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Reseach Article
An Improvised Scheduling Algorithm in Cloud Environment
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 169 - Number 10 |
| Year of Publication: 2017 |
| Authors: Snehal Bajaj, Astha Sharma |
10.5120/ijca2017914893
|
Snehal Bajaj, Astha Sharma . An Improvised Scheduling Algorithm in Cloud Environment. International Journal of Computer Applications. 169, 10 ( Jul 2017), 19-23. DOI=10.5120/ijca2017914893
Abstract
The term scheduling implies relegating of the responsibilities to the accessible assets in some model design to finish the entire work. The target of the proposed work is to investigate the existing weighted round robin algorithm and propose a credulous methodology that defeats the downside of the existing algorithm and by consolidating both the analysis and make an enhance model which is more efficient and satisfy the user needs. The existing algorithm is not productive because of vast reaction time, high completion time, extensive turnaround time, high no. of task migration. Objective of this work is to evaluate the proposed scheduling algorithm by considering the capacities of the VM. The proposed algorithm also holds the benefits of the existing and defeating the issues. The algorithm has been compared with Weighted Round Robin(WRR) and Length based WRR it was observed that the Proposed WRR performed better than existing WRR and LWRR. Proposed WRR showed 99% improvement in Finish time over WRR. 20% and 40% improvement was observed in Task migration and Task delayed respectively over LWRR.
References
- B. Mondal, K. Dasgupta, and P. Dutta, “Load balancing in cloud computing using stochastic hill climbing-a soft computing approach,” Procedia Technology, vol. 4, pp. 783–789, 2012.
- F. Xhafa and A. Abraham, Mata-Heuristics for Grid Scheduling Problems, Springer, Berlin, Germany, 2008.
- G. Gharooni-fard, F. Moein-darbari, H. Deldari, and A. Morvaridi, “Scheduling of scientific workflows using a chaos genetic algorithm,” Procedia Computer Science, vol. 1, no. 1, pp. 1445–1454, 2010, International Conference on Computational Science, ICCS 2010.
- H. M. Fard and H. Deldari, “An economic approach for scheduling dependent tasks in grid computing,” in Proceedings of the 11th IEEE International Conference on Computational Science and Engineering (CSE Workshops ’08), pp. 71–76, IEEE, San Paulo, Brazil, July 2008.
- J. Cao, K. Li, and I. Stojmenovic, “Optimal power allocation and load distribution for multiple heterogeneous multicore server processors across clouds and data centers,” IEEE Transactionson Computers, vol. 63, no. 1, pp. 45–58, 2014.
- L. D. Dhinesh Babu and P. Venkata Krishna, “Honey bee behavior inspired load balancing of tasks in cloud computing environments,” Applied Soft Computing Journal, vol. 13, no. 5, pp. 2292–2303, 2013.
- L.-T. Lee, C.-W. Chen, H.-Y. Chang, C.-C. Tang, and K.-C. Pan, “A non-critical path earliest-finish algorithm for interdependent tasks in heterogeneous computing environments,” in Proceedings of the 11th IEEE International Conference on High Performance Computing and Communications (HPCC ’09), pp. 603–608, Seoul, Republic of Korea, June 2009.
- M. Rahman, R. Hassan, R. Ranjan, and R. Buyya, “Adaptive workflow scheduling for dynamic grid and cloud computing environment,” Concurrency and Computation: Practice and Experience, vol. 25, no. 13, pp. 1816–1842, 2013.
- Mohammadreza Mesbahi, Amir Masoud Rahmani, “Load Balancing in Cloud Computing: A State of the Art Survey ”I.J. Modern Education and Computer Science, 2016, 3, 64-78.
- M. Xu, L. Cui, H. Wang, and Y. Bi, “A multiple QoS constrained scheduling strategy of multiple workflows for cloud computing,” in Proceedings of the IEEE International Symposium onParallel and Distributed Processing with Applications (ISPA ’09), pp. 629–634, IEEE, Chengdu, China, August 2009.
- R. Basker, V. Rhymend Uthariaraj, and D. Chitra Devi, “An enhanced scheduling in weighted round robin for the cloud infrastructure services,” International Journal of Recent Advance in Engineering & Technology, vol. 2, no. 3, pp. 81–86, 2014.
- R. N. Calheiros and R. Buyya, “Meeting deadlines of scientific workflows in public clouds with tasks replication,” IEEE Transactions on Parallel and Distributed Systems, vol. 25, no. 7, pp. 1787–1796, 2014.
- S. Ghanbari and M. Othman, “A priority based job n scheduling algorithm in cloud computing,” in Proceedings of the International Conference on Advances Science and Contemporary Engineering, pp. 778–785, October 2012.
- Z. Xiao, W. Song, and Q. Chen, “Dynamic resource allocation using virtual machines for cloud computing environment,” IEEE Transactions on Parallel and Distributed Systems, vol. 24, no. 6, pp. 1107–1117, 2013.
- Vijindra and S. Shenai, “Survey on scheduling issues in cloud computing,” Procedia Engineering, vol. 38, pp. 2881–2888, 2012,Proceedings of the International Conference on Modelling Optimization and Computing.
- Z. Yu, F. Menng, and H. Chen, “An efficient list scheduling algorithm of dependent task in grid,” in Proceedings of the 3rd IEEE International Conference on Computer Science and Information Technology (ICCSIT’10), IEEE, Chengdu, China, July2010.
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