پدافند الکترونیکی و سایبری

پدافند الکترونیکی و سایبری

افزایش طول عمر در شبکه ­های حسگر بی‌سیم با به‌کارگیری روش تاپسیس فازی

نوع مقاله : مقاله پژوهشی

نویسندگان
1 دانشیار، دانشگاه ولی عصر (عج) رفسنجان، رفسنجان، ایران.
2 دانشیار، دانشگاه ولی‌عصر (عج) رفسنجان، رفسنجان، ایران
چکیده
امروزه در زمینه‌های مختلف، شبکه‌های حسگر بی‌سیم کاربردهای گسترده‌ای دارند. وظیفه اصلی گره‌های حسگر در برنامه‌های کاربردی، حس کردن محیط و تغییرات آن، همچنین گزارش حوادث غیرمترقبه در ناحیه هدف و ارسال داده‌های حس­شده به گره چاهک یا ایستگاه پایه است. محدودیت منابع و انرژی گره‌های حسگر و غیرقابل اطمینان بودن پیوند‌های بی‌سیم، و از طرفی، تقاضا‌های عملکرد مختلف در برنامه‌های کاربردی گوناگون، چالش‌هایی را در طراحی یک پروتکل ارتباطی مناسب باقابلیت تعادل بار برای شبکه‌های حسگر بی‌سیم ایجاد می‌نماید. خوشه‌بندی کارآمد می­تواند موجب تعادل بار و افزایش طول عمر در شبکه حسگر بی‌سیم ‌شود. در این مقاله، روشی برای افزایش طول عمر گره‌های شبکه‌های حسگر بی‌سیم و درنتیجه، افزایش طول عمر شبکه، مبتنی بر روش تاپسیس فازی ارائه می‌شود. با لحاظ نمودن پارامتر‌های مؤثر در توازن بار گره­ها، از قبیل انرژی سرخوشه و گره­های خوشه، پایداری خوشه و مسافت انتقال داده، خوشه‌بندی را به نحوی انجام می­دهیم که این توازن بار در شبکه، باعث مصرف متعادل انرژی گره‌ها و افزایش طول عمر شبکه شود. نتایج ارزیابی‌های انجام‌شده، کارآمدی روش پیشنهادی را در مقایسه با روش­های دیگر، در افزایش و متوازن ­سازی طول عمر گره­ ها، نشان می‌دهد.
کلیدواژه‌ها
موضوعات

عنوان مقاله English

Prolonging Lifetime for Wireless Sensor Networks Using TOPSIS-fuzzy Scheme

نویسندگان English

Mohammad Alaei 1
Fahimeh Yazdanpanah 2
1 Associate Professor , Vali-e-Asr University of Rafsanjan, Rafsanjan, Iran.
2 Associate Professor , Vali-e-Asr University of Rafsanjan, Rafsanjan, Iran.
چکیده English

Nowadays, in various fields and applications, wireless sensor networks have wide applications. The main task of sensor nodes in applications is to sense the environment and its changes, as well as report the events in the target area and send the sensed data to the sink or base station. The resource limitation of sensor nodes and the unreliability of low-energy wireless links, and on the other hand, different performance demands in various applications, create challenges in designing a suitable communication protocol with load balancing capability for wireless sensor networks. Efficient clustering can balance load and increase lifetime in wireless sensor networks. In this paper, a method of lifetime prolongation for nodes and thus for wireless sensor networks based on the fuzzy TOPSIS, is proposed. By considering the effective parameters for load balancing, such as the energy of the cluster heads and cluster nodes, cluster stability and data transmission distance, the proposed clustering is carried out in such a way that load balancing causes balanced energy consumption in nodes and increases the network's lifetime. The results of various evaluations show the effectiveness of the proposed method in comparison with other methods in increasing and balancing the lifetime of nodes.

کلیدواژه‌ها English

Wireless sensor networks TOPSIS
fuzzy Load balancing Network Lifetime optimization
[4]    H. Zhou and J. Li, “Sleep Scheduling for Enhancing the Lifetime of Three-Dimensional Heterogeneous Wireless Sensor Networks,” In book: Computer Supported Cooperative Work and Social Computing, pp.365-375, 2023. https://doi.org/ 10.1007/978-981-99-2356-4_29.
[5]    M. Alaei and F. Yazdanpanah, “ZOGLO: A Scheme of Zoning and Data Gathering for Lifetime Optimization in Wireless Sensor Networks,” Journal of Soft Computing and Information Technology (JSCIT), vol. 7, Issue 2, pp. 71-80, 2019. (in Persian)
[6]    A. Seyyedabbasi, G. Dogan, and F. Kiani, “HEEL: A New Clustering Method To Improve Wireless Sensor Network Lifetime,” IET WIRELESS SENSOR SYS, vol. 10, no. 3, pp. 130-136, 2020. https://doi.org/10.1049/ietwss.2019.0153.
[7]    S. Jadhav and S. Jadhav, “KPSO: K-Mean and PSO Based Clustering Algorithm for Wireless Sensor Network,” 6th IEEE International Conference On Computing, Communica-tion, Control and Automation (ICCUBEA), 2020. https://doi.org/10.1109/ICCUBEA54992.2022.10011024.
[8]    A. Joseph, R. Asaletha, V. J. Manoj, and R. Nishanth, “Enhancing the Network Lifetime of a Wireless Sensor Network using Modified K-Means Firefly Optimization,” J PHYS, vol. 2466, no. 012019, 2023. https://doi.org/10.1088/ 1742- 6596/2466/1/012019.
[9]    F. Elfouly, A. Khedr, M. H. Sharif, E. Alreshidi, K. Yadav, H. Kusetogullari, and R. Ramadan, “ERCP: Energy-Efficient and Reliable-Aware Clustering Protocol for Wireless Sensor Networks,” SENSORS,  vol. 22, no. 8950, pp. 1-17, 2022. https://doi.org/10.3390/s22228950.
[10]  M. Alaei and F. Yazdanpanah, “EELCM: An Energy Efficient Load-Based Clustering Method for Wireless Mobile Sensor Networks,” MOBILE NETW APPL, vol. 24, no. 5, pp.1486-1498, 2019. https://doi.org/10.1007/s11036-019-01270 -2.
[11]  B. Sarangi and B. Tripathy, “Outlier Detection Technique for Wireless Sensor Network Using GAN with Autoencoder to Increase the Network Lifetime,” INT J COMP NETW INF SEC, vol. 15, pp. 26-38, 2023. https://doi.org/10.4018/ IJBDCN.286705.
[13]  D. S. Sultana, D. Bordoloi, C. Singh, D. Srivastava, N. Thiyagarajan, and N. Chinthamu, “A Comparative Approach on Enhancing Lifetime of Wireless Sensor Networks,” 5th IEEE International Conference on Contemporary Computing and Informatics, 2023. https://doi.org/10.47750/pnr.2022.13 .S07.189.
[14]  R. Subha and A. Haldorai, “Improved EPOA Clustering Protocol for Lifetime Longevity in Wireless Sensor Network,” SENSORS,  vol. 3. no. 100199, 2022. https://doi.org/10.1016/j.sintl.2022.100199.
[15]  D. Agrawal, S. Pandey, P. Gupta, and M. K. Goyal, “Optimization of Cluster Heads Through Harmony Search Algorithm in Wireless Sensor Networks,” J INTELL FUZZY SYST, vol. 39, no. 6, pp. 8587-8597, 2020, https://doi.org/ 10.3233/ JIFS-189175.
[16]  L. Jawad and A. Idrees, “Integrated Encoding and Scheduling Protocol for Improving the Lifetime in Wireless Sensor Networks,” INT J COMPUT APPL T, vol. 69, no. 334, pp. 334-343, 2022. https://doi.org/ 10.1504/IJCAT. 2022.10054564.
[17]  V. Narayan  and A. K. Daniel, “Energy Efficient Protocol for Lifetime Prediction of Wireless Sensor Network using Multivariate Polynomial Regression Model,” J SCI IND RES INDIA, vol. 81, no. 12, pp. 1297-1309, 2022. https://doi.org /0.56042/jsir.v81i12.54908.
[18]  K. Debasis, L. Sharma, V. Bohat, and R. Bhadoria, “An Energy-Efficient Clustering Algorithm for Maximizing Lifetime of Wireless Sensor Networks using Machine Learning,” MOBILE NETW APPL, vol.28, no.2, pp. 1-15, 2023. https://doi.org/ 10.1007/s11036-023-02109-7.
[19]  S. Phommasan, Widyawan, and I. W. Mustika “Cluster Selection Technique with Fuzzy Logic-Based Wireless Sensor Network to Increase the Lifetime of Networks,” 5th International Conference on Research of Information Technology and Intelligent Systems (ISRITI), 2022. https://doi.org/ 10.1109/ISRITI56927.2022.10052871.
[20]  A. Taha, H. Abouroumia, S. Mohamed, and L. Amar, “Enhancing the Lifetime and Energy Efficiency of Wireless Sensor Networks Using Aquila Optimizer Algorithm,” FUTURE INTERNET, vol. 14. no. 365, pp. 1-17, 2022. https://doi.org/ 10.3390/fi14120365.
[21]  C. D. Tran, N. Tam, N. Quy, and H. Binh, “An Energy-Efficient Scheme for Maximizing Data Aggregation Tree Lifetime in Wireless Sensor Network,” J AMB INTEL HUM COMP, vol. 14, 2023. https://doi.org/s12652-023-04621-w.
[22]  A. J. Yuste-Delgado, J. C. Cuevas-Martinez, and A. Trivino-Cabrera, “A Distributed Clustering Algorithm Guided by the Base Station to Extend the Lifetime of Wireless Sensor Networks,” SENSORS, vol. 20, no. 8, ID: 2312, pp. 1-18, 2020. https://doi.org/10.3390/s20082312.
[23]  A. M. Jubair, R. Hassan, A. Aman, H. Sallehudin, Z. Al-Mekhlafi, B. Mohammed, and M. Alsaffar, “Optimization of Clustering in Wireless Sensor Networks: Techniques and Protocols,” APPL SCI, vol. 11, no. 23, 11448, pp. 1-30, 2021. https://doi.org/10.3390/app112311448.
[24]  M. Mirzasadeghi and H. Bakhshi, “A New Method for Clustering Wireless Sensor Networks to Improve the Energy Consumption,” J COMMUN ENG, vol. 5, no. 2, pp. 136-149, 2016. https://doi.org/10.22070/jce.2017.1614.
[25]  M. Khan, J. Khan, K. Mahmood, I. Bari, H. Ali, N. Jan, and R. Ghoniem, “Algorithm for Increasing Network Lifetime in Wireless Sensor Networks Using Jumping and Mobile Sensor Nodes,” ELECTRONICS, vol. 11, no.2913, pp. 1-15, 2022. https://doi.org/ 10.3390/electronics11182913.
[26]  R. Medeiros, J. M. Villanueva, and E. Macedo, “Lifetime Increase for Wireless Sensor Networks Using Cellular Learning Automata,” WIRELESS PERS COMMUN, vol. 123, pp. 3413–3432, 2022. https://doi.org/10.1007/s11277-021-09295-1.
[27]  R. Marappan, P. Vardhini, G. Kaur, S. Murugesan, M. Kathiravan, N. Bharathiraja, and R. Venkatesan, “Efficient Evolutionary Modeling in Solving Maximization of Lifetime of Wireless Sensor Healthcare Networks,” SOFT COMPUT, vol. 27, Issue. 16, PP. 11853-11867, 2023. https://doi.org/ 10.1007 /s00500-023-08623-w.
[28]  M. Alaei, P. Sabbagh, and F. Yazdanpanah, “A QoS-aware Congestion Control Mechanism for Wireless Multimedia Sensor Networks,” WIREL NETW, vol. 25, no. 3, pp. 4173-4192, 2019. https://doi.org/10.1007/s11276-018-1738-8.
[29]  S. Misra and R. Kumar, “An Analytical Study of LEACH and PEGASIS Protocol in Wireless Sensor Networks,” International Conference on Innovations in information Embedded and Communication Systems (ICIIECS), 2017, https://doi.org/10.1109/ICIIECS.2017.8276118.
[30]  R. Chang and C. Kuo, “An Energy Efficient Routing Mechanism for Wireless Sensor Networks,” 20th International Conference on Advanced Information Networking and Applications (AINA’06), 2006. https://doi. org/10.1109/AINA.2006.86.
[31]  W. B. Heinzelman, A.P. Chandrakasan, and H. Balakrish-nan, “An Application-specific Protocol Architecture for Wireless Microsensor Networks,” IEEE T WIREL COMMUN, vol. 1, Issue 4, 2002. https://doi.org/10.1109/ TWC.2002.804190.
دوره 13، شماره 3 - شماره پیاپی 51
پاییز
پاییز 1404
صفحه 147-161

  • تاریخ دریافت 22 تیر 1404
  • تاریخ بازنگری 23 شهریور 1404
  • تاریخ پذیرش 22 مهر 1404
  • تاریخ انتشار 01 آبان 1404