Resource Allocation in Cloud Computing: A Review
Keywords:
Cloud computing, service models, virtualization, resource allocationAbstract
Cloud computing has quickly appeared as a outstanding standard for contributing IT infrastructure, resources and services on a pay-per-use basis from the last few years. Cloud computing is a promising technology and number of researches has been proposed for solving the issues faced by the cloud. There are number of challenges that a cloud is facing, from which, the main challenge is the resource allocation technique. Cloud permits the provisioning of resource on-demand. This procedure of allocating and re-allocating of resources is the way to accommodate the impulsive demands with an improvement of return on investment by means of infrastructure with the support of cloud. Resource allocation is the method in which the resources are allocated to each cloud user by the providers of cloud services. The varied factors like response time, cost, and dynamic allocation need to be acknowledged while choosing a technique of resource allocation. Though, in spite of the recent growth in cloud computing market, number of problems in the resource allocation remains unaddressed. This source course has introduced the significant concepts and the mechanisms of cloud computing and deliberates some research question on the topic while emphasizing on challenges and state-of-art solutions in the resource allocation. The article will expectantly inspire the future researchers to come up with the optimal and smarter resource allocation algorithms and structures to build up the paradigm of cloud computing
References
Armbrust, M., Fox, A., Griffith, R., Joseph, A. D., Katz, R., Konwinski, A., ... & Zaharia, M. (2010). A view of cloud computing. Communications of the ACM, 53(4), 5058.
Qian, L., Luo, Z., Du, Y., & Guo, L. (2009). Cloud computing: An overview. Cloud computing, 626-631.
Dillon, T., Wu, C., & Chang, E. (2010, April). Cloud computing: issues and challenges. In Advanced Information Networking and Applications (AINA), 2010 24th IEEE International Conference on (pp. 27-33). Ieee.
Armbrust, M., Fox, A., Griffith, R., Joseph, A. D., Katz,
R., Konwinski, A., ... & Zaharia, M. (2010). A view of
cloud computing. Communications of the ACM, 53(4), 5058.
Krutz, R. L., & Vines, R. D. (2010). Cloud security: A comprehensive guide to secure cloud computing. Wiley Publishing.
Buyya, R., Ranjan, R., & Calheiros, R. N. (2009, June). Modeling and simulation of scalable Cloud computing environments and the CloudSim toolkit: Challenges and opportunities. In High Performance Computing & Simulation, 2009. HPCS'09. International Conference on (pp. 1-11). IEEE.
Xing, Y., & Zhan, Y. (2012). Virtualization and cloud computing. Future Wireless Networks and Information Systems, 305-312.
Swathi, T., Srikanth, K., & Reddy, S. R. (2014). Virtualization in cloud computing. International Journal of Computer Science and Mobile Computing, 3(5), 540546.
Zhang, Y. Virtualization and Cloud Computing. Network Function Virtualization: Concepts and Applicability in 5G Networks: Concepts and Applicability in 5G Networks, 1336.
Sharma, G. P., Singh, S., Singh, A., & Kaur, R. (2016). Virtualization in Cloud Computing.
Tsai, J. T., Fang, J. C., & Chou, J. H. (2013). Optimized task scheduling and resource allocation on cloud computing environment using improved differential evolution algorithm. Computers & Operations
Research, 40(12), 3045-3055.
Shu, W., Wang, W., & Wang, Y. (2014). A novel energyefficient resource allocation algorithm based on immune clonal optimization for green cloud computing. EURASIP Journal on Wireless Communications and
Networking, 2014(1), 64.
Wang, Y., Li, J., & Wang, H. H. (2017). Cluster and cloud computing framework for scientific metrology in flow control. Cluster Computing, 1-10.
Li, W., Liu, X., Zhang, X., & Zhang, X. (2017, October). Multi-resource fair allocation with bounded number of tasks in cloud computing systems. In National Conference of Theoretical Computer Science (pp. 3-17). Springer, Singapore.
Hameed, A., Khoshkbarforoushha, A., Ranjan, R.,
Jayaraman, P. P., Kolodziej, J., Balaji, P., ... & Khan, S. U. (2016). A survey and taxonomy on energy efficient resource allocation techniques for cloud computing systems. Computing, 98(7), 751-774.
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.
