Abstract
Cloud service providers (CSPs) like Amazon Web Services, Google Engine, and Microsoft Azure have the major share in providing cloud-related services globally. Their user-friendly approach to provide Infrastructure, Platform, and Software-as-a-Service encourages many industries to switch to virtual mode with high availability, low maintenance, and deployment cost using cloud computing. In this paper, the main focus is on infrastructure-related services. For hosting the web applications, a user requires a virtual machine using the Infrastructure-as-a-Service model of CSPs. The creation of a single instance on servers is effortless. But the process of creating more than 100 machines, deploying one at a time, can be time-consuming, tedious, and error-prone. Though many CSPs have already included services for the creation and management of multiple virtual machines, a novel model named Secure Virtual Infrastructure Model (SViM) is proposed to enhance the service quality, accessibility, and usability of the IaaS cloud. It can add functionality to the existing process of creating multiple virtual machines by CSPs. In this model, a new cryptography technique is also proposed to exchange data between client and virtual servers. For the implementation of the proposed framework, a cloud simulator, Cloudsim, is used.
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References
Amazon EC2 Official Site. (n.d.). Retrieved 10 Sept 2020, from https://aws.amazon.com/ec2/
AMI-Amazon EC2. (n.d.). Retrieved 10 Sept 2020, from https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/AMIs.html?6AAEBD6E-4AD4-0945-8BB5-C39CA29CBA98_kis_cup_C6FA3ED5_6D17_47D1_B6E2_F4B02CC905E0_
Anderson, J., & Cho, J. H. (2017). Software defined network based virtual machine placement in cloud systems. Proceedings - IEEE Military Communications Conference MILCOM, 876–881. https://doi.org/10.1109/MILCOM.2017.8170772
Aneri, P., & Sumathy, S. (2017). Dynamic virtual machine allocation policy in cloud computing complying with service level agreement using CloudSim. IOP Conference Series: Materials Science and Engineering, 263(4). https://doi.org/10.1088/1757-899X/263/4/042016
AWS. (n.d.). Retrieved 11 Feb 2021, from https://aws.amazon.com/
Baldassarre, M. T., Barletta, V. S., Caivano, D., & Scalera, M. (2020). Integrating security and privacy in software development. Software Quality Journal. https://doi.org/10.1007/s11219-020-09501-6
Banisakher, M., Mohammed, D., & Simeon, J. (2018). Security analysis of the workload distribution and resource pooling architecture in cloud systems. Proceedings - 2018 UKSim-AMSS 20th International Conference on Modelling and Simulation, UKSim 2018, 7, 114–120. https://doi.org/10.1109/UKSim.2018.00032
Caballer, M., Blanquer, I., Moltó, G., & de Alfonso, C. (2015). Dynamic management of virtual infrastructures. Journal of Grid Computing, 13(1), 53–70. https://doi.org/10.1007/s10723-014-9296-5
Canalys Q2 2020. (n.d.). Retrieved September 11, 2020, from https://www.canalys.com/static/press_release/2020/Canalys-cloudq220.pdf
Churi, P. P. (2019). Performance analysis of data encryption algorithm. International Journal of Recent Technology and Engineering, 8(3), 6230–6235. https://doi.org/10.35940/ijrte.C5775.098319
Cloud Virtualization. (n.d.). Retrieved 10 Sept 2020, from https://www.w3schools.in/cloud-computing/cloud-virtualization/
Cloudsim. (n.d.). Retrieved 10 Sept 2020, from http://www.cloudbus.org/cloudsim/
DIldar, M. S., Khan, N., Abdullah, J. Bin, & Khan, A. S. (2017). Effective way to defend the hypervisor attacks in cloud computing. 2017 2nd International Conference on Anti-Cyber Crimes, ICACC 2017, 154–159. https://doi.org/10.1109/Anti-Cybercrime.2017.7905282
Docker. (n.d.). Retrieved 10 Sept 2020, from https://www.docker.com/
Domínguez-Mayo, F. J., García-García, J. A., Escalona, M. J., Mejías, M., Urbieta, M., & Rossi, G. (2015). A framework and tool to manage Cloud Computing service quality. In Software Quality Journal (Vol. 23, Issue 4). https://doi.org/10.1007/s11219-014-9248-0
EBS. (n.d.). Retrieved 24 Aug 2021, from https://us-east-2.console.aws.amazon.com/elasticbeanstalk/home?region=us-east-2#/welcome
Eucalyptus. (n.d.). Retrieved 2 June 2021, from https://www.eucalyptus.cloud/
Google Cloud. (n.d.). Retrieved 10 Sept 2020, from https://cloud.google.com/
Guan, X., Wan, X., Choi, B. Y., Song, S., & Zhu, J. (2017). Application oriented dynamic resource allocation for data centers using docker containers. IEEE Communications Letters, 21(3), 504–507. https://doi.org/10.1109/LCOMM.2016.2644658
Hussain, S. A., Fatima, M., Saeed, A., Raza, I., & Shahzad, R. K. (2017). Multilevel classification of security concerns in cloud computing. Applied Computing and Informatics, 13(1), 57–65. https://doi.org/10.1016/j.aci.2016.03.001
Image in Azure. (n.d.). Retrieved 26 Aug 2021, from https://docs.microsoft.com/en-us/azure/virtual-machines/windows/create-vm-generalized-managed
Intel® SGX. (n.d.). Retrieved 20 Aug 2021, from https://software.intel.com/content/www/us/en/develop/topics/software-guard-extensions.html
Islam, T., & Hasan, M. S. (2017). A performance comparison of load balancing algorithms for cloud computing. Conference Proceedings - 2017 International Conference on the Frontiers and Advances in Data Science, FADS 2017, (Vm), 130–135. https://doi.org/10.1109/FADS.2017.8253211
López, J., Kushik, N., & Zeghlache, D. (2019). Virtual machine placement quality estimation in cloud infrastructures using integer linear programming. Software Quality Journal, 27(2), 731–755. https://doi.org/10.1007/s11219-018-9420-z
Maniah, Abdurachman, E., Gaol, F. L., & Soewito, B. (2019). Survey on threats and risks in the cloud computing environment. Procedia Computer Science, 161, 1325–1332. https://doi.org/10.1016/j.procs.2019.11.248
Mars Eclipse | The Eclipse Foundation. (n.d.). Retrieved 8 Sept 2020, from https://www.eclipse.org/mars/
Mell, P., & Grance, T. (n.d.). The NIST Definition of Cloud Computing Recommendations of the National Institute of Standards and Technology. https://doi.org/10.6028/NIST.SP.800-145
Microsoft Azure. (n.d.). Retrieved 10 Sept 2020, from https://azure.microsoft.com/en-in/
Nwe, K. M., Oo, M. K., & Htay, M. M. (2018). Efficient resource management for virtual machine allocation in cloud data centers. 2018 IEEE 7th Global Conference on Consumer Electronics, GCCE 2018, 836–837. https://doi.org/10.1109/GCCE.2018.8574804
OpenStack. (n.d.). Retrieved11 Feb 2021, from https://www.openstack.org/
Pierleoni, P., Concetti, R., Belli, A., & Palma, L. (2020). Amazon, Google and Microsoft Solutions for IoT: Architectures and a Performance Comparison. IEEE Access, 8, 5455–5470. https://doi.org/10.1109/ACCESS.2019.2961511
Puri, S., & Agnihotri, M. (2018). A Proactive approach for cyber attack mitigation in cloud network. 2017 International Conference on Energy, Communication, Data Analytics and Soft Computing, ICECDS 2017, 171–176. https://doi.org/10.1109/ICECDS.2017.8389740
Raspberry Pi. (n.d.). Retrieved 20 Aug 2021, from https://www.raspberrypi.org/software/raspberry-pi-desktop/
Ren, J., Liu, L., Zhang, D., Zhou, H., & Zhang, Q. (2016). ESI-cloud: Extending virtual machine introspection for integrating multiple security services. Proceedings - 2016 IEEE International Conference on Services Computing, SCC 2016, 804–807. https://doi.org/10.1109/SCC.2016.111
RG-Google Cloud. (n.d.). Retrieved 26 Aug 2021, from https://cloud.google.com/monitoring/groups
Rivest, R. L., Shamir, A., & Adleman, L. (1978). A method for obtaining digital signatures and public-key cryptosystems. Communications of the ACM, 21(2), 120–126. https://doi.org/10.1145/359340.359342
Serrano, N., Gallardo, G., & Hernantes, J. (2015). Infrastructure as a service and cloud technologies. IEEE Software, 32(2), 30–36. https://doi.org/10.1109/MS.2015.43
Simulink. (n.d.). Retrieved 20 Aug 2021, from https://www.mathworks.com/products/simulink-coder.html
Sollfrank, M., Loch, F., Denteneer, S., & Vogel-Heuser, B. (2021). Evaluating Docker for Lightweight Virtualization of Distributed and Time-Sensitive Applications in Industrial Automation. IEEE Transactions on Industrial Informatics, 17(5), 3566–3576. https://doi.org/10.1109/TII.2020.3022843
Sultan, S., Ahmad, I., & Dimitriou, T. (2019). Container security: Issues, challenges, and the road ahead. IEEE Access, 7, 52976–52996. https://doi.org/10.1109/ACCESS.2019.2911732
Suraj, A. R., Shekar, S. J., & Mamatha, G. S. (2018). A robust security model for cloud computing applications. 7th IEEE International Conference on Computation of Power, Energy, Information and Communication, ICCPEIC 2018, 18–22. https://doi.org/10.1109/ICCPEIC.2018.8525141
Torquato, M., Maciel, P., & Vieira, M. (2020). Availability and reliability modeling of VM migration as rejuvenation on a system under varying workload. Software Quality Journal, 28(1), 59–83. https://doi.org/10.1007/s11219-019-09474-1
Urias, V. E., Van Leeuwen, B., Stout, W. M. S., & Lin, H. (2018). Applying a threat model to cloud computing. Proceedings - International Carnahan Conference on Security Technology, 2018-Octob, 1–5. https://doi.org/10.1109/CCST.2018.8585471
Vennela, G. S., Varun, N. V., Neelima, N., Priya, L. S., & Yeswanth, J. (2018). Performance analysis of cryptographic algorithms for cloud security. Proceedings of the International Conference on Inventive Communication and Computational Technologies, ICICCT 2018, Icicct, 273–279. https://doi.org/10.1109/ICICCT.2018.8473148
VirusTotal. (n.d.). Retrieved 2 June 2021, from https://www.virustotal.com/gui/
VMSS-Azure. (n.d.). Retrieved 26 Aug 2021, from https://azure.microsoft.com/en-in/services/virtual-machine-scale-sets/
VMware. (n.d.). Retrieved 2 June 2021, from https://www.vmware.com/in.html
Wang, R., Ying, S., Li, M., & Jia, S. (2020). HSACMA: a hierarchical scalable adaptive cloud monitoring architecture. Software Quality Journal. https://doi.org/10.1007/s11219-020-09524-z
What is IaaS (Infrastructure-as-a-Service) | IBM. (n.d.). Retrieved 10 Sept 2020, from https://www.ibm.com/cloud/learn/iaas
Xen-Hypervisor. (n.d.). Retrieved 2 June 2021, from https://xenproject.org/developers/teams/xen-hypervisor/
Zykov, S., & Shumsky, L. (2016). Application of information processes applicative modelling to virtual machines auto configuration. Procedia Computer Science, 96(September), 1041–1048. https://doi.org/10.1016/j.procs.2016.08.124
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The authors wish to acknowledge and admire the support of the administration of the University School of Information, Communication and Technology, GGSIP University, for providing a research-oriented platform and all necessary infrastructures in performing this research.
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Varshney, K., Ujjwal, R.L. Novel framework for secured bulk creation of virtual machine in IaaS platform. Software Qual J 30, 513–549 (2022). https://doi.org/10.1007/s11219-021-09573-y
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DOI: https://doi.org/10.1007/s11219-021-09573-y