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A Model of Multiagent Information and Control System Distributed Data Storage

  • Eduard Melnik
  • Anna Klimenko
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 874)

Abstract

This paper deals with the information and control system dependability issue. Firstly, the “criterion delegating” approach is presented briefly. This approach, developed earlier, allows to improve the system elements reliability by the criteria number reducing within the configuration forming problem. As such approach needs a data storage to distribute up-to-date monitoring and control tasks context data through the system, the one’s models are developed and presented. We develop two model types, centralized (based on Viewstamped Replication protocol) and fully decentralized. The models are considered and discussed in terms of communication environment workload on the operation and reconfiguration stages of the system.

Keywords

Information and control system Dependability Reliability Distributed data storage Data replication Multiagent control system 

Notes

Acknowledgement

The paper has been prepared within the GZ SSC RAS N GR project 01201354238 and RFBR projects 17-08-01605 A, 18-29-03229 mk, 18-05-80092 and SO SSC RAS N GR project 01201354238, the program of RAS presidium fundamental research I.30 “Theory and technologies of multilevel decentralized group management in conflict and cooperation conditions” (project № AAAA-A18-118011290099-9).

References

  1. 1.
    Crestani, D., Godary-Dejean, K.: Fault tolerance in control architectures for mobile robots: fantasy or reality? In: 7th National Conference on Control Architectures of Robots (2012). http://hal.archives-ouvertes.fr/docs/00/80/43/70/PDF/2012_CAR_FTRobotic-FantasyOrReality.pdf
  2. 2.
    Avizienis, A, Laprie, J.C., Randell, B.: Fundamental concepts of dependability. Technical report, Seriesuniversity of Newcastle Upon Tyne, Computing Science, vol. 1145, pp. 7–12 (2001). https://doi.org/10.1.1.24.6074Google Scholar
  3. 3.
    Carlson, J., Murphy, R.R.: How UGVs physically fail in the field. IEEE Trans. Robot. 21(3), 423–437 (2005).  https://doi.org/10.1109/TRO.2004.838027CrossRefGoogle Scholar
  4. 4.
    Melnik, E., Korovin, I., Klimenko, A.: Improving dependability of reconfigurable robotic control system. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence (LNAI) and Lecture Notes in Bioinformatics), vol. 10459 (2017).  https://doi.org/10.1007/978-3-319-66471-2_16Google Scholar
  5. 5.
    Melnik, E.V., Klimenko, A.B., Schaefer, G., Korovin, I.S.: A novel approach to fault tolerant information and control system design. In: 2016 5th International Conference on Informatics, Electronics and Vision, ICIEV 2016 (2016).  https://doi.org/10.1109/ICIEV.2016.7760182
  6. 6.
    Korovin, I., Melnik, E., Klimenko, A.: A recovery method for the robotic decentralized control system with performance redundancy. Lecture Notes in Computer Science (LNCS) (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9812 (2016).  https://doi.org/10.1007/978-3-319-43955-6_2Google Scholar
  7. 7.
    Melnik, E., Klimenko, A., Korobkin, V.: Reconfigurable distributed information and control system multiagent management approach. In: Advances in Intelligent Systems and Computing, vol. 680 (2018).  https://doi.org/10.1007/978-3-319-68324-9_10Google Scholar
  8. 8.
    Strogonov, A.: Dolgovechnost Integralnih schem I proizvodstvenniye metody ee prognozirovaniya. ChipNews, № 6, pp. 44–49 (2002)Google Scholar
  9. 9.
    Ingber, L.: Simulated annealing: practice versus theory. Math. Comput. Model. 18(11), 29–57 (1993).  https://doi.org/10.1016/0895-7177(93)90204-CMathSciNetCrossRefzbMATHGoogle Scholar
  10. 10.
    Liskov, B.: From viewstamped replication to Byzantine fault tolerance. Lecture Notes in Computer Science (LNCS) (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5959, pp. 121–149 (2010).  https://doi.org/10.1007/978-3-642-11294-2_7Google Scholar
  11. 11.
    Kirsch, J., Amir, Y.: Paxos for system builders. In: Proceedings of the 2nd Workshop on Large-Scale Distributed Systems and Middleware - LADIS 2008, p. 1 (2008).  https://doi.org/10.1145/1529974.1529979
  12. 12.
    Liskov, B., Cowling, J.: Viewstamped replication revisited. In: IEICE Transactions on Information and Systems, (MIT-CSAIL-TR-2012-021), pp. 1–14 (2012). http://18.7.29.232/handle/1721.1/71763
  13. 13.
    Van Renesse, R., Schiper, N., Schneider, F.B.: Vive La Différence: Paxos vs. Viewstamped Replication vs. Zab. IEEE Trans. Depend. Secure Comput. 12(4), 472–484 (2015).  https://doi.org/10.1109/TDSC.2014.2355848CrossRefGoogle Scholar
  14. 14.
    Junqueira, F.P., Reed, B.C., Serafini, M.: Zab: high-performance broadcast for primary-backup systems. In: Proceedings of the International Conference on Dependable Systems and Networks (pp. 245–256).  https://doi.org/10.1109/DSN.2011.5958223

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Southern Scientific Center of the Russian Academy of ScienceRostov-on-DonRussia
  2. 2.Scientific Research Institute of Multiprocessor Computer Systems of Southern Federal UniversityTaganrogRussia

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