Systematic literature review: Dvelopment of the leach protocol algorithm for efficient energy consumption in WSN

• Autorzy: Isnomo Yoyok Heru Prasetyo , Muladi Muladi , Elmunsyah Hakkun

Identyfikatory

DOI

10.15199/48.2024.07.31

Warianty tytułu

PL

Systematyczny przegląd literatury: Opracowanie algorytmu protokołu wymywania w celu efektywnego zużycia energii w WSN

• Języki publikacji: EN

Abstrakty

EN

Efficient energy consumption routing protocols in the field of Wireless Sensor Networks (WSN) still receive considerable attention from researchers. One model is the Low Energy Adaptive Clustering Hierarchy (LEACH) which has continued to develop from 2000 until now. The level of energy efficiency is determined by the size of energy consumption. The benefit of increasing energy efficiency is to extend the life of the network. The aim of this research is to present published information about the development of the LEACH protocol in its role in overcoming the problem of limited energy in WSNs, which has an impact on network lifespan. This research uses the Systematic Literature Review (SLR) method, to analyze high quality articles from the last six years (2017 – 2023) taken from six databases, namely IEEEXPLORE, Springer, Elsevier, ScienceDirect, Taylor & Francis, and MDPI. The results of the study show that researchers are very enthusiastic about conducting research in the field of energy consumption in WSNs with the development of the LEACH protocol. The information obtained contained 68% of protocols with Leach's development, 16% of protocols related to Leach, and 16% of protocols not Leach, From the Geographic Space study, it can be seen that there are 11 active countries, with nine countries having quite high activity, India ranks first as the most active country reaching 33%. Based on research methodology, it shows that the experimental method is in the highest position with a total of 37 papers published.

PL

Protokoły routingu efektywnego zużycia energii w dziedzinie bezprzewodowych sieci czujników (WSN) nadal cieszą się dużym zainteresowaniem badaczy. Jednym z modeli jest hierarchia klastrów adaptacyjnych niskoenergetycznych (LEACH), która rozwija się od 2000 r. do chwili obecnej. Poziom efektywności energetycznej zależy od wielkości zużycia energii. Korzyścią ze zwiększenia efektywności energetycznej jest wydłużenie żywotności sieci. Celem badań jest przedstawienie opublikowanych informacji na temat rozwoju protokołu LEACH w jego roli w przezwyciężaniu problemu ograniczonej energii w WSN, który ma wpływ na żywotność sieci. W badaniu wykorzystano metodę Systematic Literature Review (SLR) do analizy wysokiej jakości artykułów z ostatnich sześciu lat (2017 – 2023) pobranych z sześciu baz danych, a mianowicie IEEEXPLORE, Springer, Elsevier, ScienceDirect, Taylor & Francis i MDPI. Wyniki badania pokazują, że badacze z dużym entuzjazmem podchodzą do prowadzenia badań w zakresie zużycia energii w WSN wraz z rozwojem protokołu LEACH. Uzyskane informacje zawierały 68% protokołów z opracowaniem Leacha, 16% protokołów związanych z Leachem i 16% protokołów niezwiązanych z Leachem. Z badania przestrzeni geograficznej wynika, że istnieje 11 aktywnych krajów, przy czym dziewięć krajów ma dość wysokiej aktywności, Indie zajmują pierwsze miejsce wśród najbardziej aktywnych krajów, osiągając 33%. Z metodologii badań wynika, że na najwyższym miejscu znajduje się metoda eksperymentalna, w której opublikowano ogółem 37 prac.

Słowa kluczowe

EN

leach development; SLR; WSN; energy consumption

PL

rozwój ługowania; SLR; WSN; zużycie energii

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2024
• Tom: R. 100, nr 7
• Strony: 148--157
• Opis fizyczny: Bibliogr. 75 poz., rys., tab.

Twórcy

autor

Isnomo Yoyok Heru Prasetyo

• Electrical Engineering, Malang State Polytechnic, Indonesia

• https://orcid.org/0009-0003-6387-0281

autor

Muladi Muladi

• Electrical and informatics Engineering Study Program, Malang State University, Indonesia

• https://orcid.org/0000-0002-2904-5398

autor

Elmunsyah Hakkun

• Electrical and informatics Engineering Study Program, Malang State University, Indonesia

• https://orcid.org/0000-0002-0754-3097

Bibliografia

• [1] A. Ali, Y. K. Jadoon, S. A. Changazi, and M. Qasim, “Military Operations: Wireless Sensor Networks based Applications to Reinforce Future Battlefield Command System,” Proc. - 2020 23rd IEEE Int. Multi-Topic Conf. INMIC 2020, 2020, doi:10.1109/INMIC50486.2020.9318168.
• [2] T. Rajasekaran and S. Anandamurugan, Challenges and Applications of Wireless Sensor Networks in Smart Farming—A Survey, vol. 750. Springer Singapore, 2019. doi: 10.1007/978-981-13-1882-5_30.
• [3] A. A. Rezaee and F. Pasandideh, “A Fuzzy Congestion Control Protocol Based on Active Queue Management in Wireless Sensor Networks with Medical Applications,” Wirel. Pers. Commun., vol. 98, no. 1, pp. 815–842, 2018, doi: 10.1007/s11277-017-4896-6.
• [4] A. Lavric and V. Popa, “Performance evaluation of routing algorithms used in large- scale wsn: A step towards a smart city,” Prz. Elektrotechniczny, vol. 91, no. 8, pp. 96–100, 2015, doi: 10.15199/48.2015.08.24.
• [5] M. Majid et al., “Applications of Wireless Sensor Networks and Internet of Things Frameworks in the Industry Revolution 4.0: A Systematic Literature Review,” Sensors, vol. 22, no. 6, pp. 136, 2022, doi: 10.3390/s22062087.
• [6] M. Elshrkawey, S. M. Elsherif, and M. Elsayed Wahed, “An Enhancement Approach for Reducing the Energy Consumption in Wireless Sensor Networks,” J. King Saud Univ. - Comput. Inf. Sci., vol. 30, no. 2, pp. 259–267, 2018, doi: 10.1016/j.jksuci.2017.04.002.
• [7] E. A. Evangelakos, D. Kandris, D. Rountos, G. Tselikis, and E. Anastasiadis, “Energy Sustainability in Wireless Sensor Networks: An Analytical Survey,” J. Low Power Electron. Appl., vol. 12, no. 4, 2022, doi: 10.3390/jlpea12040065.
• [8] O. Younis and S. Fahmy, “Distributed clustering in ad-hoc sensor networks: A hybrid, energy-efficient approach,” Proc. - IEEE INFOCOM, vol. 1, pp. 629–640, 2004, doi: 10.1109/infcom.2004.1354534.
• [9] R. Gantassi, B. Ben Gouissem, O. Cheikhrouhou, S. El Khediri, and S. Hasnaoui, “Optimizing Quality of Service of Clustering Protocols in Large-Scale Wireless Sensor Networks with Mobile Data Collector and Machine Learning,” Secur. Commun. Networks, vol. 2021, 2021, doi: 10.1155/2021/5531185.
• [10] F. H. El-Fouly, M. Kachout, Y. Alharbi, J. S. Alshudukhi, A. Alanazi, and R. A. Ramadan, “Environment-Aware Energy Efficient and Reliable Routing in Real-Time Multi-Sink Wireless Sensor Networks for Smart Cities Applications,” Appl. Sci., vol. 13, no. 1, 2023, doi: 10.3390/app13010605.
• [11] R. Mahakud et al., “Energy Management in Wireless Sensor Network Using PEGASIS,” Procedia Comput. Sci., vol. 92, pp. 207–212, 2016, doi: 10.1016/j.procs.2016.07.347.
• [12] W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan, “Energy-efficient communication protocol for wireless microsensor networks,” Proc. Annu. Hawaii Int. Conf. Syst. Sci., vol. 2000-Janua, no. c, pp. 1–10, 2000.
• [13] I. Daanoune, B. Abdennaceur, and A. Ballouk, “A comprehensive survey on LEACH-based clustering routing protocols in Wireless Sensor Networks,” Ad Hoc Networks, vol. 114, no. January, p. 102409, 2021, doi: 10.1016/j.adhoc.2020.102409.
• [14] Moorthi and R. Thiagarajan, “Energy consumption and network connectivity based on Novel-LEACH-POS protocol networks,” Comput. Commun., vol. 149, no. June 2019, pp. 90–98, 2020, doi: 10.1016/j.comcom.2019.10.006.
• [15] F. Zhang, Z. Yin, A. Gu, Y. Li, and H. Liu, “Research on simulation of cluster routing protocol for industrial wireless sensor networks,” 2018 IEEE 4th Int. Conf. Comput. Commun. ICCC 2018, pp. 265–269, 2018, doi: 10.1109/CompComm.2018.8780600.
• [16] M. Farsi, M. Badawy, M. Moustafa, H. A. Arafat, and Y. Abdulazeem, “A Congestion-Aware Clustering and Routing (CCR) Protocol for Mitigating Congestion in WSN,” IEEE Access, vol. 7, pp. 105402–105419, 2019, doi: 10.1109/ACCESS.2019.2932951.
• [17] I. Kaushik and N. Sharma, Black Hole Attack and Its Security Measure in Wireless Sensors Networks, vol. 1132. 2020. doi: 10.1007/978-3-030-40305-8_20.
• [18] L. K. Ketshabetswe, A. M. Zungeru, M. Mangwala, J. M. Chuma, and B. Sigweni, “Communication protocols for wireless sensor networks: A survey and comparison,” Heliyon, vol. 5, no. 5, p. e01591, 2019, doi: 10.1016/j.heliyon.2019.e01591.
• [19] Y. Ge, S. Wang, and J. Ma, “Optimization on TEEN routing protocol in cognitive wireless sensor network,” Eurasip J. Wirel. Commun. Netw., vol. 2018, no. 1, 2018, doi: 10.1186/s13638018-1039-z.
• [20] R. P. Mahapatra and R. K. Yadav, “Descendant of LEACH Based Routing Protocols in Wireless Sensor Networks,” Procedia Comput. Sci., vol. 57, pp. 1005–1014, 2015, doi: 10.1016/j.procs.2015.07.505.
• [21] L. Zhao, S. Qu, and Y. Yi, “A modified cluster-head selection algorithm in wireless sensor networks based on LEACH,”Eurasip J. Wirel. Commun. Netw., vol. 2018, no. 1, 2018, doi: 10.1186/s13638-018-1299-7.
• [22] J. Chu and W. Han, “Internet Communication System Protocol Based on Wireless Sensor,” Radioelectron. Commun. Syst., vol. 62, no. 8, pp. 422–429, 2019, doi: 10.3103/S0735272719080065.
• [23] H. Liang, S. Yang, L. Li, and J. Gao, “Research on routing optimization of WSNs based on improved LEACH protocol,” Eurasip J. Wirel. Commun. Netw., vol. 2019, no. 1, 2019, doi: 10.1186/s13638-019-1509-y.
• [24] H. Upadhyay and M. Mehta, “Improved APAC algorithm for minimizing delay in wireless sensor network with mobile sink,” Int. J. Adv. Comput. Res., vol. 7, no. 28, pp. 23–31, 2017, doi: 10.19101/IJACR.2016.627001.
• [25] P. Maratha and K. Gupta, “A comprehensive and systematized review of energy-efficient routing protocols in wireless sensor networks,” Int. J. Comput. Appl., vol. 44, no. 1, pp. 83–100, 2019, doi: 10.1080/1206212X.2019.1697513.
• [26] N. Chauhan and S. Chauhan, “Partly Centralized Partly Distributed Energy Efficient Sleep/Wake Scheduling in Wireless Sensor Networks for Applications Requiring Continuous Sensing,” IETE Tech. Rev. (Institution Electron. Telecommun. Eng. India), vol. 39, no. 4, pp. 940–952, 2022, doi: 10.1080/02564602.2021.1934906.
• [27] M. A. Jamshed, K. Ali, Q. H. Abbasi, M. A. Imran, and M. UrRehman, “Challenges, Applications, and Future of Wireless Sensors in Internet of Things: A Review,” IEEE Sens. J., vol. 22, no. 6, pp. 5482–5494, 2022, doi: 10.1109/JSEN.2022.3148128.
• [28] B. N. Silva, M. Khan, and K. Han, “Internet of Things: A Comprehensive Review of Enabling Technologies, Architecture, and Challenges,” IETE Tech. Rev. (Institution Electron. Telecommun. Eng. India), vol. 35, no. 2, pp. 205–220, 2018, doi: 10.1080/02564602.2016.1276416.
• [29] S. Selvan, M. Zaman, R. Gobbi, and H. Y. Wong, “Recent advances in the design and development of radio frequencybased energy harvester for powering wireless sensors: a review,” J. Electromagn. Waves Appl., vol. 32, no. 16, pp. 2110–2134, 2018, doi: 10.1080/09205071.2018.1497548.
• [30] E. M. Manuel, V. Pankajakshan, and M. T. Mohan, “Efficient Strategies for Signal Aggregation in Low-Power Wireless Sensor Networks With Discrete Transmission Ranges,” IEEE Sensors Lett., vol. 7, no. 3, pp. 5–8, 2023, doi: 10.1109/LSENS.2023.3250432.
• [31] M. E. Al-Sadoon, A. Jedidi, and H. Al-Raweshidy, “Dual-Tier Cluster-Based Routing in Mobile Wireless Sensor Network for IoT Application,” IEEE Access, vol. 11, no. January, pp. 40794094, 2023, doi: 10.1109/ACCESS.2023.3235200.
• [32] B. Pitchaimanickam and G. Murugaboopathi, “A hybrid firefly algorithm with particle swarm optimization for energy efficient optimal cluster head selection in wireless sensor networks,” Neural Comput. Appl., vol. 32, no. 12, pp. 7709–7723, 2020, doi: 10.1007/s00521-019-04441-0.
• [33] S. Jain and N. Agrawal, “Development of Energy Efficient Modified LEACH Protocol for IoT Applications,” Proc. - 2020 12th Int. Conf. Comput. Intell. Commun. Networks, CICN 2020, pp. 160–164, 2020, doi: 10.1109/CICN49253.2020.9242619.
• [34] A. S. Al-Zubaidi, A. A. Ariffin, and A. K. Al-Qadhi, “Enhancing the stability of the improved-leach routing protocol for wsns,” J. ICT Res. Appl., vol. 12, no. 1, pp. 1–13, 2018, doi: 10.5614/itbj.ict.res.appl.2018.12.1.1.
• [35] S. Arjunan, S. Pothula, and D. Ponnurangam, “F5N-based unequal clustering protocol (F5NUCP) for wireless sensor networks,” Int. J. Commun. Syst., vol. 31, no. 17, pp. 1–14, 2018, doi: 10.1002/dac.3811.
• [36] Y. Chen, C. Shen, K. Zhang, H. Wang, and Q. Gao, “LEACH Algorithm based on energy consumption equilibrium,” Proc. - 3rd Int. Conf. Intell. Transp. Big Data Smart City, ICITBS 2018, vol. 2018-Janua, pp. 677–680, 2018, doi: 10.1109/ICITBS.2018.00176.
• [37] R. Gantassi, Z. Masood, and Y. Choi, “Enhancing QoS and Residual Energy by Using of Grid-Size Clustering, K-Means, and TSP Algorithms With MDC in LEACH Protocol,” IEEE Access, vol. 10, pp. 58199–58211, 2022, doi: 10.1109/ACCESS.2022.3178434.
• [38] M. Gamal, N. E. Mekky, H. H. Soliman, and N. A. Hikal, “Enhancing the Lifetime of Wireless Sensor Networks Using Fuzzy Logic LEACH Technique-Based Particle Swarm Optimization,” IEEE Access, vol. 10, pp. 36935–36948, 2022, doi: 10.1109/ACCESS.2022.3163254.
• [39] S. El Khediri, W. Fakhet, T. Moulahi, R. Khan, A. Thaljaoui, and A. Kachouri, “Improved node localization using K-means clustering for Wireless Sensor Networks,” Comput. Sci. Rev., vol. 37, p. 100284, 2020, doi: 10.1016/j.cosrev.2020.100284.
• [40] A. M. Pasikhani, J. A. Clark, P. Gope, and A. Alshahrani, “Intrusion Detection Systems in RPL-Based 6LoWPAN: A Systematic Literature Review,” IEEE Sens. J., vol. 21, no. 11, pp. 12940–12968, 2021, doi: 10.1109/JSEN.2021.3068240.
• [41] J. Liu, M. Nogueira, J. Fernandes, and B. Kantarci, “Adversarial Machine Learning: A Multilayer Review of the State-of-the-Art and Challenges for Wireless and Mobile Systems,” IEEE Commun. Surv. Tutorials, vol. 24, no. 1, pp. 123–159, 2022, doi: 10.1109/COMST.2021.3136132.
• [42] S. K. Singh and P. Kumar, “A comprehensive survey on trajectory schemes for data collection using mobile elements in WSNs,” J. Ambient Intell. Humaniz. Comput., vol. 11, no. 1, pp. 291–312, 2020, doi: 10.1007/s12652-019-01268-4.
• [43] S. M. Chowdhury and A. Hossain, “Different Energy Saving Schemes in Wireless Sensor Networks: A Survey,” Wirel. Pers. Commun., vol. 114, no. 3, pp. 2043–2062, 2020, doi: 10.1007/s11277-020-07461-5.
• [44] T. R. Beegum, M. Y. I. Idris, M. N. Bin Ayub, and H. A. Shehadeh, “Optimized Routing of UAVs Using Bio-Inspired Algorithm in FANET: A Systematic Review,” IEEE Access, vol. 11, no. February, pp. 15588–15622, 2023, doi: 10.1109/ACCESS.2023.3244067.
• [45] V. Vimal et al., “Clustering Isolated Nodes to Enhance Network’s Life Time of WSNs for IoT Applications,” IEEE Syst. J., vol. 15, no. 4, pp. 5654–5663, 2021, doi: 10.1109/JSYST.2021.3103696.
• [46] B. Zeng, C. Zhao, Y. Zhang, J. Sun, and X. Gao, “A SectorBased Energy-Efficient Lightweight Clustering Algorithm,” IEEE Access, vol. 10, no. September, pp. 108285–108295, 2022, doi: 10.1109/ACCESS.2022.3213826.
• [47] A. Elsayed and M. Sharaf, “MA-LEACH: Energy Efficient Routing Protocol for WSNs using Particle Swarm Optimization and Mobile Aggregator,” Int. J. Comput. Networks Appl., vol. 5, no. 1, p. 1, 2018, doi: 10.22247/ijcna/2018/49344.
• [48] A. Pietrabissa and F. Liberati, “Dynamic distributed clustering in wireless sensor networks via Voronoi tessellation control,” Int. J. Control, vol. 92, no. 5, pp. 1001–1014, 2019, doi: 10.1080/00207179.2017.1378441.
• [49] A. Verma, S. Kumar, P. R. Gautam, T. Rashid, and A. Kumar, “Fuzzy Logic Based Effective Clustering of Homogeneous Wireless Sensor Networks for Mobile Sink,” IEEE Sens. J., vol. 20, no. 10, pp. 5615–5623, 2020, doi: 10.1109/JSEN.2020.2969697.
• [50] S. Phoemphon, C. So-In, P. Aimtongkham, and T. G. Nguyen, “An energy-efficient fuzzy-based scheme for unequal multihop clustering in wireless sensor networks,” J. Ambient Intell. Humaniz. Comput., vol. 12, no. 1, pp. 873–895, 2021, doi: 10.1007/s12652-020-02090-z.
• [51] R. Vinodha, S. Durairaj, and S. Padmavathi, “Energy-efficient routing protocol and optimized passive clustering in WSN for SMART grid applications,” Int. J. Commun. Syst., vol. 35, no. 1, pp. 1–18, 2022, doi: 10.1002/dac.5019.
• [52] Y. Di Yao et al., “Multihop Clustering Routing Protocol Based on Improved Coronavirus Herd Immunity Optimizer and QLearning in WSNs,” IEEE Sens. J., vol. 23, no. 2, pp. 16451659, 2023, doi: 10.1109/JSEN.2022.3225956.
• [53] M. J. Page et al., “The PRISMA 2020 statement: an updated guideline for reporting systematic reviews,” Syst. Rev., vol. 10, no. 1, pp. 1–11, 2021, doi: 10.1186/s13643-021-01626-4.
• [54] A. S. Ghiduk, M. R. Girgis, and M. H. Shehata, “Higher order mutation testing: A Systematic Literature Review,” Comput. Sci. Rev., vol. 25, pp. 29–48, 2017, doi: 10.1016/j.cosrev.2017.06.001.
• [55] B. A. Kitchenham and S. Charters, “Guidelines for performing Systematic Literature Reviews in Software Engineering (Software Engineering Group, Department of Computer Science, Keele …,” Tech. Rep. EBSE 2007- 001. Keele Univ. Durham Univ. Jt. Rep., no. January, 2007.
• [56] W. W. Wang et al., “Introduction to COSMOS-E: Guidance on conducting systematic reviews and Meta-analyses on etiology of observational studies,” Zhonghua Liu Xin10.3760/cma.j.cn112338-20191024-00758.
• [57] G. Lame, “Systematic literature reviews: An introduction,” Proc. Int. Conf. Eng. Des. ICED, vol. 2019-Augus, no. August, pp. 1633–1642, 2019, doi: 10.1017/dsi.2019.169.
• [58] J. Pérez, J. Díaz, J. Garcia-Martin, and B. Tabuenca, “Systematic literature reviews in software engineering-enhancement of the study selection process using Cohen’s Kappa statistic,” J. Syst. Softw., vol. 168, p. 110657, 2020, doi: 10.1016/j.jss.2020.110657.
• [59] T. M. Behera, S. K. Mohapatra, U. C. Samal, M. S. Khan, M. Daneshmand, and A. H. Gandomi, “I-SEP: An Improved Routing Protocol for Heterogeneous WSN for IoT-Based Environmental Monitoring,” IEEE Internet Things J., vol. 7, no. 1, pp. 710–717, 2020, doi: 10.1109/JIOT.2019.2940988.
• [60] S. Kumar, O. Kaiwartya, M. Rathee, N. Kumar, and J. Lloret, “Toward Energy-Oriented Optimization for Green Communication in Sensor Enabled IoT Environments,” IEEE Syst. J., vol. 14, no. 4, pp. 4663–4673, 2020, doi: 10.1109/JSYST.2020.2975823.
• [61] J. Gu, H. Wang, G. Ding, Y. Xu, Z. Xue, and H. Zhou, “Energyconstrained completion time minimization in UAV-enabled internet of things,” IEEE Internet Things J., vol. 7, no. 6, pp. 5491–5503, 2020, doi: 10.1109/JIOT.2020.2981092.
• [62] Y. Xiong, G. Chen, M. Lu, X. Wan, M. Wu, and J. She, “A TwoPhase Lifetime-Enhancing Method for Hybrid EnergyHarvesting Wireless Sensor Network,” IEEE Sens. J., vol. 20, no. 4, pp. 1934–1946, 2020, doi: 10.1109/JSEN.2019.2948620.
• [63] T. Stephan, K. Sharma, A. Shankar, S. Punitha, V. Varadarajan, and P. Liu, “Fuzzy-Logic-Inspired Zone-Based Clustering Algorithm for Wireless Sensor Networks,” Int. J. Fuzzy Syst., vol. 23, no. 2, pp. 506–517, 2021, doi: 10.1007/s40815-020-00929-3.
• [64] F. Bouakkaz and M. Derdour, “Maximizing WSN Life Using Power Efficient Grid-Chain Routing Protocol (PEGCP),” Wirel. Pers. Commun., vol. 117, no. 2, pp. 1007–1023, 2021, doi: 10.1007/s11277-020-07908-9.
• [65] V. Rajaram and N. Kumaratharan, “Multi-hop optimized routing algorithm and load balanced fuzzy clustering in wireless sensor networks,” J. Ambient Intell. Humaniz. Comput., vol. 12, no. 3, pp. 4281–4289, 2021, doi: 10.1007/s12652-020-01827-0.
• [66] N. M. Shagari, M. Y. I. Idris, R. Bin Salleh, I. Ahmedy, G. Murtaza, and A. Q. B. M. Sabri, “A hybridization strategy using equal and unequal clustering schemes to mitigate idle listening for lifetime maximization of wireless sensor network,” Wirel. Networks, vol. 27, no. 4, pp. 2641–2670, 2021, doi: 10.1007/s11276-021-02608-z.
• [67] N. Moussa and A. El Belrhiti El Alaoui, “An energy-efficient cluster-based routing protocol using unequal clustering and improved ACO techniques for WSNs,” Peer-to-Peer Netw. Appl., vol. 14, no. 3, pp. 1334–1347, 2021, doi: 10.1007/s12083-020-01056-4.
• [68] P. C. S. Rao, P. Lalwani, H. Banka, and G. S. N. Rao, “Competitive swarm optimization based unequal clustering and routing algorithms (CSO-UCRA) for wireless sensor networks,” Multimed. Tools Appl., vol. 80, no. 17, pp. 26093–26119, 2021, doi: 10.1007/s11042-021-10901-4.
• [69] P. S. Mehra, “E-FUCA: enhancement in fuzzy unequal clustering and routing for sustainable wireless sensor network,” Complex Intell. Syst., vol. 8, no. 1, pp. 393–412, 2022, doi: 10.1007/s40747-021-00392-z.
• [70] X. Liu, J. Yu, W. Zhang, and H. Tian, “Low-energy dynamic clustering scheme for multi-layer wireless sensor networks,” Comput. Electr. Eng., vol. 91, no. March, p. 107093, 2021, doi: 10.1016/j.compeleceng.2021.107093.
• [71] N. Ma, H. Zhang, H. Hu, and Y. Qin, “ESCVAD: An EnergySaving Routing Protocol Based on Voronoi Adaptive Clustering for Wireless Sensor Networks,” IEEE Internet Things J., vol. 9, no. 11, pp. 9071–9085, 2022, doi: 10.1109/JIOT.2021.3120744.
• [72] Z. A. Khan, S. Amjad, F. Ahmed, A. M. Almasoud, M. Imran, and N. Javaid, “A Blockchain-Based Deep-Learning-Driven Architecture for Quality Routing in Wireless Sensor Networks,” IEEE Access, vol. 11, no. February, pp. 31036–31051, 2023, doi: 10.1109/ACCESS.2023.3259982.
• [73] I. Raziah, Y. Yunida, Y. Away, R. Muharar, and N. Nasaruddin, “A New Adaptive Power Control Based on LEACH Clustering Protocol for Interference Management in Cooperative D2D Systems,” IEEE Access, vol. 10, no. November, pp. 113513-113522, 2022, doi: 10.1109/ACCESS.2022.3217219.
• [74] S. A. Chafi, H. Abbad, M. K. Benhaoua, and A. El Hassan Benyamina, “Improvement of LEACH Protocol: W-LEACH Approach,” Int. Conf. Smart Comput. Appl. ICSCA 2023, 2023, doi: 10.1109/ICSCA57840.2023.10087572.
• [75] C. H. Lin and M. J. Tsai, “A comment on ‘HEED: A Hybrid, Energy-Efficient, Distributed clustering approach for ad hoc sensor networks,’” IEEE Trans. Mob. Comput., vol. 5, no. 10, pp. 1471–1472, 2006, doi: 10.1109/TMC.2006.141.

Uwagi

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