A Study of Cloud Computing Based on Virtualization and Security Threats
DOI:
https://doi.org/10.26438/ijcse/v5i9.108112Keywords:
Cloud computing, Virtualization, service model, Virtual machine migration, security threats and energy efficiencyAbstract
Cloud computing is an emerging technology based on the network that provides access to the data from server. It Cloud computing is an emerging technology based on the network that provides access to the data from server. It illustrates an extremely scalable computing asset offered as an external service Paid by Internet method. In cloud computing, mainly we have focused on virtualization, energy efficiency and security. In this paper, we conducted a survey of cloud computing which is a framework that uses different services, IaaS, PaaS, SaaS and HaaS. A comparison for the same is also explained. The concept of virtualization is also discussed following Bare metal hypervisor, Hosted hypervisor and VMM (Virtual machine migration). Different security threats have been mentioned being considered for cloud services. For the calculation of energy consumption, cloud computing uses energy efficiency concept. Work done by various authors in cloud computing has been discussed with the research gap as well.
References
. Ostermann, S., Iosup, A., Yigitbasi, N., Prodan, R., Fahringer, T., & Epema, D. (2009, October). A performance analysis of EC2 cloud computing services for scientific computing. In International Conference on Cloud Computing (pp. 115-131). Springer, Berlin, Heidelberg..
. 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), 50-58.
. Qian, L., Luo, Z., Du, Y., & Guo, L. (2009). Cloud computing: An overview. Cloud computing, 626-631.
. Subashini, S., & Kavitha, V. (2011). A survey on security issues in service delivery models of cloud computing. Journal of network and computer applications, 34(1), 1-11.
. Alshammari, A., Alhaidari, S., Alharbi, A., & Zohdy, M. (2017, June). Security Threats and Challenges in Cloud Computing. In Cyber Security and Cloud Computing (CSCloud), 2017 IEEE 4th International Conference on (pp. 46-51). IEEE.
. Wei, Y., & Blake, M. B. (2010). Service-oriented computing and cloud computing: Challenges and opportunities. IEEE Internet Computing, 14(6), 72-75.
. Tsai, W. T., Sun, X., & Balasooriya, J. (2010, April). Service-oriented cloud computing architecture. In Information Technology: New Generations (ITNG), 2010 Seventh International Conference on (pp. 684-689). IEEE
. Lombardi, F., & Di Pietro, R. (2011). Secure virtualization for cloud computing. Journal of Network and Computer Applications, 34(4), 1113-1122.
. Jain, R., & Paul, S. (2013). Network virtualization and software defined networking for cloud computing: a survey. IEEE Communications Magazine, 51(11), 24-31.
. Shaikh, F. B., & Haider, S. (2011, December). Security threats in cloud computing. In Internet technology and secured transactions (ICITST), 2011 international conference for (pp. 214-219). IEEE.
. Kajal, N., & Ikram, N. (2015, May). Security threats in cloud computing. In Computing, Communication & Automation (ICCCA), 2015 International Conference on (pp. 691-694). IEEE.
. Jain, R., & Paul, S. (2013). Network virtualization and software defined networking for cloud computing: a survey. IEEE Communications Magazine, 51(11), 24-31..
. Shivlal Mewada, Arti Sharivastava, Pradeep Sharma, N Purohit and S.S. Gautam, "An Performance Analysis of Encryption Algorithm in Cloud Computing", International Journal of Computer Sciences and Engineering, Vol.3, Issue.2, pp.83-89, 2015.
. Cao, Y., Song, F., Liu, Q., Huang, M., Wang, H., & You, I. (2017). A LDDoS-aware Energy-efficient Multipathing Scheme for Mobile Cloud Computing Systems. IEEE Access.
. Razaque, A., Vennapusa, N. R., Soni, N., & Janapati, G. S. (2016, April). Task scheduling in cloud computing. In Long Island Systems, Applications and Technology Conference (LISAT), 2016 IEEE (pp. 1-5). IEEE.
. Mathew, T., Sekaran, K. C., & Jose, J. (2014, September). Study and analysis of various task scheduling algorithms in the cloud computing environment. In Advances in Computing, Communications and Informatics (ICACCI, 2014 International Conference on (pp. 658-664). IEEE.
. Arabnejad, H., Barbosa, J. G., & Prodan, R. (2016). Low-time complexity budget–deadline constrained workflow scheduling on heterogeneous resources. Future Generation Computer Systems, 55, 29-40.
. Yu, J., & Buyya, R. (2006, June). A budget constrained scheduling of workflow applications on utility grids using genetic algorithms. In Workflows in Support of Large-Scale Science, 2006. WORKS'06. Workshop on (pp. 1-10). IEEE.
. Ting, T. O., Rao, M. V. C., & Loo, C. K. (2006). A novel approach for unit commitment problem via an effective hybrid particle swarm optimization. IEEE Transactions on Power Systems, 21(1), 411-418.
. He, Q., & Wang, L. (2007). A hybrid particle swarm optimization with a feasibility-based rule for constrained optimization. Applied mathematics and computation, 186(2), 1407-1422.
. Meena, J., Kumar, M., & Vardhan, M. (2016). Cost Effective Genetic Algorithm for Workflow Scheduling in Cloud Under Deadline Constraint. IEEE Access, 4, 5065-5082.
. Visheratin, A. A., Melnik, M., & Nasonov, D. (2016). Workflow scheduling algorithms for hard-deadline constrained cloud environments. Procedia Computer Science, 80, 2098-2106.
. Beloglazov, A., Abawajy, J., & Buyya, R. (2012). Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing. Future generation computer systems, 28(5), 755-768.
. Chen, W., Xie, G., Li, R., Bai, Y., Fan, C., & Li, K. (2017). Efficient task scheduling for budget constrained parallel applications on heterogeneous cloud computing systems. Future Generation Computer Systems, 74, 1-11.
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.
