Resource Scheduling in Cloud: A Comparative Study
Bhupesh Kumar Dewangan1 , Amit Agarwal2 , Venkatadri M3 , Ashutosh Pasricha4
Section:Review Paper, Product Type: Journal Paper
Volume-6 ,
Issue-8 , Page no. 168-173, Aug-2018
CrossRef-DOI: https://doi.org/10.26438/ijcse/v6i8.168173
Online published on Aug 31, 2018
Copyright © Bhupesh Kumar Dewangan, Amit Agarwal, Venkatadri M, Ashutosh Pasricha . 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.
View this paper at Google Scholar | DPI Digital Library
How to Cite this Paper
- IEEE Citation
- MLA Citation
- APA Citation
- BibTex Citation
- RIS Citation
IEEE Style Citation: Bhupesh Kumar Dewangan, Amit Agarwal, Venkatadri M, Ashutosh Pasricha, “Resource Scheduling in Cloud: A Comparative Study,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.8, pp.168-173, 2018.
MLA Style Citation: Bhupesh Kumar Dewangan, Amit Agarwal, Venkatadri M, Ashutosh Pasricha "Resource Scheduling in Cloud: A Comparative Study." International Journal of Computer Sciences and Engineering 6.8 (2018): 168-173.
APA Style Citation: Bhupesh Kumar Dewangan, Amit Agarwal, Venkatadri M, Ashutosh Pasricha, (2018). Resource Scheduling in Cloud: A Comparative Study. International Journal of Computer Sciences and Engineering, 6(8), 168-173.
BibTex Style Citation:
@article{Dewangan_2018,
author = {Bhupesh Kumar Dewangan, Amit Agarwal, Venkatadri M, Ashutosh Pasricha},
title = {Resource Scheduling in Cloud: A Comparative Study},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {8 2018},
volume = {6},
Issue = {8},
month = {8},
year = {2018},
issn = {2347-2693},
pages = {168-173},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=2672},
doi = {https://doi.org/10.26438/ijcse/v6i8.168173}
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i8.168173}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=2672
TI - Resource Scheduling in Cloud: A Comparative Study
T2 - International Journal of Computer Sciences and Engineering
AU - Bhupesh Kumar Dewangan, Amit Agarwal, Venkatadri M, Ashutosh Pasricha
PY - 2018
DA - 2018/08/31
PB - IJCSE, Indore, INDIA
SP - 168-173
IS - 8
VL - 6
SN - 2347-2693
ER -
VIEWS | XML | |
1092 | 396 downloads | 318 downloads |
Abstract
Cloud computing provides a platform where services are facilitating to the cloud user through the web, either free of cost or lease base. The cloud user and demands are increasing, due to this large number of service request are submitting to the cloud service provider. To manage those service requests, scheduling plays a key role for the service provider to manage their resource and operational cost. In this paper, the state of art survey has been carried out on recent developments in resource scheduling algorithms for cloud computing. This paper provides the comparative analysis of all the surveyed algorithms in terms of different performance metrics. The observation of the survey provides some research gaps to improve the efficiency of the existing resource management system.
Key-Words / Index Term
Cloud Computing, Resource Scheduling, Performance, Efficiency
References
[1] Bhupesh Kumar Dewangan, and Amit Agarwal. “Credential and Security Issues on Cloud Service Models” in the proceeding of 2nd IEEE International Conference on Next Generation Computing Technology India pp 1-8. 2017
[2] Peter Mell and T. G. “The NIST Definition of Cloud Computing”. National Institute of Standards Technology Special Publication. pp 80-145. 2011
[3] SSukhpal Singh and Inder. “STAR: SLA-aware Autonomic Management of Cloud Resources”. Ieee Transactions On Cloud Computing, pp. 1-14. 2016.
[4] Atul Vikas Lakra and D. K. “Multi-Objective Tasks Scheduling Algorithm for Cloud Computing Throughput Optimization”. International Conference on Intelligent Computing, Communication & Convergence Bhubaneswar, Odisha, India: ELSEVIER. pp. 107-113. 2015.
[5] Saraswathi, A. T., Kalaashri, Y. R. A., and Padmavathi, S. “Dynamic resource allocation scheme in cloud computing”. Procedia Computer Science, Vol 47, pp. 30-36. 2015.
[6] Aarti Singh and D. J. “Autonomous Agent-Based Load Balancing Algorithm in Cloud Computing”. International Conference on Advanced Computing Technologies and Applications. pp. 832-841. 2015
[7] Antony Thomasa and K. G. “Credit Based Scheduling Algorithm in Cloud Computing Environment”. International Conference on Information and Communication Technologies pp. 913-920. 2014.
[8] Maria Alejandra Rodriguez and R. B. “Deadline Based Resource Provisioning and Scheduling Algorithm for Scientific Workflows on Clouds”. IEEE Transactions On Cloud Computing, Vol 2, Issue 2, pp. 222-235. 2014
[9] Ji Lia, L. F. An Greedy-Based Job Scheduling Algorithm in Cloud Computing. JOURNAL OF SOFTWARE, 9 (4), (2014). (pp. 921-925).
[10] Amit Agarwal, S. J.. Efficient Optimal Algorithm of Task Scheduling in Cloud Environment. International Journal of Computer Trends and Technology (IJCTT), 9 (7), (2014). 344-349.
[11] Mihaela-Andreea VASILE and F. P. “Resource-Aware Hybrid Scheduling Algorithm in Heterogeneous Distributed Computing”. Future Generation Computer Systems, pp. 1-22. 2014
[12] Javanmardi, S., Shojafar, M., Amendola, D., Cordeschi, N., Liu, H., and Abraham, A. “Hybrid job scheduling algorithm for cloud computing environment” In Proceedings of the Fifth International Conference on Innovations in Bio-Inspired Computing and Applications IBICA pp. 43-52. 2014.
[13] Shanthi and A. P. A “Load Balancing Model Using Firefly Algorithm In Cloud Computing”. Journal of Computer Science, Vol 10 Issue 7, pp. 1156-1165. 2014
[14] Krishna, P. V. “Honey bee behavior inspired load balancing of tasks in cloud computing environments”. Applied Soft Computing, Vol 13, Issue 5, pp. 2292-2303. 2013
[15] Jing Liu, and X. L. “Job scheduling algorithm for cloud computing based on particle swarm optimization”. Advanced Materials Research, Vol 66, Issue 2, pp. 957-960. 2013
[16] Liu, J., Luo, X. G., Zhang, X. M., Zhang, F., & Li, B. N. “Job scheduling model for cloud computing based on multi-objective genetic algorithm”. International Journal of Computer Science Issues (IJCSI), Vol 10, Issue 1, pp. 134-139. 2013
[17] Tsai, J. T., Fang, J. C., & Chou, J. H. “Optimized task scheduling and resource allocation on cloud computing environment using improved differential evolution algorithm”. Computers & Operations Research, Vol 40 Issue 12, pp. 3045-3055. 2013
[18] Nima Jafari Navimipour, F. S. “Task Scheduling in the Cloud Computing Based on the Cuckoo Search Algorithm”. International Journal of Modeling and Optimization, Vol 5 Issue 1. pp. 44-47. 2015
[19] Abrishami, S., Naghibzadeh, M., & Epema, D. H. “Deadline-constrained workflow scheduling algorithms for infrastructure as a service clouds”. Future Generation Computer Systems, Vol 29 Issue 1, pp. 158-169. 2013
[20] Salot, P. “A survey of various scheduling algorithm in cloud computing environment”. International Journal of Research in Engineering and Technology, Vol 2 Issue 2, pp. 131-135. 2013
[21] Vikas Mangotra and Richa Dogra, “Cloud Reliability Enhancement Mechanism: A Survey”, International Journal on Scientific Research in Computer Science and Engineering, Vol.6, Issue.3, pp.31-34. 2018.
[22] Anjum Mohd Aslam and Mantripatji Jaur, “A Review on energy efficient technique in green cloud: open research challenges and issues”, International Journal on Scientific Research in Computer Science and Engineering, Vol.6, Issue.3, pp.44-50. 2018