STATIC ALLOCATION METHOD IN A CLOUD ENVIRONMENT WITH A SERVICE MODEL IAAS
Main Article Content
Abstract
The article discusses a method that allows the allocation of the required computing resources for the initial launch of a virtual host. The method is focused on the functioning of a virtual host in a cloud environment focused on the service model "Infrastructure as a Service". The subject of research is the methods of static resource allocation in cloud environments. The object of study is the process of functioning of a virtual host in a cloud environment that provides all information technology resources for it. The purpose of the study is to develop a method for the static allocation of resources in the cloud environment, focused on the features of the service model "Infrastructure as a Service". Results: An approach has been developed for carrying out the decomposition of a cloud computing environment with the IAAS service model. The analysis of existing methods of static allocation of resources has been carried out. The application of the method of analysis of hierarchies for this problem is substantiated. A step-by-step algorithm for finding the most acceptable alternative from the set proposed has been developed. An example of the application of the developed method for initializing a virtual host in a cloud environment with the IAAS service model is given. Conclusion. The proposed method makes it possible to rationally use the computing resources of the cloud environment, which uses the "Infrastructure as a Service" service model. Direction for further research. The development of this direction is the development of a method for dynamic redistribution of resources in a cloud environment with the IAAS service model.
Article Details
References
Zhen, Xiao, Weija, Song, and Qu, Chen (2018), “Dynamic Resource Allocation using Virtual Machines for Cloud Computing Environment”, IEEE transaction on parallel and distributed systems, Vol. 24, Is. 6, pp. 1107 – 1117, June 2013, doi: https://doi.org/10.1109/TPDS.2012.283.v.
Franti, P. (2018,) “Efficiency of random swap clustering”, Journal of Big Data, vol. 5, No. 13, pp. 1-29. doi: https://doi.org/10.1186/s40537-018-0122-y.
Kuchuk, N., Shefer, O., Cherneva, G. and Alnaeri, F.A. (2021), “Determining the capacity of the self-healing network segment”, Advanced Information Systems, vol. 5, no. 2, pp. 114–119, Jun. 2021, doi: https://doi.org/10.20998/2522-9052.2021.2.16.
Qiang, Ye. and Zhuang, W. (2017), “Distributed and adaptive medium access control for internet-of-things-enabled mobile networks”, IEEE Internet of Things Journal, vol. 4, no. 2, pp. 446-460, doi: https://doi.org/10.1109/JIOT.2016.2566659.
Khudov, H., Tahyan, K., Chepurnyi, V., Khizhnyak, I., Romanenko, K., Nevodnichii, A. and Yakovenko, O. (2020), “Optimization of joint search and detection of objects in technical surveillance systems”, Advanced Information Systems, Vol. 4, No. 2, pp. 156-162, doi: https://doi.org/10.20998/2522-9052.2020.2.23.
Semenov, S. and Cao, Weilin, (2020), “Testing process for penetration into computer systems mathematical model modification”, Advanced Information Systems, Vol. 4, No. 3, pp. 133–138, doi: https://doi.org/10.20998/2522-9052.2020.3.19.
Kuchuk, G., Kovalenko, A., Komari, I.E., Svyrydov, A. and Kharchenko, V. (2019), “Improving big data centers energy efficiency: Traffic based model and method”, Studies in Systems, Decision and Control, vol. 171, Kharchenko, V., Kondratenko, Y., Kacprzyk, J. (Eds.), Springer Nature Switzerland AG, pp. 161-183, doi: https://doi.org/10.1007/978-3-030-00253-4_8.
Nechausov, A., Mamusuĉ, I. and Kuchuk, N. (2017), “Synthesis of the air pollution level control system on the basis of hyperconvergent infrastructures”, Advanced Information Systems, vol. 1, no. 2, , pp. 21–26. DOI: https://doi.org/10.20998/2522-9052.2017.2.04.
Kuchuk, H., Kovalenko, A., Ibrahim, B.F. and Ruban, I. (2019), “Adaptive compression method for video information”, International Journal of Advanced Trends in Computer Science and Engineering, 8(1), pp. 66–69, 2019, doi: http://dx.doi.org/10.30534/ijatcse/2019/1181.22019.
Bulba, S. (2018), “Composite application distribution methods”, Advanced Information Systems, vol. 2, no. 3, pp. 128–131, doi: https://doi.org/10.20998/2522-9052.2018.3.22.
Petrovska, I. and Kuchuk H. (2022), “Features of the distribution of computing resources in cloud systems”, Control, Navigation and Communication Systems, No. 2, pp. 75-78, doi: http://dx.doi.org/10.26906/SUNZ.2022.2.075.
Saaty T. L. (2008). “Decision making with the analytic hierarchy process”, International Journal of Services Sciences,, Vol. 1, No. 1, pp. 83-98, doi: https://doi.org/10.1504/IJSSCI.2008.017590.