Login Register Cart 0
Generic placeholder image

Recent Advances in Computer Science and Communications

Editor-in-Chief

ISSN (Print): 2666-2558
ISSN (Online): 2666-2566

Back
Journal Home About Journal Editorial Board Current Issue Volumes/Issues
Subscribe
Research Article

An Efficient Multi-Core Resource Allocation using the Multi-Level Objective Functions in Cloud Environment

Author(s): Siva Rama Krishna* and Mohammed Ali Hussain

Volume 13, Issue 5, 2020

Page: [957 - 964] Pages: 8

DOI: 10.2174/2666255813666200213105651

Price: $65

Abstract

Background: In recent years, the computational memory and energy conservation have become a major problem in cloud computing environment due to the increase in data size and computing resources. Since, most of the different cloud providers offer different cloud services and resources use limited number of user’s applications.

Objective: The main objective of this work is to design and implement a cloud resource allocation and resources scheduling model in the cloud environment.

Methods: In the proposed model, a novel cloud server to resource management technique is proposed on real-time cloud environment to minimize the cost and time. In this model different types of cloud resources and its services are scheduled using multi-level objective constraint programming. Proposed cloud server-based resource allocation model is based on optimization functions to minimize the resource allocation time and cost.

Results: Experimental results proved that the proposed model has high computational resource allocation time and cost compared to the existing resource allocation models.

Conclusion: This cloud service and resource optimization model is efficiently implemented and tested in real-time cloud instances with different types of services and resource sets.

Keywords: Cloud resources, cloud servers, optimization functions, amazon instances, resource allocation, user application.

Graphical Abstract

[1]
Z. Lu, S. Takashige, Y. Sugita, T. Morimura, and Y. Kudo, "An analysis and comparison of cloud data center energy-efficient resource management technology", Int. J. Serv. Comput. (IJSC), vol. 2, no. 4, pp. 32-51, 2014.
[http://dx.doi.org/10.29268/stsc.2014.2.4.3]
[2]
B. Jennings, and R. Stadler, "Resource management in clouds: Survey and research challenges", J. Netw. Syst. Manage., vol. 23, no. 3, pp. 567-619, 2015.
[http://dx.doi.org/10.1007/s10922-014-9307-7]
[3]
R.N. Calheiros, R. Ranjan, A. Beloglazov, C.A.F.D. Rose, and R. Buyya, "Cloudsim: A toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms", Softw. Pract. Exper., vol. 41, no. 1, pp. 23-50, 2011.
[http://dx.doi.org/10.1002/spe.995]
[4]
J. Son, A.V. Dastjerdi, R.N. Calheiros, X. Ji, Y. Yoon, and R. Buyya, "Cloudsimsdn: Modeling and simulation of software-defined cloud data centers 2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing,",
[http://dx.doi.org/10.1109/CCGrid.2015.87]
[5]
Y. Hu, J. Wong, G. Iszlai, and M. Litoiu, "Resource provisioning for cloud computing", In Proceedings of the 2009 Conference of the Center for Advanced Studies on Collaborative Research Ontario Canada,, pp. 101–111-, 2009.
[6]
Z. Xiao, W.J. Song, and Q. Chen, "Dynamic resource allocation using virtual machines for cloud computing environment", IEEE Trans. Parallel Distrib. Syst., vol. 24, no. 6, pp. 1107-1117, 2013.
[http://dx.doi.org/10.1109/TPDS.2012.283]
[7]
S. Keshav, An engineering approach to computer networking: Atm networks, the internet, and the telephone network.Reading., Addison Wesley: Boston, MA, 1997, p. 11997.
[8]
S. Radhakrishnan, R. Pan, A. Vahdat, and G. Varghese, "Netshare and stochastic netshare: Predictable bandwidth allocation for data centers", Comput. Commun. Rev., vol. 42, no. 3, pp. 5-11, 2012.
[http://dx.doi.org/10.1145/2317307.2317309]
[9]
A.F. Barsoum, and M.A. Hasan, "Provable multicopy dynamic data possession in cloud computing systems", IEEE Trans. Inf. Forensics Security, vol. 10, no. 3, pp. 485-497, 2017.
[http://dx.doi.org/10.1109/TIFS.2014.2384391]
[10]
D. Li, C. Chen, J. Guan, and Y. Zhang, "DCloud: Deadline-aware resource allocation for cloud computing jobs", IEEE Trans. Parallel Distrib. Syst., vol. 27, no. 8, pp. 2248-2260, 2016.
[http://dx.doi.org/10.1109/TPDS.2015.2489646]
[11]
C. Papagianni, A. Leivadeas, S. Papavassiliou, and V. Maglaris, "On the optimal allocation of virtual resources in cloud computing networks", IEEE Trans. Comput., vol. 62, no. 6, pp. 1060-1071, 2013.
[http://dx.doi.org/10.1109/TC.2013.31]
[12]
N.A. Toosi, K. Vanmechelen, F. Khodadadi, and R. Buyya, "An auction mechanism for cloud spot markets", ACM TAAS, vol. 11, no. 1, pp. 1-33, 2016.
[http://dx.doi.org/10.1145/2843945]
[13]
W.Z. Zhang, H.L. Zhang, and D. Zhang, "Memory cooperation optimization strategies of multiple virtual machines in cloud computing environment", Chinese J. Computers, vol. 34, pp. 2266-2277, 2011.

Rights & Permissions Print Cite
Article Metrics
3
© 2024 Bentham Science Publishers | Privacy Policy