Abstract
Grid computing is an emerging computing architecture that can solve massive computational problems by making use of large numbers of heterogeneous computers. Job scheduling is an important issue in the high performance Grid computing environment. An appropriate scheduling algorithm can efficiently reduce the response time, turnaround time and further increase the throughput. However, finding an optimal grid scheduling algorithm is intractable. In this paper, we propose a high performance scheduling algorithm based on Fuzzy Neural Networks to resolve this problem. In the proposed algorithm, we apply the Fuzzy Logic technique to evaluate the grid system load status, and adopt the Neural Networks to automatically tune the membership functions. Since there are many factors that influence the system’s load circumstances; as the number of factors increase, it becomes very difficult to set up the system using general experience. We implemented a Fuzzy Neural Network scheduler based on Globus Toolkit 4 to verify the proposed scheduling algorithm performance. NAS Grid Benchmarks (NGB) was utilized to validate the performance of our scheduling approach. The experimental results show that our proposed algorithm can reduce the turnaround time and has better speed-up ratio than previous methods.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Berman, F., Fox, G., Hey, T.: Grid Computing: Making the Global Infrastructure a Reality. John Wiley & Sons, Chichester (2003)
Elmroth, E., Tordsson, J.: An Interoperable, Standards-based Grid Resource Broker and Job Submission Service. In: First International Conference on e-Science and Grid Computing, p. 9 (2005)
Foster, I., Kesselman, C.: The Grid: Blueprint for a New Computing Infrastructure. Morgan Kaufmann, San Francisco (1998)
Foster, I., Kesselman, C., Tuecke, S.: The Anatomy of the Grid: Enabling Scalable Virtual Organizations. International Journal of Supercomputer Applications 15(3), 200–222 (2001)
Foster, I., Kesselman, C., Nick, J., Tuecke, S.: Grid Services for Distributed System Integration. IEEE Computer 35(6), 37–46 (2002)
Frumkin, M., Wijngaart, R.: NAS Grid Benchmarks: A Tool for Grid Space Exploration, pp. 247–255. Kluwer Academic Publishers, Manufactured in The Netherlands (2002)
Globus (2006), http://www.globus.org/toolkit/about.html
Herrera, J., Huedo, E., Montero, R.S., Llorente, I.M.: Loosely-coupled Loop Scheduling in Computational Grids. In: 20th International on Parallel and Distributed Processing Symposium, p. 6 (2006)
Montero, R.S., Huedo, E., Llorente, I.M.: Benchmarking of high throughput computing applications on Grids. Instituto Nacional de Te’cnica Aeroespacial Esteban Terradas (INTA) 32(4), 267–279 (2006)
Phatanapherom, S., Uthayopas, P., Kachitvichyanukul, V.: Dynamic scheduling II: fast simulation model for grid scheduling using HyperSim. In: Proceedings of the 35th conference on Winter simulation, pp. 1494–1500 (2003)
Sabin, G., Sahasrabudhe, V., Sadayappan, P.: On fairness in distributed job scheduling across multiple sites. In: IEEE International Conference on Cluster Computing, pp. 35–44. IEEE, Los Alamitos (2004)
Shin, P.-C.: Design and Implementation of a Resource Broker with Network Performance Model on Grid Computing Environments. Master Thesis (2004)
Snavely, A., Chun, G., Casanova, H., Wijngaart, R., Michael, A.: Benchmarks for Grid Computing: A Review of Ongoing Efforts and Future Directions. ACM Sigmetrics Performance Evaluation Review 30(4), 27–32 (2003)
Song, E., Jeon, Y., Han, S., Jeong, Y.: Hierarchical and Dynamic Information Management Framework on Grid Computing. In: Sha, E., Han, S.-K., Xu, C.-Z., Kim, M.H., Yang, L.T., Xiao, B. (eds.) EUC 2006. LNCS, vol. 4096, pp. 151–161. Springer, Heidelberg (2006)
Yagoubi, B., Slimani, Y.: Dynamic Load Balancing Strategy for Grid Computing. Transactions on Engineering, Computing and Technology 13, 260–265 (2006)
Zhou, J., Yu, K.-M., Chou, C.-H., Yang, L.-A., Luo, Z.-J.: A Dynamic Resource Broker and Fuzzy Logic Based Scheduling Algorithm in Grid Environment. In: International Conference on Adaptive and Natural Computing Algorithms. LNCS, Springer, Heidelberg (accepted, 2007)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Yu, KM., Luo, ZJ., Chou, CH., Chen, CK., Zhou, J. (2007). A Fuzzy Neural Network Based Scheduling Algorithm for Job Assignment on Computational Grids. In: Enokido, T., Barolli, L., Takizawa, M. (eds) Network-Based Information Systems. NBiS 2007. Lecture Notes in Computer Science, vol 4658. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74573-0_55
Download citation
DOI: https://doi.org/10.1007/978-3-540-74573-0_55
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74572-3
Online ISBN: 978-3-540-74573-0
eBook Packages: Computer ScienceComputer Science (R0)