TRP Maximization Technique based Efficient Scheduling in Grid Environment
Keywords:
Grid Environment, Resource Utilization, Maximization, TRP, Job SchedulingAbstract
The problem of heterogeneous job scheduling in grid environment is well studied. Number of approaches considers different factors of resource and process in terms of completion, waiting and throughput. However, the methods suffer to achieve higher performance in scheduling in grid environment. To improve the performance, an efficient TRP maximization algorithm is presented in this paper. First, the method identifies list of processes and their required resource with their hold time. Based on the information obtained, a set of two hop sequences are generated for each resource available. For each two hop sequence, the method compute throughput maximization support, resource utilization maximization factor and process completion maximization factor. Using all these, a scheduling maximization support has been estimated. Based on the support measure a single one has been selected for each resource available. The same will be iterated for each level of scheduling and the method produces higher efficiency in scheduling. The performance of scheduling has been improved with less waiting time.
References
Kwok, Y.K., Maciejewski, A.A., Siegel, H.J., Ahmad, I., Ghafoor, A.: A semi-static approach to mapping dynamic iterative tasks onto heterogeneous computing system. Journal of Parallel and Distributed Computing 66, 77–98 (2006)
Dogana, A., Özgüner, F.: Scheduling of a meta-task with QoS requirements in heterogeneous computing systems. Journal of Parallel and Distributed Computing 66(2), 181–196 (2006)
J. Preethi1 , R. Jayasudha2,Load Balancing and Bandwidth in Grid Computing Environments , International Journal of scientific research in computer science, engineering and technology, vol.2, issue 2, 2017.
Y. H. Lee, S. Leu, R. S. Chang, "Improving job scheduling algorithms in a grid environment", Future generation computer systems, vol. 27, no. 8, pp. 991-998, 2011.
P. Keerthika, N. Kasthuri, "A hybrid scheduling algorithm with load balancing for computational grid", International Journal of Advanced Science and Technology, vol. 58, pp. 13-28, 2013.
Chang Ruay-Shiung, Lin Chih-Yuan, Lin Chun-Fu, "An adaptive scoring job scheduling algorithm for grid computing", Information Sciences, vol. 207, pp. 79-89, 2012.
M. Yaghoobi, A. Fanian, H. Khajemohammadi, T. A. Gulliver, "A non-cooperative game theory approach to optimize workflow scheduling in grid computing", Communication Computers and Signal Processing (PACRIM), 2013.
Z. Mousavinasab, R. Entezari-Maleki, A. Movaghar, "A bee colony task scheduling algorithm in computational grids" in Digital Information Processing and Communications, Springer Berlin Heidelberg, pp. 200-210, 2011.
J.Y Maipan-Uku1 , I. Rabiu2 , Dr. Amit Mishra3, Immediate/Batch Mode Scheduling Algorithms For Grid Computing: A Review,International Journal Of Research, 2017.
Amalarethinam, G.D.I. & Kfatheen V.S., (2014). Max-min Average Algorithm for Scheduling Tasks in Grid Computing Systems. International Journal of Computer Science and Information Technologies. 3, pp. 3659-62.
Cao, L., Liu, X., Wang, H., & Zhang, Z. (2014). OPT-Min-Min Scheduling Algorithm of Grid Resources. Journal of Software, 9 (7), pp. 1868-1875.
Hemamalini, M., & Srinath, M. V. (2015). Memory Constrained Load Shared Minimum Execution Time Grid Task Scheduling Algorithm in a Heterogeneous Environment. Indian Journal of Science and Technology, 8 (15)
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors contributing to this journal agree to publish their articles under the Creative Commons Attribution 4.0 International License, allowing third parties to share their work (copy, distribute, transmit) and to adapt it, under the condition that the authors are given credit and that in the event of reuse or distribution, the terms of this license are made clear.
