A Concern towards Job scheduling In Cluster Computing
Main Article Content
Abstract
Cluster computing is one of the novel and effective approach in parallel processing. As cluster installation helps to satisfy everincreasing computing demands, so advance schedulers can help in improving resource utilization rate and quality of service. In this paper, we focus on features for developing external schedulers that can complement features of resource manager and enable sophisticated scheduling.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
IJCERT Policy:
The published work presented in this paper is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. This means that the content of this paper can be shared, copied, and redistributed in any medium or format, as long as the original author is properly attributed. Additionally, any derivative works based on this paper must also be licensed under the same terms. This licensing agreement allows for broad dissemination and use of the work while maintaining the author's rights and recognition.
By submitting this paper to IJCERT, the author(s) agree to these licensing terms and confirm that the work is original and does not infringe on any third-party copyright or intellectual property rights.
References
Abawajy, J.H..2003 Parallel job scheduling on multicluster computing system. Cluster Computing, IEEE 2003.
C. Ernemann, V. Hamscher, R. Yahyapour. 2004 Benefits of Global Grid Computing for Job Scheduling. In proceedings of the Fifth IEEE/ACM International Workshop on Grid Computing (GRID’04), 374-379, November 2004.
Chee Shin Yeo,Rajkumar Buyya. 2006 A taxonomy of market-based resource management systems for utility-driven cluster computing. Published in Journal Software—Practice & Experience archive VoL. 36, No.13, November 2006, 1381 - 1419.
E. Carsten, et al. 2002 On advantages of grid computing for parallel job scheduling.in: Proceedings of the 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid, CCGrid’02, 2002, pp. 39–39.
Ernemann, C., Hamscher, V., Streit, A., Yahyapour, R. 2002 Enhanced Algorithms for Multi-Site Scheduling. In: Parashar, M. (ed.) GRID 2002. LNCS, vol. 2536, pp. 219–231. Springer, Heidelberg (2002).
http://www.adaptivecomputing.com/products/open -source/maui/.
J. Ramírez-Alcaraz, et al. 2011 Job allocation strategies with user run time estimates for online scheduling in hierarchical grids. Journal of Grid Computing (2011), Vol.9, 95–116.
K.-C. Huang, H.-Y. Chang. 2006 An integrated processor allocation and job scheduling approach to workload management on computing grid. In Proceedings of the International Conference on Parallel and Distributed Processing Techniques and Applications, PDPTA’06, 2006, pp. 703–709, Las Vegas, USA.
K.-C. Huang, et al. 2007 Towards feasible and effective load sharing in a heterogeneous computational grid. In Proceedings of the 2nd International Conference on Advances in Grid and Pervasive Computing, GPC’07.
Marco Pasquali, Ranieri Baraglia, Gabriele Capannini, Laura Ricci, Domenico Laforenza. 2011 A multi-level scheduler for batch jobs on grids. The Journal of Supercomputing, Vol. 57, No. 1, 81-98, July 2011.
M. Hovestadt, O. Kao, A. Keller, and A. 2003 Streit. Scheduling in HPC Resource Management Systems: Queuing vs. Planning. In D. G. Feitelson and L.Rudolph, editor, Proc. of the 9th Workshop on JobScheduling Strategies for Parallel Processing, vol. 2862 of Lecture Notes in Computer Science,1– 20, Springer, 2003.
P.-C. Shih, et al.. 2010 Improving grid performance through processor allocation considering both speed heterogeneity and resource fragmentation. The Journal of Supercomputing (2010), 1–27.