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Two-Terminal Reliability Analysis of Telecommunication Networks Based on Reduction Method

https://doi.org/10.32603/1993-8985-2025-28-6-56-70

Abstract

Introduction. Methods for assessing the reliability of communication networks require simple and effective calculation tools. Although reduction methods allow the analysis of complex systems to be simplified, their application is limited by certain conditions.

Aim. To investigate a reduction method based on the sequential transformation of networks with serial and parallel connections into equivalent circuits. Bipolar connectivity that implies a path between two dedicated nodes is considered, in contrast to multipolar connectivity that evaluates connectivity between several critical nodes and all-pole connectivity that requires paths between all nodes of the network.

Materials and methods. Purely sequential and purely parallel structures, as well as their combinations, are considered. For sequential systems, the probability of operability is defined as the product of the serviceability probabilities of the elements, for parallel systems – through the probability of failure of all components.

Results. For mixed structures, a reduction algorithm for calculating their reliability using simplified formulas is proposed. The reduction procedure and the final formulas for calculating network reliability are directly derived from the rules for serial and parallel connections. A communication network was used as an example to confirm the method accuracy provided that the failures of the elements are independent.

Conclusion. The demonstrated reduction method is effective for analyzing the reliability of communication networks with series-parallel structures. The accuracy of calculations depends significantly on the assumption of the independence of failures. The advantages of the method include its simplicity and clarity; however, the method is inapplicable in cases of gradual failures and the interdependence of elements. In addition, this method processes correctly only loaded redundancy; for systems with unloaded or lightweight redundancy, the method needs to be modified. Computational difficulties for large-size networks and the possibility of information loss about the criticality of elements is noted. This is related to the loss of data on the contribution of individual components to the overall reliability of the system in the process of simplification, which impedes the analysis of weak links. The results obtained can be used in the design and optimization of communication networks, as well as for assessing their operational reliability.

About the Author

K. A. Batenkov
MIREA – Russian Technological University
Russian Federation

Kirill A. Batenkov, Dr Sci. (Eng.) (2016), Professor (2023), Professor of the Department of Applied Mathematics

78, Vernadsky Ave., Moscow 119454



References

1. Oszczypała M., Ziółkowski J., Małachowski J. Reliability Analysis of Military Vehicles Based on Censored Failures Data.Appl. Sci. 2022, vol. 12, no. 5, art. no. 2622. doi: 10.3390/app12052622

2. Zhang Q., Tang N., Fu X., Peng H., Bo C., Wang C. A Multi-Scale Attention Mechanism Based Domain Adversarial Neural Network Strategy for Bearing Fault Diagnosis. Actuators. 2023, vol. 12, no. 5, art. no. 188. doi: 10.3390/act12050188

3. Donath L. E., Mircea G., Neamțu M., Noja G. G., Sîrghi N. The Effect of Network Delay and Contagion on Mobile Banking Users: A Dynamical Analysis. Mathematics. 2024, vol. 12, no. 22, art. no. 3493. doi: 10.3390/math12223493

4. Yan J., Sui Y., Dai T. A Particle Swarm Optimization-Based Ensemble Broad Learning System for Intelligent Fault Diagnosis in Safety-Critical Energy Systems with High-Dimensional Small Samples. Mathematics. 2025, vol. 13, no. 5, art. no. 797. doi: 10.3390/math13050797

5. Mahbub K., Nehme A., Patwary M., Lacoste M., Allio S. FIVADMI: A Framework for In-Vehicle Anomaly Detection by Monitoring and Isolation. Future Internet. 2024, vol. 16, no. 8, art. no. 288. doi: 10.3390/fi16080288

6. Koo B., Bae J., Kim S., Park K., Kim H. Test Case Generation Method for Increasing Software Reliability in Safety-Critical Embedded Systems. Electronics. 2020, vol. 9, no. 5, art. no. 797. doi: 10.3390/electronics9050797

7. Xu W., Ma D. A Framework for Model and Verification of Safety-Critical Operating System Based on ARINC653. Electronics. 2021, vol. 10, no. 16, art. no. 1934. doi: 10.3390/electronics10161934

8. Si D., Jiang B., Xia Q., Li T., Wang X., Liu J. Cyber Potential Metaphorical Map Method Based on GMap. ISPRS Int. J. of Geo-Information. 2025, vol. 14, no. 2, art. no. 46. doi: 10.3390/ijgi14020046

9. Zang T., Tong X., Li C., Gong Y., Su R., Zhou B. Research and Prospect of Defense for Integrated Energy Cyber–Physical Systems Against Deliberate Attacks. Energies. 2025, vol. 18, no. 6, art. no. 1479. doi: 10.3390/en18061479

10. Zhang W., Zhang G., Dong F., Xie Z., Bian D. Capacity Model and Constraints Analysis for Integrated Remote Wireless Sensor and Satellite Network in Emergency Scenarios. Sensors. 2015, vol. 15, no. 11, pp. 29036−29055. doi: 10.3390/s151129036

11. Shikha Sh., Meghana K. M., Manjunath C. R., Santosh N. Comparison of Wireless Network Over Wired Network and Its Type. Int. J. of Research − Granthaalayah. RACSIT-17. 2017, vol. 5, no. 4, pp. 14–20. doi: 10.5281/zenodo.572289

12. Luo W., Zeng Y., Zheng X., Zha L., Cai W., Wang Q., Zhang J. System Design and Reliability Improvement of Wireless Sensor Network in Plant Factory Scenario. Agronomy. 2025, vol. 15, no. 3, art. no. 751. doi: 10.3390/agronomy15030751

13. Navarro-Ortiz J., Ramos-Munoz J. J., DelgadoFerro F., Canellas F., Camps-Mur D., Emami A., Falaki H. Combining 5G New Radio, Wi-Fi, and LiFi for Industry 4.0: Performance Evaluation. Sensors. 2024, vol. 24, no. 18, art. no. 6022. doi: 10.3390/s24186022

14. Othman W. M., Ateya A. A., Nasr M. E., Muthanna A., ElAffendi M., Koucheryavy A., Hamdi A. Key Enabling Technologies for 6G: The Role of UAVs, Terahertz Communication, and Intelligent Reconfigurable Surfaces in Shaping the Future of Wireless Networks. J. of Sensor and Actuator Networks. 2025, vol. 14, no. 2, art. no. 30. doi: 10.3390/jsan14020030

15. Vaibhav G., Om P. Y., Gunjan S., Ajay P. S. R. A Literature Review on Network Reliability Analysis and Its Engineering Applications. Proc. of the Institution of Mechanical Engineers Part O J. of Risk and Reliability. 2021, vol. 235, no. 1, pp. 167–181. doi: 10.1177/1748006X20962258

16. Batenkov A. A., Batenkov K. A., Fokin A. B. Digital Information Telecommunication Technologies. Trudy SPIIRAN. 2020, vol. 19, no. 3, pp. 644−673. (In Russ.) doi: 10.15622/sp.2020.19.3.7

17. Shi H., Wang N., Liu Q. Calculation Method for Sortie Mission Reliability of Shipborne Unmanned Vehicle Group. J. of Marine Science and Engineering. 2024, vol. 12, no. 8, art. no. 1309. doi: 10.3390/jmse12081309

18. Silva I., Guedes L. A., Portugal P., Vasques F. Reliability and Availability Evaluation of Wireless Sensor Networks for Industrial Applications. Sensors. 2012, vol. 12, no. 1, pp. 806−838. doi: 10.3390/s120100806

19. Liang J., Zhao H., Xie S. A Method for Calculating the Reliability of 2-Separable Networks and Its Applications. Axioms. 2024, vol. 13, no. 7, art. no. 459. doi: 10.3390/axioms13070459

20. Batenkov A. A., Batenkov K. A., Fokin A. B. Telecommunication Network Connectivity Probability Analysis Based on Independent Events Matrix. Avtomatika i Telemekhanika. 2023, no. 11, pp. 77−92. (In Russ.) doi: 10.31857/S0005231023110053

21. Dong L., Zhao H., Lai H.-J. Local Optimality of Mixed Reliability for Several Classes of Networks with Fixed Sizes. Axioms. 2022, vol. 11, no. 3, art. no. 91. doi: 10.3390/axioms11030091

22. Hao Y., Yao Y., Zhang Y., Zuo F. Reliability Analysis of Multi-Autonomous Underwater Vehicle Cooperative Systems Based on Fuzzy Control. Photonics. 2025, vol. 12, no. 4, art. no. 333. doi: 10.3390/photonics12040333

23. Li F., Liu W., Gao W., Liu Y., Hu Y. Design and Reliability Analysis of a Novel Redundancy Topology Architecture. Sensors. 2022, vol. 22, no. 7, art. no. 2582. doi: 10.3390/s22072582

24. Batenkov A. A., Batenkov K. A., Fokin A. B. Forming the Telecommunication Networks' CrossSections to Analyze the Latter Stability with Different Connectivity Measures. Informatics and Automation. 2021, vol. 2, iss. 20, pp. 371−406. (In Russ.) doi: 10.15622/ia.2021.20.2.5

25. Zarezadeh S., Ashrafi S., Asadi M. Network Reliability Modeling Based on a Geometric Counting Process. Mathematics. 2018, vol. 6, no. 10, art. no. 197. doi: 10.3390/math6100197

26. Alexandrov A. E., Borisov S. P., Bunina L. V., Bikovsky S. S., Stepanova I. V., Titov A. P. Statistical Model for Assessing the Reliability of Non-Destructive Testing Systems by Solving Inverse Problems. Russ. Technological J. 2023, vol. 11, no. 3, pp. 56−69. (In Russ.) doi: 10.32362/2500-316X-2023-11-3-56-69

27. Batenkov K. A. Analysis and Synthesis of Communication Network Structures by State Enumeration Method. Vestnik Sankt Peterburgskogo Universiteta. Seriya 10. Prikladnaya Matematika. Informatika. Protsessy Upravleniya. 2022, vol. 18, no. 3, pp. 300–315. (In Russ.) doi: 10.21638/11701/spbu10.2022.301

28. Kuo W., Wan R. Recent Advances in Optimal Reliability Allocation. IEEE Trans. on Systems, Man and Cybernetics. Part A. IEEE Trans. 2007, vol. 37, no. 2, pp. 143−156. doi: 10.1109/TSMCA.2006.889476

29. Payette M., Abdul-Nour G. Machine Learning Applications for Reliability Engineering: A Review. Sustainability. 2023, vol. 15, no. 7, art. no. 6270. doi: 10.3390/su15076270

30. Misra K. B. Handbook of Performability Engineering. London, Springer Verlag, 2008, 1316 p. doi: 10.1007/978-1-84800-131-2

31. Konak A., Smith A. E. Network Reliability Optimization. Ed. by M. G. C. Resende, P. M. Pardalos. Handbook of Optimization in Telecommunications. Boston, MA, Springer, 2006, pp. 735−760. doi: 10.1007/978-0-387-30165-5_26

32. Batenkov K. A., Batenkov A. A. Analysis and Synthesis of Communication Network Structures According to the Determined Stability Indicators. Trudy SPIIRAN. 2018, no. 58 (3), pp. 128−159. (In Russ.) doi: 10.15622/sp.58.6

33. Garg H., Ram M. Reliability Management and Engineering: Challenges and Future Trends (1st ed.). Boca Raton, CRC Press, 2020, 300 p. doi: 10.1201/9780429268922

34. Batenkov K. A. Accurate and boundary Estimate of Communication Network Connectivity Probability Based on Model State Complete Enumeration Method. Trudy SPIIRAN. 2019, no. 5 (18), pp. 1093−1118. (In Russ.) doi: 10.15622/sp.2019.18.5.1093-1118

35. Batenkov K. A., Fokin A. B. Analysis of the Structural Reliability of Communication Networks Supporting Protective Switching Mechanisms for One Protected Section and One Backup Section. Russ. Technological J. 2024, vol. 12, no. 2, pp. 39–47. (In Russ.) doi: 10.32362/2500-316X-2024-12-2-39-47

36. Iglesias R., Pascual-Ortigosa P., Sáenz-deCabezón E. An Algebraic Version of the Sum-ofdisjoint-products Method for Multi-state System Reliability Analysis. Proc. Int. Symp. Symbolic and Algebraic Computation (ISSAC '22), Villeneuve-d’Ascq, France, 4–7 July 2022. Association for Computing Machinery, 2022, pp. 509–516. doi: 10.1145/3476446.3535472

37. Chan J., Paredes R., Papaioannou I., DuenasOsorio L., Straub D. Adaptive Monte Carlo Methods for Estimating Rare Events in Power Grids. TechRxiv. 2024, pp. 1−10. doi: 10.36227/techrxiv.170654653.30299222/v1

38. Beheshti Nezhad H., Miri M., Ghasemi M. R. New Neural Network-Based Response Surface Method for Reliability Analysis of Structures. Neural Computing and Applications. 2019, vol. 31, pp. 777−791. doi: 10.1007/s00521-017-3109-2

39. Pabst S., Nam Y. A Quantum Algorithm for Network Reliability. Available at: https://arxiv.org/pdf/2203.10201 (accessed 29.04.2025)


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Batenkov K.A. Two-Terminal Reliability Analysis of Telecommunication Networks Based on Reduction Method. Journal of the Russian Universities. Radioelectronics. 2025;28(6):56-70. (In Russ.) https://doi.org/10.32603/1993-8985-2025-28-6-56-70

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ISSN 1993-8985 (Print)
ISSN 2658-4794 (Online)