Economics and management of national economy

The principles of synchronization in the distributed information systems

Economic Annals-XXI

Economic Annals-ХХI: Volume 183, Issue 5-6, Pages: 79-88

Citation information:
Sinitsyn, I., Mironov, A., Vorontsov, Yu., Borzykh, N., & Mikhailova, E. (2020). The principles of synchronization in the distributed information systems. Economic Annals-XXI, 183(5-6), 79-88. doi: https://doi.org/10.21003/ea.V183-08

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Ivan Sinitsyn
PhD (Engineering),
Associate Professor,
Software and IT-standard Department,
Institute of Information Technology,
MIREA – Russian Technological University
78 Vernadsky Ave., Moscow, 119454, Russia
sinicyn_i@mirea.ru
ORCID ID: https://orcid.org/0000-0002-4302-1616

Anton Mironov
PhD (Engineering),
Senior Lecturer of the Software and IT-standard Department,
Institute of Information Technology,
MIREA – Russian Technological University
78 Vernadsky Ave., Moscow, 119454, Russia
mironov_an@mirea.ru
ORCID ID: https://orcid.org/0000-0002-3086-8949

Yuriy Vorontsov
Assistant Professor of the Software and IT-standard Department,
Institute of Information Technology,
MIREA – Russian Technological University
78 Vernadsky Ave., Moscow, 119454, Russia
voroncov_yu@mirea.ru
ORCID ID: https://orcid.org/0000-0002-1732-6002

Nikita Borzykh
Assistant Professor of the Software and IT-standard Department,
Institute of Information Technology,
MIREA – Russian Technological University
78 Vernadsky Ave., Moscow, 119454, Russia
borzyh@mirea.ru
ORCID ID: https://orcid.org/0000-0002-0663-4958

Evgenia Mikhailova
Assistant Professor of the Software and IT-standard Department,
Institute of Information Technology,
MIREA – Russian Technological University
78 Vernadsky Ave., Moscow, 119454, Russia
mihajlova_e@mirea.ru
ORCID ID: https://orcid.org/0000-0002-0105-9325

The principles of synchronization in the distributed information systems

Abstract. Information, especially its automated processing, is still an important factor in improving the efficiency of any organization. Distributed information systems (IS, ISs) differ from conventional ISs in architectural and infrastructural principles, as well as in the geographic location with integration into one information cluster.

One of the examples of distributed information systems is the infrastructure of the Google search engine – more than 2,000 servers, with server bases in almost every country in the world, which allows achieving a minimum delay in sending and receiving client requests.

A distributed information system can have a large number of different databases, both local and remote, with which constant data synchronization is required, while maintaining a backup copy of previous data in case of failures and emergency stops.

Distributed information systems are highly reliable and require multi-level protection of the cluster from unauthorized access, adherence to the principles of data synchronization, which differ from a conventional information system.

Within the framework of this paper, synchronization processes are investigated using mathematical and computational tools, creating an environment for distributed information systems. It is advisable to use the results of the work to coordinate the operation of components of multi-agent systems for various purposes, transmit messages between agents, build communication protocols, and provide conditions for self-organization of multi-agent systems.

Keywords: Information System; Distributed Information System; Conventional Information System; Synchronization; IT; Software; Technology

JEL Classіfіcatіon: D85; L86

Acknowledgements and Funding: The authors received no direct funding for this research.

Contribution: The authors contributed equally to this work.

DOI: https://doi.org/10.21003/ea.V183-08

References

  1. Arrow, H., McGrath, J. E., & Berdahl, J. L. (2000). Small Groups as Complex Systems: Formation, Coordination, Development, and Adaptation. Newbury Park, CA: Sage Publications.
  2. Baronchelli, A., Ferrer-i-Cancho, R., Pastor-Satorras, R., Chater, N., & Christiansen, M. H. (2013). Networks in cognitive science. Trends Cognitive Sciences, 17, 348-360.
    doi: https://doi.org/10.1016/j.tics.2013.04.010
  3. Cats, O., West, J., & Eliasson, J. (2016). A Dynamic Stochastic Model for Evaluating Congestion and Crowding Effects in Transit Systems. Transportation Research Part B: Methodological, 89, 43-57.
    doi: https://doi.org/10.1016/j.trb.2016.04.001
  4. Daganzo, C. F., & Anderson, P. (2016). Coordinating Transit Transfers in Real Time (Final Report UCCONNECT – 2016 – TO 021 – 65A0529, 1-20). Institute of Transportation Studies at UC Berkeley.
    Retrieved from https://escholarship.org/uc/item/25h4r974
  5. Fadaei, M., Cats, O., & Bhaskar, A. (2017). A Hybrid Scheme for Real-Time Prediction of Bus Trajectories. Journal of Advanced Transportation, 50(8), 2130-2149.
    doi: https://doi.org/10.1002/atr.1450
  6. Fusaroli, R., Rączaszek-Leonardi, J., & Tylén, K. (2014). Dialog as interpersonal synergy. New Ideas Psychol, 32, 147-157.
    doi: https://doi.org/10.1016/j.newideapsych.2013.03.005
  7. Luo, C., & Wang, X. (2013). Chaos generated from the fractional-order complex Chen system and its application to digital secure communication. I International Journal of Modern Physics C, 24(4), 72-77.
    doi: https://doi.org/10.1142/S0129183113500253
  8. Manasra, H. (2015). Real-Time Control for Transit Systems with Transfers. Technion, Israel Institute of Technology.
    Retrieved from https://toledo.net.technion.ac.il/files/2017/08/5-Systems-with-transfers-Manasra.pdf
  9. Martínez-Guerra, R., & Mata-Machuca, J. L. (2014). Fractional generalized synchronization in a class of nonlinear fractional order systems. Nonlinear Dyna, 77(4), 1237-1244.
    doi: https://doi.org/10.1007/S11071-014-1373-6
  10. Ni, J., Liu, L., Liu, Ch., Hu, X., & Li, A. (2015). Chaos suppression for a four-dimensional fundamental power system model using adaptive feedback control. Transactions of the Institute of Measurement and Control, 39(2), 194-207. doi: https://doi.org/10.1177%2F0142331215613151
  11. Ren, H.-P., Bai, C., Huang, Z.-Z., & Grebogi, C. (2017). Secure communication based on hyperchaotic chen system with time-delay. International Journal of Bifurcation and Chaos, 27(5), 15.
    doi: https://doi.org/10.1142/S0218127417500766
  12. Sánchez-Martínez, G. E., Koutsopoulos, H. N., & Wilson, N. H. M. (2016). Real-time Holding Control for High-Frequency Transit with Dynamics. Transportation Research Part B: Methodological, 83, 1-19. doi: https://doi.org/10.1016/j.trb.2015.11.013
  13. Toledo, T., Cats, O., Burghout, W., & Koutsopoulos, H. N. (2010). Mesoscopic Simulation for Transit Operations. Transportation Research Part C: Emerging Technologies, 18(6), 896-908.
    doi: https://doi.org/10.1016/j.trc.2010.02.008
  14. Vaidyanathan, S. (2013). Adaptive design of controller and synchronizer for Lu-xiao chaotic system with unknown parameters. International Journal of Computer Science & Information Technology (IJCSIT), 5(1), 197-210.
    Retrieved from http://airccse.org/journal/jcsit/5113ijcsit16.pdf
  15. Wang, M. (2015). Impulsive Synchronization of hyperchaotic Lü systems with two methods. International Journal of Modern Nonlinear Theory and Application, 4(1), 1-9.
    doi: https://doi.org/10.4236/ijmnta.2015.41001
  16. Younan, B., & Wilson, N. H. M. (2010). Improving Transit Service Connectivity: The Application of Operations Planning and Control Strategies. 12th WCTRS (World Conference on Transport Research Society), Lisbon, Portugal.
    Retrieved from http://www.wctrs-society.com/wp-content/uploads/abstracts/lisbon/selected/02959.pdf
  17. Zhou, X., Jiang, M., & Huang, Y. (2013). Combination synchronization of three identical or different nonlinear complex hyperchaotic systems. Entropy, 15(9), 3746-3761.
    doi: https://doi.org/10.3390/e15093746

Received 11.02.2020
Received in revised form 2.03.2020
Accepted 14.03.2020
Available online 4.06.2020

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