Development of models and algorithms for optimization of resource consumption in the data storage based on cloud platform

Authors

DOI:

https://doi.org/10.15587/2312-8372.2015.51415

Keywords:

load distribution, cloud computing, DSS, data migration, simulation

Abstract

The use of cloud computing technology to build information systems of research organization is discussed in this paper. The main purpose is to determine the key parameters that affect how each resource involved in the construction of systems and optimization of resource consumption taking into account solvable problem. The research results are based on queuing theory, methods of optimization and simulation. Mathematical models of service requests users to store data on a cloud platform. Also the algorithm of load balancing algorithm and intellectual migration data in cloud storage data is developed. The algorithms allow scale information system without lowering the volume of resources involved in the work. Performance evaluation showed decrease query processing time by increasing system capacity by using developed technology. The research results can be used to improve the efficiency of software and hardware resources, quality of services in information systems to the cloud platform, as well as to avoid overloading services.

Author Biography

Карина Андріївна Мацуєва, National Aviation University, 1 Kosmonavta Komarova ave., Kyiv, Ukraine, 03680

Postgraduate, Assistant

Department of Computerized Management Systems

References

  1. Aida, K., Kasahara, H., Narita, S. (1998). Job Scheduling Scheme for Pure Space Sharing among Rigid Jobs. Lecture Notes In Computer Science, Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing. London: Springer-Verlag, 98–121. doi:10.1007/bfb0053983
  2. Sinnen, O., Sousa, L. A. (2005, June). Communication contention in task scheduling. IEEE Transactions on Parallel and Distributed Systems, Vol. 16, № 6, 503–515. doi:10.1109/tpds.2005.64
  3. Gergel', V. P., Polezhaev, P. N. (2010). Issledovanie algoritmov planirovaniia parallel'nyh zadach dlia klasternyh vychislitel'nyh sistem s pomoshch'iu simuliatora. Vestnik Nizhegorodskogo universiteta im. N. I. Lobachevskogo, 5 (1), 201–208.
  4. OpenStack Open Source Cloud Computing Software. Available: http://www.openstack.org/
  5. Matsuieva, K. (2015). Methods of resource management and applications in computing systems based on cloud technology. ScienceRise, 7(2(12)), 33–38. doi:10.15587/2313-8416.2015.46591
  6. Petrov, D. L. (2010). Optimal'nyi algoritm migratsii dannyh v masshtabiruemyh oblachnyh hranilishchah. Upravlenie bol'shimi sistemami, 30, 180–197.
  7. Petrov, D. L. (2010). Dinamicheskaia model' masshtabiruemogo oblachnogo hranilishcha dannyh hranilishchah. Izvestiia LETI, 4, 17–21.
  8. Rogov, S., Namiot, D. (2002). Testirovanie proizvoditel'nosti veb-serverov. Available: http://www.osp.ru/os/2002/12/055.htm
  9. Ngenzi, A., Selvarani, R., Suchithrar, Dr. (2014). Appling mathematical models in cloud computing: A survey. Jornal of Computer Engineering, Vol. 16, № 5, 36–46. doi:10.9790/0661-16523646
  10. Ruiz-Alvarez, A., Humphrey, M. (2012). A Model and Decision Procedure for Data Storage in Cloud Computing. Proceedings of the IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing (CCGrid`12). Ottawa, 572–579. doi:10.1109/ccgrid.2012.100.
  11. Matsuieva, K. A. (2015). Modeliuvannia dynamichnoho rozpodilennia navantazhennia v informatsiinii systemi na bazi khmarnykh obchyslen. Visnyk Natsionalnoho tekhnichnoho universytetu "KhPI", 22 (1131), 28–31.

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Published

2015-09-22

How to Cite

Мацуєва, К. А. (2015). Development of models and algorithms for optimization of resource consumption in the data storage based on cloud platform. Technology Audit and Production Reserves, 5(7(25), 7–11. https://doi.org/10.15587/2312-8372.2015.51415

Issue

Vol. 5 No. 7(25) (2015): Fundamental and applied researches: integration into the world scientometric databases

Section

Mathematical Modeling - Applied Aspects

License

Copyright (c) 2016 Карина Андріївна Мацуєва

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