Research on Gird Task Scheduling Based on Ant Colony Algorithm

Chen Qi; Hou Ming

doi:10.4028/www.scientific.net/AMR.129-131.1438

Paper Titles

Modeling of Sensor Assignment in Cooperative Target Tracking
p.1400

Study on Schemes for Seamless Multicast Handover in the Proxy Mobile IPv6 Based on Wireless Networks
p.1405

Study of High-Speed Processing for Network Intrusion Detection System
p.1410

Research of Earth Berm and the Simplified Analysis
p.1415

Research and Implementation of Intrusion Detection System Based on Artificial Neural Network
p.1421

Log-Based Network Security Audit System Research and Design
p.1426

Design and Implementation of Video Acquisition System Based on Embedded Linux
p.1432

Research on Gird Task Scheduling Based on Ant Colony Algorithm
p.1438

Logging-On System Integrated B/S and C/S Based on RSA Asymmetrical Encryption and Web Service
p.1444

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 129-131Research on Gird Task Scheduling Based on Ant...

Research on Gird Task Scheduling Based on Ant Colony Algorithm

Abstract:

Combining with the advantages of ant colony algorithm to solve optimization problem, this paper designs a grid resource allocation model and task scheduling system based on ant colony algorithm. The algorithm can not only locally update for the pheromone in the allocation of grid computing resources, but also can entirely update for the pheromone after the completion of grid computing resources. Experimental results show that the ant colony algorithm can effectively achieve a reasonable task scheduling and load balancing, its application in the task scheduling in grid environment is very successful.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 129-131)

Pages:

1438-1443

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.129-131.1438

Citation:

Cite this paper

Online since:

August 2010

Authors:

Chen Qi, Hou Ming

Keywords:

ACO (Ant Colony Optimal Algorithm), Gird, Load Balancing, Task Scheduling

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Stefka Fidanova, Mariya Durchova, Ant Algorithms for grid scheduling problem, Springer Berlin/Heidelberg, LNCS 3743, pp.405-412, (2006).

DOI: 10.1007/11666806_46

Google Scholar

[2] Foster, C. Kesselman, S. Tuecke. The Anatomy of the Grid: Enabling Scalable Virtual Organizations, the International Journal of Supercomputer Applications, 2001, 15(3): 200-222.

DOI: 10.1177/109434200101500302

Google Scholar

[3] Mnaish Parashar, ZhenLi, HuaLiu, Vincent Matossian, CristinaSehmidt, Enabling Autonomic, Grid Applications: Requirements, Models and Infrastructure, Self-Star Properties in Complex Information System: Conceptual and Practical Foundations, Springer-Verlag, Berlin, 2005, 273-290.

DOI: 10.1007/11428589_18

Google Scholar

[4] Abraham, Buyya R. Nature's heuristics for scheduling jobs on computational grids[C]. Proceedings of the 8th Int Conf. on Advanced Computing and Communications, New Delhi: Tata McGraw-Hill Publishing, 2000, 45-52.

Google Scholar

[5] Rajkumar Buyya and Kris Bubendorfer (eds. ), Market Oriented Grid and Utility Computing, Wiley Press, New York, USA, 2008: 22-32.

Google Scholar

[6] Chen Shudong, Zhang Wenju, Ma Fayuan, et al. A novel agent-based load balancing algorithm for Grid computing [A], Lecture notes in computer science [C]. Berlin. German: Springer-Verlag, 2004: 156-163.

DOI: 10.1007/978-3-540-30207-0_20

Google Scholar

[7] He XS, Sun XH, Von Laszewski G. A QoS guided scheduling algorithm for grid computing. Journal of Computer Science and Technology [J]. 2003, 18(4): 442-451.

DOI: 10.1007/bf02948918

Google Scholar

[8] Nabrzyski J, Jennifer M S, Weglarz J. Grid Resource Management: State of the Art and Future Trends [M]. Boston: Kluwer Academic Publishers, 2003. 36244.

Google Scholar