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Methods to Manage Data in Self-healing Systems

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Advances in Self-healing Systems Monitoring and Data Processing

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 425))

Abstract

The chapter proposes a set of data management methods in Self-healing Systems. The proposed methods are focused on taking into account the features of Self-healing Systems and allow the improvement of the reduced QoS parameters. A method to calculate the bandwidth of network sections and the required amount of buffer memory for the known network topology and given gravity matrix, which provides the required values of failure probability for Self-healing Systems and ensures a minimum message delivery time. A method of reallocating the computing resource network section of Self-healing System is proposed, which enables increasing the efficiency of using the computing resource of the core Network of Self-healing Systems. Taking into account the peculiarities of data processing in wireless components, methods to manage information transmission routes and information transmission for modification of transport protocols of a wireless component of ShS CN are developed. A method to synthesize the models of complexes of data processing programs in Self-healing Systems is proposed, which is based on the formal-logical apparatus of temporal Petri nets. The method uses trace data obtained while monitoring Self-healing Systems.

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References

  1. Kuchuk, G., Kovalenko, A., Komari, I.E., Svyrydov, A., Kharchenko, V.: Improving big data centers energy efficiency. Traffic based model and method. Stud. Syst. Decis. Control. 171, 161–183 (2019). https://doi.org/10.1007/978-3-030-00253-4_8

  2. Anand, M., Chouhan, K., Ravi, S., Ahmed, S.M.: Context switching semaphore with data security issues using self-healing approach. Int. J. Adv. Comput. Sci. Appl. 2(6), 55–62 (2011) https://doi.org/10.14569/IJACSA.2011.020608

  3. Michiels, S., Desmet, L., Janssens, N., Mahieu, T., Verbaeten, P.: Self-adapting concurrency. In: The DMonA Architecture. Proceedings of the 1st Workshop on Self-Healing Systems, pp. 43–48. Charleston (2002), 18–19 Nov 2002. https://doi.org/10.1145/582128.582137

  4. Fuad, M.M., Deb, D., Baek, J.: Self-healing by means of runtime execution profiling. In: Proceedings of 14th International Conference on Computer and Information Technology (ICCIT 2011), pp. 202–207. Dhaka, 22–24 Dec 2011 (2012). https://doi.org/10.1109/ICCITechn.2011.6164784

  5. Ardagna, D., Cappiello, C., Fugini, M.G., Mussi, E., Pernici, B., Plebani, P.: Faults and recovery actions for self-healing web services (2006). https://www.academia.edu/20153099/Faults_and_recovery_actions_for_self-healing_web_services

  6. Georgiadis, J., Kramer, M.J.: Self-organizing software architectures for distributed systems. In: Proceedings of the 1st Workshop on Self-Healing Systems, pp. 33–38. Charleston (2002), 18–19 Nov 2002. https://doi.org/10.1145/582128.582135

  7. Carzaniga, A., Gorla, A., Pezzè, M.: Self-healing by means of automatic workarounds. In: SEAMS’08. Leipzig (2008), 12–13 May 2008. https://doi.org/10.1145/1370018.1370023

  8. Ghosh, D., Sharman, R., Rao, H.R. Upadhyaya, S.: Self-healing systems—survey and synthesis. Decis. Support. Syst. 42(4), 2164–2185 (2007). https://doi.org/10.1016/j.dss.2006.06.011

  9. Sánchez, J., Ben Yahia, I.G., Crespi, N.: POSTER: Self-healing mechanisms for software-defined networks (2014). https://arxiv.org/abs/1507.02952

  10. Ehlers, J., van Hoorn, A., Waller, J., Hasselbring, W.: Self-adaptive software system monitoring for performance anomaly localization. In: ICAC’11, Karls-ruhe, 14–18 June 2011 (2011). https://doi.org/10.1145/1998582.1998628

  11. Svyrydov, A., Kuchuk, H., Tsiapa, O.: Improving efficienty of image recognition process: approach and case study. In: Proceedings of 2018 IEEE 9th International Conference on Dependable Systems, Services and Technologies, DESSERT 2018. pp. 593–597 (2018). https://doi.org/10.1109/DESSERT.2018.8409201

  12. Kuchuk, H., Kovalenko, A., Ibrahim, B.F., Ruban, I.: Adaptive compression method for video information. Int. J. Adv. Trends Comput. Sci. Eng. 66–69 (2019). https://doi.org/10.30534/ijatcse/2019/1181.22019

  13. Katti, A., Di Fatta, G., Naughton, T., Engelmann, C.: Scalable and fault tolerant failure detection and consensus. In: EuroMPI’15, pp 1–9. Bordeaux (2015), 21–23 Sept 2015. https://doi.org/10.1145/2802658.2802660

  14. Aldrich, J., Sazawal, V., Chambers, C., Nokin, D.: Architecture centric programming for adaptive systems. In: Proceedings of the 1st Workshop on Self-Healing Systems, pp. 93–95, Charleston (2002), 18–19 Nov 2002. https://doi.org/10.1145/582128.582146

  15. Jiang, M., Zhang, J., Raymer, D., Strassner, J.: A modeling framework for self-healing software systems (2007). https://st.inf.tu-dresden.de/MRT07/papers/MRT07_Jiangl_etall.pdf

  16. Kuchuk, N., Shefer, O., Cherneva, G., Alnaeri, F.A.: Determining the capacity of the self-healing network segment. Adv. Inf. Syst. 5(2), 114–119 (2021). https://doi.org/10.20998/2522-9052.2021.2.16

  17. Mukhin, V., Kuchuk, N., Kosenko, N., Kuchuk, H., Kosenko, V.: Decomposition method for synthesizing the computer system architecture. Adv. Intell. Syst. Comput. AISC. 938, 289–300 (2020). https://doi.org/10.1007/978-3-030-16621-2_27

  18. Tkachov, V., Kovalenko, A., Kuchuk, H., Ia, N.: Method of ensuring the survivability of highly mobile computer networks. Adv. Inf. Syst. 5(2), 159–165 (2021). https://doi.org/10.20998/2522-9052.2021.2.24

  19. Pliushch, O., Vyshnivskyi, V., Berezovska, Y.: Robust telecommunication channel with parameters changing on a frame-by-frame basis. Adv. Inf. Syst. 4(3), 62–69 (2020). https://doi.org/10.20998/2522-9052.2020.3.07

  20. Fakhouri, H.: A survey about self-healing systems (Desktop and Web Application). Commun. Netw. 9(01), 71–88 (2017). https://doi.org/10.4236/cn.2017.91004

  21. Sidiroglou, S., Laadan, O., Perez, R., Viennot, N., Nieh, J., Keromytis, D.: ASSURE. Automatic software self-healing using rescue points. In: Proceedings of the 14th International Conference on Architectural Support for Programming Languages and Operating Systems, ASPLOS 2009, vol. 44(3), pp. 37–48. Washington, DC, USA (2009), 7–11 Mar 2009. https://doi.org/10.1145/2528521.1508250

  22. Frei, R., McWilliam, R., Derrick, B., Purvis, A., Tiwari, A., Serugendo, G.D.M.: Self-healing and self-repairing technologies. Int. J. Adv. Manuf. Technol. 69, 1033–1061 (2013). https://doi.org/10.1007/s00170-013-5070-2

  23. Merlac, V., Smatkov, S., Kuchuk, N., Nechausov, A.: Resourses distribution method of University e-learning on the hypercovergent platform. In: 2018 IEEE 9th International Conference on Dependable Systems, Service and Technologies, DESSERT’2018, pp. 136–140. Kyiv (2018). https://doi.org/10.1109/DESSERT.2018.8409114

  24. Attar, H., Khosravi, M.R., Igorovich, S.S., Georgievan, K.N.: Alhihi, M.: Review and performance evaluation of FIFO, PQ, CQ, FQ, and WFQ algorithms in multimedia wireless sensor networks. Int. J. Distrib. Sens. Netw. 16(6), 155014772091323 (2020). https://doi.org/10.1177/1550147720913233

  25. Momit, O., Zhyvotovskyi, R., Onbinskyi, Y., Lyashenko, A.: Analysis of the known methods of channels communication control with the interference and selective fading. Adv. Inf. Syst. 3(4), 45–51 (2019). https://doi.org/10.20998/2522-9052.2019.4.06

  26. Gorla, A., Pezzè, M., Wuttke, J.: Achieving cost-effective software reliability through self-healing. Comput. Inf. 29(1), 93–115 (2010)

    Google Scholar 

  27. Hudaib, A.A., Fakhouri, H.N.: An automated approach for software fault detection and recovery. Commun. Netw. 08(03), 158–169 (2016). https://doi.org/10.4236/cn.2016.83016

  28. Zaitseva, E., Levashenko, V.: Multiple-Valued Logic mathematical approaches for multi-state system reliability analysis. J. Appl. Log. 11(3), 350–362 (2013)

    Article  MathSciNet  Google Scholar 

  29. Sedlacek, P., Zaitseva, E., Levashenko, V., Kvassay, M.: Critical state of non-coherent multi-state system. Reliab. Eng. Syst. Saf. 215 (2021)

    Google Scholar 

  30. Kovalenko, A., Kuchuk, H., Kuchuk, N., Kostolny, J.: Horizontal scaling method for a hyperconverged network. In: 2021 International Conference on Information and Digital Technologies (IDT). Zilina, Slovakia (2021). https://doi.org/10.1109/IDT52577.2021.9497534

  31. Zaitseva, E., Levashenko, V., Sedlacek, P., Kvassay, M., Rabcan, J.: Logical differential calculus for calculation of Birnbaum importance of non-coherent system, Reliab. Eng. Syst. Saf. 215 (2021)

    Google Scholar 

  32. Levashenko, V., Lukyanchuk, I., Zaitseva, E., Kvassay, M., Rabcan, J., Rusnak, P.: Development of programmable logic array for multiple-valued logic functions. In: IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 39(12), pp. 4854–4866 (2020)

    Google Scholar 

  33. Attar, H., Khosravi, M.R., Igorovich, S.S., Georgievan, K.N., Alhihi, M.: Review and performance evaluation of FIFO, PQ, CQ, FQ, and WFQ algorithms in multimedia wireless sensor networks. Int. J. Distrib. Sens. Netw. 16(6), (2020). https://doi.org/10.1177/1550147720913233

  34. Aleksandrov, Y., Aleksandrova, T., Kostianyk, I.: Parametric synthesis of the digital invariant stabilizer for a non-stationary object. Adv. Inf. Syst. 4(1), 39–44 (2020). https://doi.org/10.20998/2522-9052.2020.1.07

  35. Zaitseva, E., Levashenko, V., Lukyanchuk, I., Rabcan, J., Kvassay, M., Rusnak, P.: Application of generalized reed–muller expression for development of non-binary circuits. Electronics (Switzerland) 9(1), (2020), Article number 12, (4)

    Google Scholar 

  36. Rabcan, J., Levashenko, V., Zaitseva, E., Kvassay, M.: Review of methods for EEG signal classification and development of new fuzzy classification-based approach. IEEE Access 8, 189720–189734 (2020)

    Google Scholar 

  37. Kuchuk, G.A., Akimova, Y.A., Klimenko, L.A.: Method of optimal allocation of relational tables. Eng. Simul. 17(5), 681–689 (2000)

    Google Scholar 

  38. Rabcan, J., Levashenko, V., Zaitseva, E., Kvassay, M.: EEG signal classification based on fuzzy classifiers. IEEE Trans. Ind. Inf. 18(2), 757-766 (2022)

    Google Scholar 

  39. Semenov, S., Sira, O., Gavrylenko, S., Kuchuk, N.: Identification of the state of an object under conditions of fuzzy input data. East.-Eur. J. Enterp. Technol. 1(4), 22–30 (2019). https://doi.org/10.15587/1729-4061.2019.157085

  40. Dustdar, P.S.: A survey on self-healing systems. Approaches Syst. 9(1), 43–73 (2011). https://doi.org/10.1007/s00607-010-0107-y

  41. Abdullah, A., Candrawati, R. Bhakti, M.A.C.: Multi-tiered bio-inspired self-healing architectural paradigm for software systems. J. Teknologi Maklumat Multimedia 5, 1–24 (2009)

    Google Scholar 

  42. Shin, M.E.: Self-healing component in robust software architecture for concurrent and distributed systems. Sci. Comput. Prog. 57(1), 27–44 (2005). https://doi.org/10.1016/j.scico.2004.10.003

  43. Zhou, J., Wunderlich, H.-J.: Software-based self-test of processors under power constraints. In: Proceedings of Design, Automation and Test in Europe, vol. 1, pp. 1–6. Munich (2006), 6–10 Mar 2006. https://doi.org/10.1109/DATE.2006.243798

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Author information

Authors and Affiliations

  1. Kharkiv National University of Radio Electronics, 14 Nauki ave., Kharkiv, 61166, Ukraine

    Andriy Kovalenko

  2. National Technical University “Kharkiv Polytechnic Institute”, 2, Kyrpychova str., Kharkiv, 61166, Ukraine

    Heorhii Kuchuk

Authors
  1. Andriy Kovalenko
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Editors and Affiliations

  1. Kharkiv National University of Radio Electronics, Kharkiv, Ukraine

    Igor Ruban

  2. Kharkiv National University of Radio Electronics, Kharkiv, Ukraine

    Andriy Kovalenko

  3. Faculty of Management Science and Informatics, University of Žilina, Zilina, Slovakia

    Vitaly Levashenko

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Kovalenko, A., Kuchuk, H. (2022). Methods to Manage Data in Self-healing Systems. In: Ruban, I., Kovalenko, A., Levashenko, V. (eds) Advances in Self-healing Systems Monitoring and Data Processing. Studies in Systems, Decision and Control, vol 425. Springer, Cham. https://doi.org/10.1007/978-3-030-96546-4_3

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