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Comparative Based Study of Scheduling Algorithms for Resource Management in Cloud Computing Environment

Rajesh Verma1

Section:Review Paper, Product Type: Isroset-Journal
Vol.1 , Issue.4 , pp.17-23, Jul-2013


Online published on Aug 31, 2013


Copyright © Rajesh Verma . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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IEEE Style Citation: Rajesh Verma , “Comparative Based Study of Scheduling Algorithms for Resource Management in Cloud Computing Environment,” International Journal of Scientific Research in Computer Science and Engineering, Vol.1, Issue.4, pp.17-23, 2013.

MLA Style Citation: Rajesh Verma "Comparative Based Study of Scheduling Algorithms for Resource Management in Cloud Computing Environment." International Journal of Scientific Research in Computer Science and Engineering 1.4 (2013): 17-23.

APA Style Citation: Rajesh Verma , (2013). Comparative Based Study of Scheduling Algorithms for Resource Management in Cloud Computing Environment. International Journal of Scientific Research in Computer Science and Engineering, 1(4), 17-23.

BibTex Style Citation:
@article{Verma_2013,
author = {Rajesh Verma },
title = {Comparative Based Study of Scheduling Algorithms for Resource Management in Cloud Computing Environment},
journal = {International Journal of Scientific Research in Computer Science and Engineering},
issue_date = {7 2013},
volume = {1},
Issue = {4},
month = {7},
year = {2013},
issn = {2347-2693},
pages = {17-23},
url = {https://www.isroset.org/journal/IJSRCSE/full_paper_view.php?paper_id=67},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.isroset.org/journal/IJSRCSE/full_paper_view.php?paper_id=67
TI - Comparative Based Study of Scheduling Algorithms for Resource Management in Cloud Computing Environment
T2 - International Journal of Scientific Research in Computer Science and Engineering
AU - Rajesh Verma
PY - 2013
DA - 2013/08/31
PB - IJCSE, Indore, INDIA
SP - 17-23
IS - 4
VL - 1
SN - 2347-2693
ER -

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Abstract :
Cloud Computing (CC) is emerging as the next generation platform which would facilitate the user s per requirement. It provides a number of benefits which could not otherwise be realized. The p e efficient access to remote and geographically distributed resources. A scheduling algorithm is n o the different resources. There are different types of resource scheduling technologies in CC envi ented at different levels based on different parameters like cost, performance, resource utilization, tances, throughput, bandwidth, resource availability etc. In this research paper various types of r algorithms that provide efficient cloud services have been surveyed and analyzed. Based on the st a classification of the scheduling algorithms on the basis of selected features has been presented.

Key-Words / Index Term :
Cloud computing;Scheduling algorithms; Resource allocation; Open source; Virtual machine

References :
[1] I. Foster, Y. Zhao, I. Raicu and S. Lu, "Cloud Computing and Grid Computing 360 Degree Compared", Grid Computing Environments Workshop, Austin, 2008.
[2] G. Boss, P. Malladi, D. Quan, L. Legregni and H. Hall, Cloud Computing (White Paper), IBM, october2007, http://download.boulder.ibm.com/ibmdl/pub/software/dw/wes/hipods/ Cloud_computing_wp_final_8Oct.pdf , accessed on May. 19, 2009.
[3] R. Buyya, C. S. Yeo, and S. Venugopal, “Market-Oriented Cloud and Atmospheric Computing: Hype, Reality, and Vision”, Proc. of 10th IEEE International Conference on High Performance Computing and Communications (HPCC-08), 5-13, Dalian, China, September, 2008.
[4] I. Gandotra,P.Abrol,”Cloud computing :A new paradigm for Education”,ICAET10, 2010, pp 92.
[5] I. Gandotra, P Abrol,”cloud computing a new Era of Ecommerce”, book chapter in Strategic Service management, Published by Excel Books, pp 228, 2010
[6] S. Sadhasivam , N.Nagaveni ,R. Jayarani,and R. Vasanth Ram , “Design and Implementation of an efficient Two-level Scheduler for Cloud Computing Environment’, International Conference on Advances in Recent Technologies in Communication and Computing,2009.
[7] Rodrigo N. Calheiros, Rajiv Ranjan1, César A. F. De Rose, and Rajkumar Buyya,”CloudSim: A Novel Framework for Modeling and Simulation of Cloud Computing Infrastructures and Services”.
[8] J. Singh, B. Patra, S. P. Singh ,”An Algorithm to Reduce the Time Complexity of Earliest Deadline First Scheduling Algorithm in Real-Time System”, (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 2, No.2, February 2011
[9] Shin-ichi Kuribayash”,Optimal Joint Multiple Resource Allocation Method for Cloud Computing Environments”, International Journal of Research and Reviews in Computer Science (IJRRCS) Vol. 2, No. 1, March 2011.
[10] A. Avanes and J. Freytag,,” Adaptive Workflow Scheduling under Resource Allocation Constraints and Network Dynamics”. Proc. VLDB Endow, 1(2), August 2008, pp 1631-1637.
[11] K. Liu, Y. Yang, J. Chen, X. Liu, D. Yuan , H. Jin, “A Compromised-Time-Cost Scheduling Algorithm in SwinDeW-C for Instance-intensive Cost-Constrained Workflows on Cloud Computing Platform”, Int. Journal of High Performance Computing Applications, Volume 24 Issue 4, 2010.
[12] D. A. Menasc and E.Casalicchio, “A Framework for Resource Allocation in Grid Computing”, Proc. of the 12th Annual International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems, Volendam, The Netherlands, October, 2004,pp 259-267.
[13] J. Yu, R. Buyya and C. K. Tham, “A Cost-based Scheduling of Scientific Workflow Applications on Utility Grids”, Proc. of the 1st IEEE International Conference on e-Science and Grid Computing, Melbourne, Australia, December 2005 , pp140-147.
[14] Young Choon Lee, Chen Wang, Albert Y. Zomaya, Bing Bing Zhou,”Profit-driven Service Request Scheduling in Clouds”, 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing,2010
[15] B Sotomayor, R S. Montero, I M. Llorente, and I Foster , “An Open Source Solution for Virtual Infrastructure Management in Private and Hybrid Clouds”, IEEE INTERNET COMPUTING, SPECIAL ISSUE ON CLOUD COMPUTING ,July 2009
[16] Nada M. A. Al Salami , “Ant Colony Optimization Algorithm”, UbiCC Journal, Volume 4, Number 3, August 2009
[17] Sachin V. Solanki, B. Minal Gour and C. Dr.(Mrs.) A. R. Mahajan, “An Overview of Different Job Scheduling Heuristics Strategies for Cloud Computing Environment”, www.icett.com,2011
[18] J. Yu and R. Buyya, “Scheduling Scientific Workflow Applications with Deadline and Budget Constraints using Genetic Algorithms”, Scientific Programming Journal, 14(3-4), 217-230, IOS Press, 2006.
[19] R. Sakellariou, H. Zhao, E. Tsiakkouri, and M. D. Dikaiakos, “Scheduling Workflows with Budget Constraints, CoreGRID Workshop on Integrated research in Grid Computing, “ ,Technical Report TR-05-22, University of Pisa, Dipartimento Di Informatica, Pisa, Italy, November 2005.
[20] Bo Li, J. Li, J. Huai, T. Wo, Q. Li, L. Zhong, ”Ena,Cloud: An Energy-saving Application Live Placement Approach for Cloud Computing Environments”, in Proc. IEEE Int. Conf. Cloud Computing, ,IEEE, 2009, pp 17-24.
[21] R. Buyya, A. Beloglazov, J. Abawajy ,”Energy-Efficient Management of Data Center Resources for Cloud Computing: A Vision, Architectural Elements, and Open Challenges”, in Proc. of the Int. Conf. on Parallel and Distributed Processing Techniques and Applications (PDPTA 2010), Las Vegas, USA, July 12-15, 2010.
[22] T. V. T. Duy, Y. Sato, Y Inoguchi, ”Performance Evaluation of a Green Scheduling Algorithm for Energy Savings in Cloud Computing”, IEEE, 2010.
[23] http://www.rackspace.com/cloud/cloud_hosting_products/loadbalancers/technology/
[24] Ke Liu1, Jinjun Chen, Yun Yang and Hai Jin,” A throughput maximization strategy for scheduling transaction-intensive workflows on SwinDeW-G”, Concurrency Computat.: Pract. Exper. 2008; 20:1807–1820 Published online 10 July 2008 inWiley InterScience (www.interscience.wiley.com). DOI: 10.1002/cpe.1316
[25] H. Zhong, K. Tao, X. Zhang, ”An Approach to Optimized Resource Scheduling Algorithm for Open-source Cloud Systems”, in Proc.chinagrid2010,pp. 124-129 IEEE ,2010.
[26] S Banerjee, I Mukherjee, and P.K. Mahanti “Cloud Computing Initiative using Modified Ant Colony Framework” , World Academy of Science, Engineering and Technology, , 56 2009, pp 221-224
[27] S Pandey1, LinlinWu, S M Guru, R Buyya1, “A Particle Swarm Optimization-based Heuristic for Scheduling Workflow Applications in Cloud Computing Environments” , in Proc.24th IEEE Int. Conf. on Advanced Information Networking and Applications, IEEE, 2010, pp. 400-407.
[28] http://opennebula.org/documentation:archives:rel2.0:schg
[29] D Dutta,R C Joshi ,“A Genetic –Algorithm Approach to Cost-Based Multi-QoS Job Scheduling in Cloud Computing Environment”, International Conference and Workshop on Emerging Trends in Technology (ICWET 2011) – TCET, Mumbai, India,2011
[30] J. Yu and R. Buyya, “Workflow Schdeduling Algorithms for Grid Computing, Technical Report”, GRIDS-TR-2007-10, Grid Computing and Distributed Systems Laboratory, The University of Melbourne, Australia, May 2007.
[31] Selvarani, S.; Sadhasivam, G.S.,”Improved cost-based algorithm for task scheduling in cloud computing”, Computational Intelligence and Computing Research (ICCIC), 2010 IEEE International conference on 2010 , pp 1–5
[32] Meng Xu, Lizhen Cui, Haiyang Wang, Yanbing Bi, “A Multiple QoS Constrained Scheduling Strategy of Multiple Workflows for Cloud Computing”, in 2009 IEEE International Symposium on Parallel and Distributed Processing.

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