بررسی قابلیت اطمینان با معماری جدید مدل مارکوف گره پشتیبان با نرخ تعمیر و تعویض بهتر و نظارت بیشتر در پرهیز از خرابی شبکه‌های حسگر بی‌سیم صنعتی

محورهای موضوعی : مهندسی برق و کامپیوتر

احمدرضا زمانی ¹ (دانشکده گروه مهندسی مکانیک، برق و کامپیوتر واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران)
محمد علی پور مینا ² (دانشکده مهندسی مکانیک، برق و کامپیوتر، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی، تهران، ایران)
رامین شقاقی کندوان ³ (دانشکده گروه مهندسی برق و کامپیوتر واحد یادگار امام خمینی(ره) شهر ری، دانشگاه آزاد اسلامی، تهران، ایران)

تاریخ دریافت : 1402/08/11 تاریخ پذیرش : 1403/01/10 تاریخ انتشار : 1403/09/30

کلید واژه: افزونگی گره پشتیبان, تحمل‌پذیری خطا, حسگر آماده‌باش, شبکه‌های حسگر بی‌سیم , قابلیت اطمینان,

چکیده مقاله :

گره‌های حسگر به¬دلیل کاربردهای متنوع محیط‌های عملیاتی، مستعد خرابی هستند. ایده این مقاله، ارایه یک¬معماری جدید با مدل مارکوف برای بهبود قابلیت اطمینان می¬باشد. در اصلاح ایده¬هاي قبل با توجه به خستگي¬كاري، هزينه مصرف انرژي و تعميرات بالا مي¬توان از ایده افزایش نرخ تعمیر و تعویض در پرهیز از خرابی با در¬دسترس¬بودن گره¬های جایگزین با برنامه¬ريزي دقیق تعمیرات ، بهره برد. مزاياي این¬روش کاهش میزان خرابی ، افزایش قابلیت اطمینان، پیاده سازی و استقرار سریع، بهره¬وری انرژی و صرفه¬جویی اقتصادی، بهبود عملکرد و عمر مفید شبکه، کاهش تاخير و جوان¬سازی و پویایی سیستم می¬با¬شد. ساختار روش پیشنهادی با استفاده از حالت خواب و بیداری گره آماده به¬کار سرد یا گرم به¬گونه¬ای است که گره یدکی به موازات گره اصلی قرار می¬گیرد و در صورت آسیب-دیدن یک یا دو گره، سیستم برگشت¬پذیر می¬باشد و می¬توان خرابی را تعمیر یا جایگزین نمود. تکنیک‌ زمان بیکاری و در¬دسترس¬بودن حسگر یدک پشتیبان ، نقش مهمی در کاهش مصرف انرژی دارد. و کارشناسان واحد پشتیباني تنظیمات پیکربندی را به گونه‌ای انجام می¬دهند تا در زمان بیکاری، تجهیزات به حالت خاموشی یا آماده¬به¬کار بروند و در صورت آسیب¬دیدن یک یا دو گره، ابتدا گره یدکی سالم بیدار و در سرویس و سپس گره آسیب¬دیده تعمیر و تعویض ¬و در حالت آماده¬به¬کار یا خواب قرار گیرد. از نتایج حاصل از نوآوري این روش، تأکید بر نظارت سلامتی گره، جلوگیری از خرابی و بهبود نرخ تعمیر و تعویض، کاهش مصرف و بهره¬وری انرژی می‌توان اشاره نمود. نتایج شبیه‌سازی در مقایسه با مدلهای قبل، بهبود بهتری را نشان می¬دهد.

چکیده انگلیسی:

Sensor nodes are prone to failure due to the various applications of operating environments. This paper presents a new architecture with a Markov model to improve reliability. In the modification of the previous ideas, due to work fatigue, energy consumption and high maintenance costs, the idea of increasing the repair and replacement rate to avoid failure with the availability of replacement nodes with detailed planning of the support unit.The advantages of this method are reducing the failure rate, increasing reliability, fast implementation and deployment, energy efficiency and economic savings, improving the performance and useful life of the network, reducing delay and system rejuvenation and dynamics.The structure of the proposed method is by using the sleep and wake mode of the hot or cold standby node in such a way that the spare node is placed parallel to the main node and if one or both nodes are damaged, the system is reversible and. the damage can be repaired or replaced. The technique of idle time and the availability of the backup spare sensor play an important role in reducing energy consumption. The experts of the support unit perform the configuration settings so that the equipment goes to sleep or standby mode during idle time. And if one or two nodes are damaged, first the healthy spare¬node is awake and in service, and then the damaged node is repaired and replaced and placed in standby or sleep mode. The results of the innovation, we can mention the emphasis on node health monitoring, failure avoidance, improving repair and replacement rates and efficiency. The simulation results show a better improvement compared to the previous models.

منابع و مأخذ:

J. N. pour, M. A. Pourmina, M. N. Moghaddasi, and B. Ghalamkari, "An artificial intelligent network model to monitor the condition of a patient with a breast tumor based on fuzzy logic," Health and Technology, vol. 14, no. 1, pp. 119-139, 2024, doi: https://doi.org/10.1007/s12553-023-00800-z.
[2] D. Bein, V. Jolly, B. Kumar, and S. Latifi, "Reliability modeling in wireless sensor networks," International Journal of Information Technology, vol. 11, no. 2, pp. 1-8, 2005, doi: 10.2174/1872212113666191209091947.
[3] L. Xing, H. Li, and H. E. Michel, "Fault-tolerance and reliability analysis for wireless sensor networks," International Journal of Performability Engineering, vol. 5, no. 5, p. 419, 2009, doi: 10.23940/ijpe.09.5.p419.mag.
[4] C. Vasar, O. Prostean, I. Filip, R. Robu, and D. Popescu, "A reliability analysis for wireless sensor networks in a wind farm," in 2009 XXII International Symposium on Information, Communication and Automation Technologies, 2009: IEEE, pp. 1-5, doi: 10.1109/ICAT.2009.5348408.
[5] M. Chahine, C. Taddia, and G. Mazzini, "Reliable Data Forwarding in Wireless Sensor Networks: Delay and Energy Trade Off," SCIYO. COM, p. 289, 2010, doi: 10.5772/10168.
[6] V. Kumar, R. Patel, M. Singh, and R. Vaid, "Markov model for reliable packet delivery in Wireless Sensor Networks," International Journal of Computer Science Issues (IJCSI), vol. 8, no. 3, p. 429, 2011, doi: 10.1109/ICCP.2009.5284742.
[7] R. Kim, J. Song, and B. F. Spencer Jr, "Reliability analysis of wireless sensor networks," in Proceedings of the 6th international workshop on advanced smart materials and smart structures technology ANCRiSST2011, 2011, pp. 1-12, doi: 10.1109/ICON.2008.4772586.
[8] I. Silva, L. A. Guedes, P. Portugal, and F. Vasques, "Reliability and availability evaluation of Wireless Sensor Networks for industrial applications," Sensors (Basel), vol. 12, no. 1, pp. 806-38, 2012, doi: 10.3390/s120100806.
[9] L. Venkatesan, S. Shanmugavel, and C. Subramaniam, "A survey on modeling and enhancing reliability of wireless sensor network," Wireless Sensor Network, vol. 5, no. 03, p. 41, 2013, doi: 10.4236/wsn.2013.53006.
[10] M. Kumar, R. Tripathi, and S. Tiwari, "A reliable real-time routing protocol for industrial wireless sensor networks," in 2014 International Conference on Power, Control and Embedded Systems (ICPCES), 2014: IEEE, pp. 1-5, doi: 10.1109/ICPCES.2014.7062831.
[11] C. Wang, L. Xing, V. M. Vokkarane, and Y. L. Sun, "Reliability and lifetime modeling of wireless sensor nodes," Microelectronics Reliability, vol. 54, no. 1, pp. 160-166, 2014, doi: https://doi.org/10.1016/j.microrel.2013.08.001.
[12] A. Munir, J. Antoon, and A. Gordon-Ross, "Modeling and analysis of fault detection and fault tolerance in wireless sensor networks," ACM Transactions on Embedded Computing Systems (TECS), vol. 14, no. 1, pp. 1-43, 2015, doi: 10.1145/2680538.
[13] M. Kumar, R. Tripathi, and S. Tiwari, "Critical data real‐time routing in industrial wireless sensor networks," IET Wireless Sensor Systems, vol. 6, no. 4, pp. 144-150, 2016, doi: 10.1049/iet-wss.2015.0060.
[14] M. Kumar, R. Tripathi, and S. Tiwari, "QoS guarantee towards reliability and timeliness in industrial wireless sensor networks," Multimedia Tools and Applications, vol. 77, no. 4, pp. 4491-4508, 2018, doi: 10.1007/s11042-017-4832-5.
[15] D. Deif and Y. Gadallah, "A comprehensive wireless sensor network reliability metric for critical Internet of Things applications," EURASIP Journal on Wireless Communications and Networking, vol. 2017, pp. 1-18, 2017, doi: 10.1186/s13638-017-0930-3.
[16] I. Kabashkin and J. Kundler, "Reliability of sensor nodes in wireless sensor networks of cyber physical systems," Procedia Computer Science, vol. 104, pp. 380-384, 2017, doi: 10.1016/j.procs.2017.01.149.
[17] P. Zhou et al., "A comprehensive technological survey on dependable self-managing CPS: The decade of researches on correctness and dependability," 2017, doi: 10.20944/ preprints201707.0044.V1.
[18] P. A. Wumnaya, S. Musyoki, and W. Mwangi, "Reliability and Availability Analysis of a Triplex Sensor Node System with Shared Repair," International Journal for Modern Trends in Science and Technology, vol. 4, no. 06, pp. 79-83, 2018, doi: https://doi.org/10.3390/s120100806.
[19] R. M. Ostberg, "Investing in a Better World: A Study of Country-Level Factors on Investment Outcomes," 2013.
[20] S. Zoppi, S. P. Shantharam, and W. Kellerer, "Delay-reliability model of industrial WSN for networked control systems," in GLOBECOM 2020-2020 IEEE Global Communications Conference, 2020: IEEE, pp. 1-7, doi: 10.1109/GLOBECOM42002.2020.9348072.
[21] M. Catelani, L. Ciani, A. Bartolini, C. Del Rio, G. Guidi, and G. Patrizi, "Reliability Analysis of Wireless Sensor Network for Smart Farming Applications," Sensors (Basel), vol. 21, no. 22, p. 7683, Nov 18 2021, doi: 10.3390/s21227683.
[22] H. Yang, F. Li, D. Yu, Y. Zou, and J. Yu, "Reliable data storage in heterogeneous wireless sensor networks by jointly optimizing routing and storage node deployment," Tsinghua Science and Technology, vol. 26, no. 2, pp. 230-238, 2020, doi: 10.26599/TST.2019.9010061.
[23] L. Xing, "Reliability modeling of wireless sensor networks: a review," Recent Patents on Engineering, vol. 15, no. 1, pp. 3-11, 2021, doi: 10.3390/s120100806.
[24] J. Persis, "A novel routing protocol for underwater wireless sensor network using pareto uninformed and heuristic search techniques," Wireless Personal Communications, vol. 121, no. 3, pp. 1917-1944, 2021, doi: 10.1007/s11277-021-08747-y.
[25] H. Zhang et al., "Delay-reliability-aware protocol adaption and quality of service guarantee for message queuing telemetry transport-empowered electric Internet of things," International Journal of Distributed Sensor Networks, vol. 18, no. 5, p. 15501329221097815, 2022, doi: 10.1177/15501329221097815.
[26] F. Joglar, "Reliability, availability, and maintainability," SFPE Handbook of Fire Protection Engineering, pp. 2875-2940, 2016, doi: 10.1007/978-1-4939-2565-0_74.
[27] M. Rentschler and P. Laukemann, "Performance analysis of parallel redundant WLAN," in Proceedings of 2012 IEEE 17th International Conference on Emerging Technologies & Factory Automation (ETFA 2012), 2012: IEEE, pp. 1-8, doi: 10.1109/ETFA.2012.6489647.
[28] S. S. Gill and R. Buyya, "Failure management for reliable cloud computing: a taxonomy, model, and future directions," Computing in Science & Engineering, vol. 22, no. 3, pp. 52-63, 2018, doi: 10.1109/MCSE.2018.2873866.
[29] M. Atif et al., "Soft computing techniques for dependable cyber-physical systems," IEEE Access, vol. 7, pp. 72030-72049, 2019, doi: 10.1109/ACCESS.2019.2920317.
[30] A. Zamani, M. A. Pourmina, and R. S. Kandovan, "Improving the Mean Time to Failure of the System with the New Architecture of the Main Node with the Replacement Node of Industrial Wireless Sensor Networks for Monitoring and Control using Markov Model," Majlesi Journal of Telecommunication Devices, vol. 11, no. 3, pp. 143-153, 2022, doi: 10.30486/mjtd.2022.695924.