
(2) Reem Falah Hassan

(3) Sarah O. Al-Tahir

(4) Noorulden Basil

(5) Alfian Ma'arif

(6) * Hamzah M. Marhoon

*corresponding author
AbstractThis research provides a thorough analysis of the algorithms used in the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol for Wireless Sensor Networks (WSNs) to apply Fuzzy Logic, Adaptive Neuro-Fuzzy Inference System (ANFIS), and Harris Hawks Optimisation-Particle Swarm Optimisation (HHOPSO). The primary aim of this paper is to compare and measure these methods by how they save energy, prolong the network’s lifetime and choose the best cluster heads. We look at major indicators such as First Node Death (FND) and the number of rounds when 80% and 50% of nodes are still working, by testing 100 simulated network nodes. The HHOPSO is shown to do a better job at keeping node batteries alive and, at length the network in operation than both Fuzzy Logic and ANFIS. Moreover, ANFIS is more effective than Fuzzy Logic, because it can learn better from data. It is found that HHOPSO helps LEACH become more efficient and effective, contributing new information about how to manage energy and network performance in Wireless Sensor Networks. The document shows the effectiveness of advanced algorithms in keeping sensor networks running longer and offers ideas on how to evaluate them in various network settings.
KeywordsWSNs; LEACH Protocol; Fuzzy Logic Controller; ANFIS; HHOPSO
|
DOIhttps://doi.org/10.31763/ijrcs.v5i3.1918 |
Article metrics10.31763/ijrcs.v5i3.1918 Abstract views : 59 | PDF views : 21 |
Cite |
Full Text![]() |
References
[1] R. Jia and H. Zhang, “Wireless Sensor Network (WSN) Model Targeting Energy Efficient Wireless Sensor Networks Node Coverage,” IEEE Access, vol. 12, pp. 27596-27610, 2024, https://doi.org/10.1109/ACCESS.2024.3365511.
[2] V. K, L. M, S. V. Swamy, S. K, N. N and A. S, “Enhancing Wireless Sensor Network Routing Strategies with Machine Learning Protocols,” 2024 2nd International Conference on Networking and Communications (ICNWC), pp. 1-7, 2024, https://doi.org/10.1109/ICNWC60771.2024.10537481.
[3] Bagwari et al., “An Enhanced Energy Optimization Model for Industrial Wireless Sensor Networks Using Machine Learning,” IEEE Access, vol. 11, pp. 96343-96362, 2023, https://doi.org/10.1109/ACCESS.2023.3311854.
[4] K. Guleria and A. K. Verma, “Comprehensive Review for energy efficient hierarchical routing protocols on wireless sensor networks,” Wireless Networks, vol. 25, no. 3, pp. 1159-1183, 2018, https://doi.org/10.1007/s11276-018-1696-1.
[5] M. F. Alomari, M. A. Mahmoud, and R. Ramli, “A systematic review on the energy efficiency of dynamic clustering in a heterogeneous environment of wireless sensor networks (WSNs),” Electronics, vol. 11, no. 18, p. 2837, 2022, https://doi.org/10.3390/electronics11182837.
[6] D. Srinivasan, A. Kiran, S. Parameswari, and J. Vellaichamy, “Energy efficient hierarchical clustering based dynamic data fusion algorithm for wireless sensor networks in Smart Agriculture,” Scientific Reports, vol. 15, no. 1, p. 7207, 2025, https://doi.org/10.1038/s41598-024-85076-7.
[7] M. H. Anisi, A. H. Abdullah, S. A. Razak, M. A. Ngadi, “Overview of data routing approaches for Wireless Sensor Networks,” Sensors, vol. 12, no. 4, pp. 3964-3996, 2012, https://doi.org/10.3390/s120403964.
[8] M. Elhoseny and A. E. Hassanien, “Hierarchical and clustering WSN models: Their requirements for complex applications,” Studies in Systems, Decision and Control, pp. 53-71, 2018, https://doi.org/10.1007/978-3-319-92807-4_3.
[9] L. Chan, K. Gomez Chavez, H. Rudolph, and A. Hourani, “Hierarchical Routing Protocols for wireless sensor network: A compressive survey,” Wireless Networks, vol. 26, no. 5, pp. 3291-3314, 2020, https://doi.org/10.1007/s11276-020-02260-z.
[10] G. Siamantas, D. Rountos, and D. Kandris, “Energy saving in wireless sensor networks via leach-based, energy-efficient routing protocols,” Journal of Low Power Electronics and Applications, vol. 15, no. 2, p. 19, 2025, https://doi.org/10.3390/jlpea15020019.
[11] D. Tignola, S. D. Vito, G. Fattoruso, F. D’Aversa, and G. D. Francia, “A Wireless Sensor Network Architecture for Structural Health Monitoring,” Lecture Notes in Electrical Engineering, pp. 397-400, 2013, https://doi.org/10.1007/978-3-319-00684-0_76.
[12] U. Ntabeni, B. Basutli, H. Alves, and J. Chuma, “Improvement of the low-energy adaptive clustering hierarchy protocol in wireless sensor networks using mean field games,” Sensors, vol. 24, no. 21, p. 6952, 2024, https://doi.org/10.3390/s24216952.
[13] A. F. Mohammed, H. M. Marhoon, N. Basil, and A. Ma’arif, “A new hybrid intelligent fractional order proportional double derivative + integral (FOPDD+I) controller with ANFIS simulated on automatic voltage regulator system,” International Journal of Robotics and Control Systems, vol. 4, no. 2, pp. 463-479, 2024, https://doi.org/10.31763/ijrcs.v4i2.1336.
[14] H. M. Marhoon, N. Basil, and A. F. Mohammed, “Medical defense nanorobots (MDNRs): A new evaluation and selection of controller criteria for improved disease diagnosis and patient safety using narma(l2)-fop + d(anfis)µ – i?-based Archimedes optimization algorithm,” International Journal of Information Technology, 2024, https://doi.org/10.1007/s41870-023-01724-7.
[15] N. Basil, H. M. Marhoon, and A. F. Mohammed, “Evaluation of a 3-DOF helicopter dynamic control model using FOPID controller-based three optimization algorithms,” International Journal of Information Technology, 2024, https://doi.org/10.1007/s41870-024-02373-0.
[16] N. Basil, B. M. Sabbar, H. M. Marhoon, A. F. Mohammed, and A. Ma’arif, “Systematic review of Unmanned Aerial Vehicles Control: Challenges, solutions, and meta-heuristic optimization,” International Journal of Robotics and Control Systems, vol. 4, no. 4, pp. 1794-1818, 2024, https://doi.org/10.31763/ijrcs.v4i4.1596.
[17] N. Basil, H. M. Marhoon, M. R. Hayal, E. E. Elsayed, I. Nurhidayat, and M. A. Shah, “Black-hole optimisation algorithm with FOPID-based automation intelligence photovoltaic system for voltage and power issues,” Australian Journal of Electrical and Electronics Engineering, vol. 21, no. 2, pp. 115-127, 2024, https://doi.org/10.1080/1448837X.2024.2308415.
[18] N. Basil and H. M. Marhoon, “Towards evaluation of the PID criteria based uavs observation and tracking head within resizable selection by Coa Algorithm,” Results in Control and Optimization, vol. 12, p. 100279, 2023, https://doi.org/10.1016/j.rico.2023.100279.
[19] N. Basil et al., “Performance analysis of hybrid optimization approach for UAV path planning control using FOPID-TID controller and HAOAROA algorithm,” Scientific Reports, vol. 15, p. 4840, 2025, https://doi.org/10.1038/s41598-025-86803-4.
[20] A. Hadir, Y. Regragui and N. M. Garcia, “Accurate Range-Free Localization Algorithms Based on PSO for Wireless Sensor Networks,” IEEE Access, vol. 9, pp. 149906-149924, 2021, https://doi.org/10.1109/ACCESS.2021.3123360.
[21] N. Basil and H. M. Marhoon, “Correction to: Selection and evaluation of FOPID criteria for the X-15 Adaptive Flight Control System (AFCS) via Lyapunov candidates: Optimizing trade-offs and critical values using optimization algorithms,” e-Prime - Advances in Electrical Engineering, Electronics and Energy, vol. 8, p. 100589, 2024, https://doi.org/10.1016/j.prime.2024.100589.
[22] H. Q. A. Abdulrab et al., “Optimal Coverage and Connectivity in Industrial Wireless Mesh Networks Based on Harris’ Hawk Optimization Algorithm,” IEEE Access, vol. 10, pp. 51048-51061, 2022, https://doi.org/10.1109/ACCESS.2022.3173316.
[23] H. M. Marhoon, N. Basil, and A. Ma’arif, “Exploring blockchain data analysis and its communications architecture: Achievements, challenges, and Future Directions: A review article,” International Journal of Robotics and Control Systems, vol. 3, no. 3, pp. 609-626, 2023, https://doi.org/10.31763/ijrcs.v3i3.1100.
[24] N. B. Mohamadwasel and A. Ma’arif, “NB Theory with Bargaining Problem: A New Theory,” International Journal of Robotics and Control Systems, vol. 2, no. 3, pp. 606-609, 2022, https://doi.org/10.31763/ijrcs.v2i3.798.
[25] S. Singh, D. Garg, Manju, and A. Malik, “A novel cluster head selection algorithm based IOT enabled heterogeneous wsns distributed architecture for Smart City,” Microprocessors and Microsystems, vol. 101, p. 104892, 2023, https://doi.org/10.1016/j.micpro.2023.104892.
[26] N. B. Mohamadwasel and S. Kurnaz, “Implementation of the parallel robot using FOPID with fuzzy type-2 in use social spider optimization algorithm,” Applied Nanoscience, vol. 13, no. 2, pp. 1389-1399, 2023, https://doi.org/10.1007/s13204-021-02034-9.
[27] S. Rahman et al., “An Optimal Delay Tolerant and Improved Data Collection Schema Using AUVs for Underwater Wireless Sensor Networks,” IEEE Access, vol. 12, pp. 30146-30163, 2024, https://doi.org/10.1109/ACCESS.2024.3366651.
[28] N. Basil, H. M. Marhoon, and A. R. Ibrahim, “A new thrust vector-controlled rocket based on JOA using MCDA,” Measurement: Sensors, vol. 26, p. 100672, 2023, https://doi.org/10.1016/j.measen.2023.100672.
[29] T. Sarkar, R. Kumar, M. S. Kumar, S. Aggarwal, A. Sandhya, and A. M. Shukla, “Review Paper of Performance Analysis in Wireless Sensor Networks,” Proceedings of the KILBY 100 7th International Conference on Computing Sciences 2023 (ICCS 2023), 2024, https://dx.doi.org/10.2139/ssrn.4485301.
[30] M. S. Islam and M. K. C. Tilak, “Sustainable IOT networks: Designing energy-efficient protocols for smart cities and industries,” Journal of Computer Science and Technology Studies, vol. 7, no. 2, pp. 395-404, 2025, https://doi.org/10.32996/jcsts.2025.7.2.41.
[31] P. Banerjee et al., “A study on the performance of various predictive models based on artificial neural network for backward metal flow forming process,” International Journal on Interactive Design and Manufacturing (IJIDeM), vol. 18, no. 3, pp. 1141-1150, 2022, https://doi.org/10.1007/s12008-022-01079-6.
[32] V. Prakash, D. Singh, S. Pandey, S. Singh, and P. K. Singh, “Energy-optimization route and cluster head selection using M-PSO and GA in wireless sensor networks,” Wireless Personal Communications, 2024, https://doi.org/10.1007/s11277-024-11096-1.
[33] A. F. Mohammed et al., “Selection and Evaluation of Robotic Arm based Conveyor Belts (RACBs) Motions: NARMA (L2)-FO (ANFIS) PD-I based Jaya Optimization Algorithm,” International Journal of Robotics and Control Systems, vol. 4, no. 1, pp. 262-290, 2024, https://doi.org/10.31763/ijrcs.v4i1.1243.
[34] J. F. Lima, A. Patiño-León, M. Orellana, and J. L. Zambrano-Martinez, “Evaluating the impact of membership functions and Defuzzification methods in a fuzzy system: Case of air quality levels,” Applied Sciences, vol. 15, no. 4, p. 1934, 2025, https://doi.org/10.3390/app15041934.
[35] D. Karaboga and E. Kaya, “Adaptive network based Fuzzy Inference System (ANFIS) training approaches: A comprehensive survey,” Artificial Intelligence Review, vol. 52, no. 4, pp. 2263-2293, 2018, https://doi.org/10.1007/s10462-017-9610-2.
[36] N. Walia, H. Singh, and A. Sharma, “ANFIS: Adaptive Neuro-Fuzzy Inference system- A survey,” International Journal of Computer Applications, vol. 123, no. 13, pp. 32-38, 2015, https://doi.org/10.5120/ijca2015905635.
[37] P. P. I. Vazhuthi, A. Prasanth, S. P. Manikandan, and K. K. Sowndarya, “A hybrid ANFIS reptile optimization algorithm for energy-efficient inter-cluster routing in internet of things-enabled Wireless Sensor Networks,” Peer-to-Peer Networking and Applications, vol. 16, no. 2, pp. 1049-1068, 2023, https://doi.org/10.1007/s12083-023-01458-0.
[38] A. Malik, Y. Tikhamarine, S. S. Sammen, S. I. Abba, and S. Shahid, “Prediction of meteorological drought by using hybrid support vector regression optimized with HHO versus PSO algorithms,” Environmental Science and Pollution Research, vol. 28, no. 29, pp. 39139-39158, 2021, https://doi.org/10.1007/s11356-021-13445-0.
[39] A. A. Kadhim and S. A. Rafea, “Improved routing protocols based on RPL for full IoT-WSN Stack,” Iraqi Journal of Information and Communications Technology, vol. 1, no. 1, pp. 58-69, 2021, https://doi.org/10.31987/ijict.1.1.172.
[40] A. K. Yas and A. A. Qassab, “Oil and gas pipelines monitoring using IoT platform,” Iraqi Journal of Information and Communication Technology, vol. 6, no. 1, pp. 9-27, 2024, https://doi.org/10.31987/ijict.6.1.209.
[41] N. Basil and H. M. Marhoon, “Selection and evaluation of FOPID criteria for the X-15 adaptive flight control system (AFCS) via Lyapunov candidates: Optimizing trade-offs and critical values using optimization algorithms,” e-Prime - Advances in Electrical Engineering, Electronics and Energy, vol. 6, p. 100305, 2023, https://doi.org/10.1016/j.prime.2023.100305.
[42] N. Basil, M. E. Alqaysi, M. Deveci, A. S. Albahri, O. S. Albahri, and A. H. Alamoodi, “Evaluation of autonomous underwater vehicle motion trajectory optimization algorithms,” Knowledge-Based Systems, p. 110722, 2023, https://doi.org/10.1016/j.knosys.2023.110722.
[43] F. S. Raheem and N. Basil, “Automation intelligence photovoltaic system for power and voltage issues based on Black Hole Optimization algorithm with FOPID,” Measurement: Sensors, vol. 25, p. 100640, 2023, https://doi.org/10.1016/j.measen.2022.100640.
[44] N. Basil, H. M. Marhoon, S. Gokulakrishnan, and D. Buddhi, “Jaya optimization algorithm implemented on a new novel design of 6-DOF AUV body: a case study,” Multimedia Tools and Applications, pp. 1-26, 2022, https://doi.org/10.21203/rs.3.rs-1075174/v1.
[45] H. M. Marhoon, A. R. Ibrahim, and N. Basil, “Enhancement of Electro Hydraulic Position Servo Control System Utilising Ant Lion Optimiser,” International Journal of Nonlinear Analysis and Applications, vol. 12, no. 2, pp. 2453-2461, 2021, http://dx.doi.org/10.22075/ijnaa.2021.5387.
[46] A. R. Ibrahim, N. Basil, and M. I. Mahdi, “Implementation enhancement of AVR control system within optimization techniques,” International Journal of Nonlinear Analysis and Applications, vol. 12, no. 2, pp. 2021-2027, 2021, https://doi.org/10.22075/ijnaa.2021.5339.
[47] N. B. Mohamadwasel, “Rider Optimization Algorithm implemented on the AVR control system using MATLAB with FOPID,” IOP Conference Series: Materials Science and Engineering, vol. 928, no. 3, p. 032017, 2020, https://doi.org/10.1088/1757-899X/928/3/032017.
[48] Y. R. Mohammed, N. Basil, O. Bayat, and A. Hamid, “A New Novel Optimization Techniques Implemented on the AVR Control System using MATLAB-SIMULINK,” International Journal of Advanced Science and Technology, vol. 29, no. 5, pp. 4515-4521, 2020, https://www.researchgate.net/publication/341216081_A_New_Novel_Optimization_Techniques_Implemented_on_the_AVR_Control_System_using_MATLAB-SIMULINK.
[49] H. M. Marhoon, A. I. Alanssari, and N. Basil, “Design and Implementation of an Intelligent Safety and Security System for Vehicles Based on GSM Communication and IoT Network for Real-Time Tracking,” Journal of Robotics and Control, vol. 4, no. 5, pp. 708-718, 2023, https://doi.org/10.18196/jrc.v4i5.19652.
[50] N. Basil et al., “Multi-criteria decision model for multicircular flight control of unmanned aerial vehicles through a hybrid approach,” Scientific Reports, vol. 15, p. 18962, 2025, https://doi.org/10.1038/s41598-025-01508-y.
[51] P. Chotikunnan et al., “Comparative Analysis of Sensor Fusion for Angle Estimation Using Kalman and Complementary Filters,” International Journal of Robotics and Control Systems, vol. 5, no. 1, pp. 1-21, 2025, https://doi.org/10.31763/ijrcs.v5i1.1674.
[52] A. M. Hussein et al., “A Hybrid PSO-GCRA Framework for Optimizing Control Systems Performance,” International Journal of Robotics and Control Systems, vol. 5, no. 1, pp. 459-478, 2025, https://doi.org/10.31763/ijrcs.v5i1.1738.
[53] B. Singh, O. A. Shah, and S. Arora, “Seasonal Electrical Load Forecasting Using Machine Learning Techniques and Meteorological Variables,” International Journal of Robotics & Control Systems, vol. 4, no. 3, pp. 1092-1108, 2024, https://doi.org/10.31763/ijrcs.v4i3.1446.
[54] I. G. S. M. Diyasa et al., “Enhanced Human Hitting Movement Recognition Using Motion History Image and Approximated Ellipse Techniques,” International Journal of Robotics and Control Systems, vol. 5, no. 1, pp. 222-239, 2025, https://doi.org/10.31763/ijrcs.v5i1.1599.
[55] A. Dahmani et al., “Parametric Analysis of Climate Factors for Monthly Weather Prediction in Ghardaïa District Using Machine Learning-Based Approach: ANN-MLPs,” International Journal of Robotics and Control Systems, vol. 5, no. 1, pp. 179-196, 2025, https://doi.org/10.31763/ijrcs.v5i1.1651.
[56] Y. Maamar et al., “Design, Modeling, and Simulation of a New Adaptive Backstepping Controller for Permanent Magnet Linear Synchronous Motor: A Comparative Analysis,” International Journal of Robotics and Control Systems, vol. 5, no. 1, pp. 296-310, 2025, https://doi.org/10.31763/ijrcs.v5i1.1425.
[57] R. W. Shiddiq, N. Karna, and I. D. Irawati, “Optimizing Machine Learning-Based Network Intrusion Detection System with Oversampling, Feature Selection and Extraction,” Jurnal Ilmiah Teknik Elektro Komputer dan Informatika, vol. 11, no. 2, pp. 225-237, 2025, https://doi.org/10.26555/jiteki.v11i2.30675.
[58] S. Tahcfulloh, D. Maulianawati, and D. Wiharyanto, “Optimizing 2.4GHz Wireless Networks in Shrimp Ponds with Particle Swarm Optimization,” Jurnal Ilmiah Teknik Elektro Komputer dan Informatika, vol. 10, no. 4, pp. 817-832, 2024, https://doi.org/10.26555/jiteki.v10i4.30236.
[59] A. Sahrab and H. M. Marhoon, “Design and fabrication of a low-cost system for smart home applications,” Journal of Robotics and Control (JRC), vol. 3, no. 4, pp. 409-414, 2022, https://doi.org/10.18196/jrc.v3i4.15413.
[60] H. Setiawan, A. Ma'arif, H. M. Marhoon, A. N. Sharkawy, and A. Çakan, “Distance Estimation on Ultrasonic Sensor Using Kalman Filter,” Buletin Ilmiah Sarjana Teknik Elektro, vol. 5, no. 2, pp. 210-217, 2023, https://doi.org/10.12928/biste.v5i2.8089.
[61] N.-L. Tao, D.-H. Pham, M.-K. Pham, and T.-V.-A. Nguyen, “Optimization of hierarchical sliding mode control parameters for a two-wheeled balancing mobile robot using the firefly algorithm,” Journal of Robotics and Control (JRC), vol. 6, no. 1, pp. 76-88, 2025, https://doi.org/10.18196/jrc.v6i1.24192.
[62] M. R. Sagita, A. Ma’arif, F. Furizal, C. Rekik, W. Caesarendra, and R. Majdoubi, “Motion System of a Four-Wheeled Robot Using a PID Controller Based on MPU and Rotary Encoder Sensors,” Control Systems and Optimization Letters, vol. 2, no. 2, pp. 257-265, 2024, https://doi.org/10.59247/csol.v2i2.150.
[63] J. Zhang and J. Zhang, “Classical Dance-Metaheuristic: A Metaheuristic Optimization Algorithm Inspired by Classical Dance,” Control Systems and Optimization Letters, vol. 3, no. 2, pp. 165-173, 2025, https://doi.org/10.59247/csol.v3i2.206.
[64] S. A. Aessa, S. W. Shneen, and M. K. Oudah, “Optimizing PID Controller for Large-Scale MIMO Systems Using Flower Pollination Algorithm,” Journal of Robotics and Control (JRC), vol. 6, no. 2, pp. 553-559, 2025, https://doi.org/10.18196/jrc.v6i2.24409.
[65] M. Qasim, A. I. Abdulla, and A. B. Ayoub, “Design of a Robust Component-wise Sliding Mode Controller for a Two-Link Manipulator,” Journal of Robotics and Control (JRC), vol. 6, no. 2, pp. 527-534, 2025, https://doi.org/10.18196/jrc.v6i2.25632.
[66] I. V. Merkuryev, T. B. Duishenaliev, G. Wu, Z. Z. Dotalieva, and A. A. Orozbaev, “Robust Velocity Control of Rehabilitation Robots Using Adaptive Sliding Mode and Admittance Strategies,” Journal of Robotics and Control (JRC), vol. 6, no. 3, pp. 1347-1356, 2025, https://doi.org/10.18196/jrc.v6i3.26493.
Refbacks
- There are currently no refbacks.
Copyright (c) 2025 Hamzah M. Marhoon, Zaid Shafeeq Bakr, Reem Falah Hassan, Sarah O. Al-Tahir, Noorulden Basil

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
About the Journal | Journal Policies | Author | Information |
International Journal of Robotics and Control Systems
e-ISSN: 2775-2658
Website: https://pubs2.ascee.org/index.php/IJRCS
Email: ijrcs@ascee.org
Organized by: Association for Scientific Computing Electronics and Engineering (ASCEE), Peneliti Teknologi Teknik Indonesia, Department of Electrical Engineering, Universitas Ahmad Dahlan and Kuliah Teknik Elektro
Published by: Association for Scientific Computing Electronics and Engineering (ASCEE)
Office: Jalan Janti, Karangjambe 130B, Banguntapan, Bantul, Daerah Istimewa Yogyakarta, Indonesia