ming-Hui

Author_Institution

Dept. of Comput., Zhejiang Univ. City Coll., Hangzhou, China

Volume

5

fYear

2005

fDate

18-21 Aug. 2005

Firstpage

2957

Abstract

In this paper, we propose an improved ant algorithm for job scheduling in grid computing. The new algorithm is based on the general ant adaptive scheduling heuristics and an added in load balancing guide component. The load balancing factor, related to the job finishing rate, is introduced to change the pheromone. That makes the job finishing rate at different resource being similar and the ability of the systematic load balancing improved. It has been successfully tested in a simulation grid environment. The experiments show that the new ant heuristic method can lead to significant performance in various applications.

Keywords

artificial life; grid computing; processor scheduling; resource allocation; ant adaptive scheduling heuristics; grid computing; job finishing rate; job scheduling; load balancing; Adaptive scheduling; Cities and towns; Computational modeling; Educational institutions; Finishing; Grid computing; Load management; Processor scheduling; Scheduling algorithm; Testing; ant algorithm; grid; job scheduling; load balancing;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on

Conference_Location

Guangzhou, China

Print_ISBN

0-7803-9091-1

Type

conf

DOI

10.1109/ICMLC.2005.1527448

Filename

1527448