Design of fault-tolerant structures for underwater sensor networks based on Markov chains

• Autorzy: Maksimov Maksim , Kozlov Oleksiy , Retsenko Serhii , Kryvda Viktoriia

Identyfikatory

DOI

10.14313/jamris‐2025‐006

• Języki publikacji: EN

Abstrakty

EN

Recently, underwater sensor networks (USN) have gained widespread adoption, proving instrumental in diverse research endeavors within the marine environment and across various scientific and technological domains. Considering the challenging operational conditions, a paramount issue in the present day is the creation of USNs with a predetermined fault tolerance margin. The primary focus of this study is the development and evaluation of a design method for fault-tolerant structures of USNs using Markov chains. The proposed method enables the creation of suitable USNs’ structures, ensuring a guaranteed attainment of the desired number of operational cycles before failure at reasonable costs. Utilizing the mathematical framework of Markov chains, coupled with the strategy of a well-selected sequence of hierarchy levels, enables the precise determination of the network’s actual number of operation cycles before failure as well as performing efficient reservation without excessive redundancy. To evaluate the efficacy of the proposed method, this study undertakes a specific case – the development of a fault-tolerant structure for a real USN with predetermined parameters. The analysis of the results obtained confirms the high feasibility of utilizing the developed method for crafting USNs for various purposes, ensuring a predefined level of fault tolerance while maintaining acceptable costs.

Słowa kluczowe

EN

underwater sensor network; fault tolerance; hierarchical structure; structure designing method; Markov chains

• Wydawca: Łukasiewicz Industrial Research Institute for Automation and Measurements PIAP
• Czasopismo: Journal of Automation Mobile Robotics and Intelligent Systems
• Rocznik: 2025
• Tom: Vol. 19, No. 1
• Strony: 49--64
• Opis fizyczny: Bibliogr. 61 poz., rys.

Twórcy

autor

Maksimov Maksim

• Department of Software and Computer‐integration Technologies, Odesa Polytechnic National University, Odesa, Ukraine, 65044

autor

Kozlov Oleksiy

• Department of Intelligent Information Systems, Petro Mohyla Black Sea National University, Mykolaiv, Ukraine, 54003

• https://orcid.org/0000-0003-2069-5578

autor

Retsenko Serhii

• Department of Armament, Ukrainian Naval Institute National University “Odesa Maritime Academy”, Odesa, Ukraine, 65052

autor

Kryvda Viktoriia

• Department of Power Supply and Energy Management, Odesà Polytechnic National University, Odesa, Ukraine, 65044

Bibliografia

• [1] A. Narwaria, A. P. Mazumdar, “Software-Defined Wireless Sensor Network: A Comprehensive Survey”, Journal of Network and Computer Applications, vol. 215, 2023, 103636. https://doi.org/10.1016/j.jnca.2023.103636
• [2] M. M. Rahaman, M. Azharuddin, “Wireless sensor networks in agriculture through machine learning: A survey”, Computers and Electronics in Agriculture, vol. 197, 2022, 106928. https://doi.org/10.1016/j.compag.2022.106928
• [3] Y. Wu., et al., “Epidemic spreading in wireless sensor networks with node sleep scheduling”,Physica A: Statistical Mechanics and its Applications, vol. 629, 2023, 129204. https://doi.org/10.1016/j.physa.2023.129204
• [4] E. Pievanelli, et al., “Dynamic wireless sensor networks for real time safeguard of workers exposed to physical agents in constructions sites,” 2013 IEEE Topical Conference on Wireless Sensors and Sensor Networks (WiSNet), Austin, TX, USA, 2013, pp. 55–57. doi: 10.1109/WiSNet.2013.6488632.
• [5] R. Elhabyan, W. Shi, M. St-Hilaire, “Coverage protocols for wireless sensor networks: Review and future directions”, Journal of Communications and Networks, vol. 21, no. 1, 2019, pp. 45–60. doi: 10.1109/JCN.2019.000005.
• [6] M. Kumar, et al., “Optimization of Wireless Sensor Networks Inspired by Small World Phenomenon”, 2015 IEEE 10th International Conference on Industrial and Information Systems(ICIIS), Peradeniya, Sri Lanka, 2015, pp. 66–70. doi: 10.1109/ICIINFS.2015.7398987.
• [7] R. G. Baldovino, I. C. Valenzuela, E. P. Dadios, “Implementation of a Low-power Wireless Sensor Network for Smart Farm Applications”, IEEE 10th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM), Baguio City, Philippines, 2018, pp. 1–5, doi: 10.1109/HNICEM.2018.86 66262.
• [8] H. K. Sethi, et al, “Incremental Model forComplete Area Coverage in Wireless Sensor Networks”, 2015 International Conference on Computational Intelligence and Networks, Odisha, India, 2015, pp. 92–97. doi: 10.1109/CINE.2015.27.
• [9] R. T. Tse, Y. Xiao, “A Portable Wireless Sensor Network system for real-time environmental monitoring”, 2016 IEEE 17th International Symposium on A World of Wireless, Mobile and Multimedia Networks(WoWMoM), Coimbra, Portugal, 2016, pp. 1–6. doi: 10.1109/WoWMoM.2016.7523588.
• [10] S. M. Kamruzzaman, et al., “Wireless Positioning Sensor Network Integrated with Cloud for Industrial Automation”, 2017 IEEE 42nd Conference on Local Computer Networks (LCN), Singapore, 2017, pp. 543–546. doi: 10.1109/LCN.2017.68.
• [11] I. A. Sawaneh, I. Sankoh, D. K. Koroma, “A survey on security issues and wearable sensors in wireless body area network for healthcare system”, 2017 14th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP), Chengdu, China, 2017, pp. 304–308. doi: 10.1109/ICCWAMTIP.2017.8301502.
• [12] J. Villadangos, et al., “Distributed Opportunistic Wireless Mapplicationing System towards Smart City Service Provision”, 2021 IEEE Sensors, Sydney, Australia, 2021, pp. 1–4. doi: 10.1109/SENSORS47087.2021.9639791.
• [13] S. Li, et al., “Survey on high reliability wireless communication for underwater sensor networks”, Journal of Network and Computer Applications, vol. 148, 2019, 102446.https://doi.org/10.1016/j.jnca.2019.102446
• [14] M. Ahmed, M. Salleh, M. I. Channa, “Routing protocols based on protocol operations for underwater wireless sensor network: A survey”, Egyptian Informatics Journal, vol. 19, no. 1, 2018, pp. 57–62. https://doi.org/10.1016/j.eij.2017.07.002
• [15] K. K. Gola, et al., “An empirical study on underwater acoustic sensor networks based onlocalization and routing approaches”, Advances in Engineering Software, vol. 175, 2023, 103319.https://doi.org/10.1016/j.advengsoft.2022.103319
• [16] G. Yang, et al., “Challenges and Security Issues in Underwater Wireless Sensor Networks”, Procedia Computer Science, vol. 147, 2019, pp. 210–216. https://doi.org/10.1016/j.procs.2019.01.225
• [17] I. F. Akyildiz, D. Pompili, T. Melodia, “Underwater acoustic sensor networks: research challenges”, Ad Hoc Networks, vol. 3, no. 3, 2005, pp. 257–279. https://doi.org/10.1016/j.adhoc.2005.01.004
• [18] M. Dong, et al., “Learning automaton-based energy-efficient and fault-tolerant topology evolution algorithm for underwater acoustic sensor network”, Journal of Network and Computer Applications, vol. 217, 2023, 103690. https://doi.org/10.1016/j.jnca.2023.103690
• [19] A. P. Das, S. M. Thampi, “Fault-resilient localization for underwater sensor networks”, Ad Hoc Networks, vol. 55, 2017, pp. 132–142. https://doi.org/10.1016/j.adhoc.2016.09.003
• [20] R. R. Priyadarshini, N. Sivakumar, “Failure prediction, detection & recovery algorithms using MCMC in tree-based network topology to improve coverage and connectivity in 3D-UW environment”, Applied Acoustics, vol. 158, 2020, 107053. https://doi.org/10.1016/j.apacoust.2019.107053
• [21] T. R. Chenthil, P. J. Jayarin, “Energy Efficient Clustering Based Depth Coordination Routing Protocol For Underwater Wireless Sensor Networks”, 2022 International Conference on Wireless Communications Signal Processing and Networking (WiSPNET), Chennai, India, 2022, pp. 370–375. doi: 10.1109/WiSPNET54241.2022.9767124
• [22] X. Liu, F. Zhou, “Energy-Efficient Routing Protocol Based on Data Dissemination for UnderwaterWireless Sensor Network”OCEANS 2023 - Limerick, Limerick, Ireland, 2023, pp. 1–5. doi: 10.1109/OCEANSLimerick52467.2023.10244378
• [23] G. Qiao, et al., “Distributed Localization Based on Signal Propagation Loss for Underwater Sensor Networks”, IEEE Access, vol. 7, 2019, pp. 112985–112995. doi: 10.1109/ACCESS.2019.2934978
• [24] A. Sabra, W. -k. Fung, P. Radhakrishna, “Confidence-based Underwater Localization Scheme for Large-Scale Mobile Sensor Networks”, OCEANS 2018 MTS/IEEE Charleston, Charleston, SC, USA, 2018, pp. 1–6. doi: 10.1109/OCEANS.2018.8604878
• [25] F. Steinmetz, B. -C. Renner, “From the Long-Range Channel in the Ocean to the Short-Range and Very Shallow-Water Acoustic Chan-nel in Ports and Harbors”, 2021 Fifth Underwater Communications and Networking Conference (UComms), Lerici, Italy, 2021, pp. 1–5. doi: 10.1109/UComms50339.2021.9598094
• [26] D. Schütze et al., “Miniaturized Sensor Modules for under Water Applications realized byPrinted Circuit Board Embedding Technology”,2022 IEEE 9th Electronics System-Integration Technology Conference (ESTC), Sibiu, Romania, 2022, pp. 49–54. doi: 10.1109/ESTC55720.2022.9939405
• [27] G. Sang et al., “Three-Wavelength Fiber Laser Sensor With Miniaturization, Integration for the Simultaneous Measurement of Underwater pH, Salinity, Temperature, and Axial Strain”, IEEE Transactions on Instrumentation and Measurement, vol. 72, 2023, Art no. 7006815, pp. 1–15. doi: 10.1109/TIM.2023.3309356.
• [28] B. Mishachandar, S. Vairamuthu, “An underwater cognitive acoustic network strategy for efficient spectrum utilization”, Applied Acoustics, vol. 175, 2021, 107861. https://doi.org/10.1016/j.apacoust.2020.107861
• [29] H. Dol et al., “EDA-SALSA: Development of a self-reconfigurable protocol stack for robust under-water acoustic networking”, OCEANS 2023 - Limerick, Limerick, Ireland, 2023, pp. 1–10. doi: 10.1109/OCEANSLimerick52467.2023.10244330.
• [30] H. Li, et al., “Security and privacy in localization for underwater sensor networks”, IEEE Communications Magazine, vol. 53, no. 11, 2015, pp. 56–62. doi: 10.1109/MCOM.2015.7321972.
• [31] X. Feng, Z. Wang, N. Han, “Protection Research of Sink Location Privacy in Underwater Sensor Networks”, IEEE INFOCOM 2019 - IEEE Conference on Computer Communications Workshops (INFO-COM WKSHPS), Paris, France, 2019, pp. 1–6. doi:10.1109/INFOCOMWKSHPS47286.2019.9093749.
• [32] N. V. U. Reddy, “Reducing the Network Latency to Maintain Network Stability in UASN by Using Bio-Inspired Algorithms”, 2023 Second International Conference on Augmented Intelligence and Sustainable Systems(ICAISS), Trichy, India, 2023, pp. 139–144. doi: 10.1109/ICAISS58487.2023.10250497. [33] S. Kaveripakam, R. Chinthaginjala, “Clustering-based dragonfly optimization algorithm for underwater wireless sensor networks”, Alexandria Engineering Journal, vol. 81, 2023, pp. 580–598. https://doi.org/10.1016/j.aej.2023.09.047
• [34] O.V. Kozlov, Y.P. Kondratenko, O.S. Skakodub, “Information Technology for Parametric Optimization of Fuzzy Systems Based on Hybrid Grey Wolf Algorithms”, SN Computer Science, vol. 3, no. 6, 2022. 463. https://doi.org/10.1007/s42979-022-01333-4
• [35] Y.P. Kondratenko, A.V. Kozlov, “Parametric optimization of fuzzy control systems based on hybrid particle swarm algorithms with elite strategy”, Journal of Automation and Information Sciences, vol. 51, no. 12, 2019, New York: BegelHouse Inc., pp. 25–45. DOI: 10.1615/JAutomatIn fScien.v51.i12.40
• [36] O.V. Kozlov, “Optimal Selection of Membership Functions Types for Fuzzy Control and Decision Making Systems”, in: Proceedings of the 2nd International Workshop on Intelligent Information Technologies & Systems of Information Security with CEUR-WS, Khmelnytskyi, Ukraine, IntelITSIS 2021, CEUR-WS, Vol-2853, 2021, pp.238–247.
• [37] “Advance trends in soft computing”, M. Jamshidi, V. Kreinovich, J. Kacprzyk, Eds. Cham: Springer-Verlag, 2013. DOI https://doi.org/10.1007/978-3-319-03674-8
• [38] J. Kacprzyk, Y. Kondratenko, J. M. Merigo, J. H. Hormazabal, G. Sirbiladze, A. M. Gil-Lafuente, “AStatus Quo Biased Multistage Decision Model for Regional Agricultural Socioeconomic Planning Under Fuzzy Information”, In: Y.P. Kondratenko, A.A. Chikrii, V.F. Gubarev, J. Kacprzyk (Eds) Advanced Control Techniques in Complex Engineering Systems: Theory and Applications. Dedicated to Professor Vsevolod M. Kuntsevich. Studies in Systems, Decision and Control, Vol. 203. Cham: Springer Nature Switzerland AG, 2019, 201-226. DOI: https://doi.org/10.1007/978-3-030-21927-7_10
• [39] O. Kozlov, G. Kondratenko, Z. Gomolka, Y. Kondratenko, “Synthesis and Optimization of Green Fuzzy Controllers for the Reactors of the Specialized Pyrolysis Plants”, Kharchenko V., Kondratenko Y., Kacprzyk J. (Eds) Green IT Engineering: Social, Business and Industrial Applications, Studies in Systems, Decision and Control, Vol 171, 2019, Springer, Cham, 373–396. https://doi.org/10.1007/978-3-030-00253-4_16
• [40] I. Atamanyuk, J. Kacprzyk, Y. Kondratenko, M. Solesvik, “Control of Stochastic Systems Based on the Predictive Models of Random Sequences”, In: Y.P. Kondratenko, A.A. Chikrii, V.F. Gubarev, J. Kacprzyk (Eds) Advanced Control Techniques in Complex Engineering Systems: Theory and Applications. Dedicated to Professor Vsevolod M. Kuntsevich. Studies in Systems, Decision and Control, vol. 203. Cham: Springer Nature Switzerland AG, 2019, 105–128. https://doi.org/10.1007/978-3-030-21927-7_6
• [41] Y.P. Kondratenko, O.V. Kozlov, “Mathematical Model of Ecopyrogenesis Reactor with Fuzzy Parametrical Identification”, Recent Developments and New Direction in SoftComputing Foundations and Applications, Studies in Fuzziness and Soft Computing, vol. 342, Lotfi A. Zadeh et al. (Eds.). Berlin, Heidelberg: Springer-Verlag, 2016, 439-451. https://doi.org/10.1007/978-3-319-32229-2_30
• [42] Y.P. Kondratenko, O.V. Korobko, O.V. Kozlov, “Frequency Tuning Algorithm for Loudspeaker Driven Thermoacoustic Refrigerator Optimization”, in: K. J. Engemann, A. M. Gil-Lafuente, J. M. Merigo (Eds.), Lecture Notes in Business Information Processing, volume 115 of Modeling and Simulation in Engineering, Economics and Management, Springer-Verlag, Berlin, Heidelberg: 2012, pp. 270–279. https://doi.org/10.1007/978-3-642-30433-0_27.
• [43] M. Dong, et al., “Energy-saving and Fault-tolerant Topology for Underwater Acoustic Sensor Networks”, OCEANS 2022,Hampton Roads, Hampton Roads, VA, USA, 2022, pp. 1–5. doi: 10.1109/OCEANS47191.2022.9977158
• [44] M. Hamidzadeh, N. Forghani, A. Movaghar, “A new hierarchal and scalable architecture for performance enhancement of large scale under-water sensor networks”, 2011 IEEE Symposium on Computers & Informatics, Kuala Lumpur, Malaysia, 2011, pp. 520–525. doi: 10.1109/ISCI.2011.5958970
• [45] G.H. Adday, et al., “Fault Tolerance Structures in Wireless Sensor Networks (WSNs): Survey, Classification, and Future Directions”, Sensors 2022, 22, 6041. https://doi.org/10.3390/s22166041
• [46] L. Vihman, M. Kruusmaa, J. Raik, “Systematic Review of Fault Tolerant Techniques in Under- water Sensor Networks”, Sensors 2021, 21, 3264.https://doi.org/10.3390/s21093264
• [47] N. Goyal, M. Dave, A. K. Verma, “A novel fault detection and recovery technique for cluster-based underwater wireless sensor networks”, Int. J. Commun. Syst. 2018, vol. 31, pp. 1–14. https://doi.org/10.1002/dac.3485
• [48] Z. Zhou, et al., “E-CARP: An Energy Efficient Routing Protocol for UWSNs in the Internet of Underwater Things”, IEEE Sensors Journal, vol. 16, no. 11, pp. 4072–4082, 2016. doi: 10.1109/JSEN.2015.2437904
• [49] Y. Noh et al., “HydroCast: Pressure Routing for Underwater Sensor Networks”, IEEE Transactions on Vehicular Technology, vol. 65, no. 1, 2016, pp. 333–347. doi: 10.1109/TVT.2015.2395434
• [50] N. Desai, S. Punnekkat, “Enhancing Fault Detection in Time Sensitive Networks using Machine Learning”, 2020 International Conference on COMmunication Systems & NETworkS (COMSNETS), Bengaluru, India, 2020, pp. 714–719. doi: 10.1109/COMSNETS48256.2020.9027357
• [51] A. Shahraki, et al., “A Survey and Future Directions on Clustering: From WSNs to IoT and Modern Networking Paradigms”, IEEE Transactions on Network and Service Management, vol. 18, no. 2, 2021, pp. 2242–2274. doi: 10.1109/TNSM.2020.3035315
• [52] K. Wang, et al., “An Energy-Efficient Reliable Data Transmission Scheme for Complex Environmental Monitoring in Underwater Acoustic Sensor Networks”, IEEE Sensors Journal, vol. 16, no. 11, 2016, pp. 4051–4062. doi: 10.1109/JSEN.2015.2428712
• [53] Y. Wang, L. Cao, T. A. Dahlberg, “Efficient Fault Tolerant Topology Control for Three-Dimensional Wireless Networks”, 2008 Proceedings of 17th International Conference on Computer Communications and Networks, St. Thomas, VI, USA, 2008, pp. 1–6. doi:10.1109/ICCCN.2008.ECP.75
• [54] K. A. Alansary, et al., “Networked Control System Architecture for Autonomous Underwater Vehicles with Redundant Sensors”, 2019 11th International Conference on Electronics, Computers and Artiϔicial Intelligence (ECAI), Pitesti, Romania, 2019, pp. 1–4. doi: 10.1109/ECAI46879.2019.9042033
• [55] D. Li, J. Du, L. Liu, “A data forwarding algorithm based on Markov thought in underwater wireless sensor networks”, International Journal of Distributed Sensor Networks, 2017, 13(2). doi: 10.1177/1550147717691982
• [56] S. Petridou, S. Basagiannis, M. Roumeliotis, “Survivability Analysis Using Probabilistic Model Checking: A Study onWireless Sensor Networks”, IEEE Systems Journal, vol. 7, no. 1, 2013, pp. 4–12.doi: 10.1109/JSYST.2012.2224612
• [57] M. Martalo, S. Busanelli, G. Ferrari, “Multihop IEEE 802.15.4 Wireless Networks With Finite Node Buffers: Markov Chain-Based Analysis”, 2008 IEEE 10th International Symposium on Spread Spectrum Techniques and Applications, Bologna, Italy, 2008, pp. 644–648. doi: 10.1109/ISSSTA.2008.126
• [58] L. Xie, P. E. Heegaard, Y. Jiang, “Non-Markovian Survivability Assessment Model for InfrastructureWireless Networks”, 2018 15th International Symposium on Wireless Communication Systems (ISWCS), Lisbon, Portugal, 2018, pp. 1–5. doi: 10.1109/ISWCS.2018.8491067
• [59] S.N. Pelykh, M.V. Maksimov, “The method of fuel rearrangement control considering fuel element cladding damage and burnup”, Problems of Atomic Science and Technology, vol. 87, no. 5, 2013, 84–90. https://vant.kipt.kharkov.ua/ARTICLE/VANT_2013_5/article_2013_5_84a.pdf
• [60] M.V. Maksimov, S.N. Pelykh, R.L. Gontar, “Principles of controlling fuel-element cladding lifetime in variable VVER-1000 loading regimes”, Atomic Energy, vol. 112, no. 4, 2012, 241-249. h t tps://doi.org/10.1007/s10512-012-9552-3
• [61] I.G. Maysyan, M. V. Maksimov, “Methodology for Assessing the Reliability of ACS TP Software Using Failure Recovery”, Bulletin of Cherkasy State Technological University, vol. 3, 2006, pp. 8–13. (In Russian).

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).