Preview

Journal of Instrument Engineering

Advanced search

Method for Estimating the Performance of Large Information Systems with Transaction Clustering

https://doi.org/10.17586/0021-3454-2022-65-9-623-629

Abstract

A method for estimating the upper and lower bounds of large information system performance with the account for the system data integrity requirement, is proposed. The integrity is ensured by locking the computing resources necessary for the transaction execution and releasing them when the transaction is completed or cancelled. Clustering of transactions allows for parallel processing of different user requests belonging to different clusters. The features of query processing give no way of analytical assessment of large information systems performance, and a fullscale or simulation experiment is time consuming. The model of a large information system is formalized in the form of a mass service network. The complete set of routes in the queuing network is given by the number of clusters of similar transactions. The performance is estimated by the system response time.

About the Authors

M. N. Shelest
St. Petersburg State University of Aerospace Instrumentation
Russian Federation

Maria N. Shelest — Post-Graduate Student

St. Petersburg



T. M. Tatarnikova
St. Petersburg State University of Aerospace Instrumentation; Institute of Information technologies and Programming
Russian Federation

Tatiana M. Tatarnikova — Dr. Sci., Professor; Director

St. Petersburg



References

1. Proskuryakov N.E., Anufrieva A.Yu. News of the Tula State University. Technical Sciences, 2013, no. 3, pp. 368-377. (in Russ.)

2. Challawala S., Mehta C., Patel K., Lakhatariya J. MySQL 8 for Big Data: Effective Data Processing with MySQL 8, Hadoop, NoSQL APIs, and Other Big Data Tools. Packt Publishing, 2017, 226 p.

3. Fomin D.S., Bal'zamov A.V. University Proceedings. Volga Region. Technical Sciences, 2021, no. 2(58), pp. 15-23, DOI:10.21685/2072-3059-2021-2-2 (in Russ.)

4. Bogatyrev V.A., Bogatyrev A.V., Bogatyrev S.V. Journal of Instrument Engineering, 2014, no. 4(57), pp. 46-48. (in Russ.)

5. Burmistrov V.D., Zakovryashin E.M. Molodoy uchenyy (Young Scientist), 2016, no. 12, pp. 143-147. (in Russ.)

6. Tatarnikova T.M., Volskiy A.V. Information and Control Systems, 2018, no. 3(94), pp. 54-60. (in Russ.)

7. Shelest M.N. Information and Control Systems, 2022, no. 2, pp. 32-41, DOI:10.31799/1684-8853-2022-2-32-41. (in Russ.)

8. Bogatyrev V.A., Karmanovsky N.S., Poptsova N.A., Parshutina S.A., Voronina D.A., Bogatyrev S.V. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2016, no. 5(16), pp. 831-838, DOI: 10.17586/2226-1494-2016-16-5-831-838. (in Russ.)

9. Harary F. Graph Theory, Addison–Wesley, 1969.

10. Shelest M.N., Bakin E.A. Wave Electronics and its Application in Information and Telecommunication Systems (WECONF), Pitsataway, NJ, 2018, pp. 1-4.


Review

For citations:


Shelest M.N., Tatarnikova T.M. Method for Estimating the Performance of Large Information Systems with Transaction Clustering. Journal of Instrument Engineering. 2022;65(9):623-629. (In Russ.) https://doi.org/10.17586/0021-3454-2022-65-9-623-629

Views: 12


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 0021-3454 (Print)
ISSN 2500-0381 (Online)