Energy Consumption Optimization in Wireless Sensor Networks Using Adaptive Routing Algorithms
Keywords:
Keywords: Wireless Sensor Network, adaptive routing, energy optimization, network lifetime, multi-hop communicationAbstract
Wireless Sensor Networks (WSNs) are widely used in various monitoring applications, but the limited energy resources of sensor nodes pose a major challenge that affects network performance and lifetime. Conventional routing protocols tend to be static and less adaptable to dynamic network conditions, resulting in uneven energy consumption and shortening network lifetime. This study aims to optimize energy consumption and extend network lifetime in WSNs through the application of adaptive routing algorithms. This study uses a simulation-based quantitative study approach, by designing an adaptive routing algorithm that considers node energy remaining, transmission distance, and communication load. Performance evaluation was conducted through network simulation with a multi-hop communication scheme and compared with the LEACH and PEGASIS routing algorithms using the same simulation parameters. Simulation results show that the adaptive routing algorithm has lower total network energy consumption, which is around ±120 Joules, compared to LEACH (±200 Joules) and PEGASIS (±280 Joules). In addition, the network lifetime increased to approximately ±1800 seconds, which is longer than the comparison algorithms. The results of this study prove that the adaptive routing algorithm is capable of optimizing energy consumption and significantly improving the resilience of WSN networks. Further research is recommended to test the algorithm in more complex and heterogeneous network scenarios and to integrate network security aspects.
Downloads
References
REFERENSI
[1] F. P. E. Putra, D. E. Arissandi, A. Rofiqi, and M. F. Hidayat, “Pemanfaatan Mikrotik Dalam Manajemen Bandwidth Pada Jaringan Sekolah,” 2025, researchgate.net. [Online]. Available: https://www.researchgate.net/profile/Fauzan-Eka-Putra-2/publication/392420575_Pemanfaatan_Mikrotik_Dalam_Manajemen_Bandwidth_Pada_Jaringan_Sekolah/links/6848fab46b5a287c304a61ca/Pemanfaatan-Mikrotik-Dalam-Manajemen-Bandwidth-Pada-Jaringan-Sekolah.pdf
[2] F. Prasetyo, E. Putra, M. Riski, M. S. Yahya, and M. H. Ramadhan, “Mengenal Teknologi Jaringan Nirkabel Terbaru Teknologi 5G,” J. Sistim Inf. dan Teknol., vol. 5, no. 2, pp. 167–174, 2023, [Online]. Available: https://jsisfotek.org/index.php
[3] F. P. E. Putra, S. M. Dewi, Maugfiroh, and A. Hamzah, “Privasi dan Keamanan Penerapan IoT Dalam Kehidupan Sehari-Hari : Tantangan dan Implikasi,” 2023. [Online]. Available: https://jsisfotek.org/index.php/JSisfotek/article/view/232
[4] N. Haidar Hari, F. P. Eka Putra, U. Hasanah, S. R. Sutarsih, and Riyan, “Transformasi Jaringan Telekomunikasi dengan Teknologi 5G: Tantangan, Potensi, dan Implikasi,” J. Inf. dan Teknol., pp. 146–150, 2023, doi: 10.37034/jidt.v5i2.357.
[5] F. P. E. Putra, D. A. M. Putra, A. Firdaus, and A. Hamzah, “Analisis Kecepatan Dan Kinerja Jaringan 5G (generasi ke 5) Pada Wilayah Perkotaan,” INFORMATICS Educ. Prof. J. Informatics, vol. 8, no. 1, p. 47, 2023, doi: 10.51211/itbi.v8i1.2439.
[6] N. Muhammad Akbar, F. Prasetyo Eka Putra, K. Zulfana Imam, and M. Umar Mansyur, “Analisis Kinerja dan Interopabilitas STB Sebagai Server Penilaian Akhir Tahun,” J. Inf. dan Teknol., pp. 91–96, 2023, doi: 10.37034/jidt.v5i2.365.
[7] F. P. Eka Putra, M. N. Arifin, K. Zulfana Imam, E. Saputra, and Sofiyullah, “Pengembangan Sistem Informasi Laboratorium Terintegerasi Sistem Akademik Menggunakan Agile Scrum,” J. Inf. dan Teknol., pp. 109–119, 2023, doi: 10.37034/jidt.v5i2.367.
[8] A. Zulfikri, F. P. E. Putra, M. A. Huda, H. Hasbullah, M. Mahendra, and M. Surur, “Analisis Keamanan Jaringan Dari Serangan Malware Menggunakan Filtering Firewall Dengan Port Blocking,” 2023. doi: 10.47709/digitech.v3i2.3379.
[9] F. P. E. Putra, F. Fauzan, S. Syirofi, M. Mursidi, D. Wahid, and A. Nuraini, “Sistem Pengendali Lingkungan Pertanian Dengan Wireless Sensor Network Untuk Mengoptimalkan Budidaya Hidroponik,” 2024. doi: 10.47709/digitech.v3i2.3461.
[10] F. P. Eka Putra, F. Muslim, N. Hasanah, Holipah, R. Paradina, and R. Alim, “Analisis Komparasi Protokol Websocket dan MQTT Dalam Proses Push Notification,” J. Sistim Inf. dan Teknol., pp. 63–72, 2024, doi: 10.60083/jsisfotek.v5i4.325.
[11] X. Xia et al., “A self-powered and self-sensing wave energy harvester based on a three-rotor motor of axle disk type for sustainable sea,” Energy, vol. 312, 2024, doi: 10.1016/j.energy.2024.133512.
[12] X. Zhang, K. Xiong, W. Chen, P. Pingyi, B. Gao, and K. Ben Letaief, “Maximizing Harvested Energy in Natural Energy Powered RF WPT With Nonlinear EH Model,” IEEE Trans. Wirel. Commun., vol. 24, no. 7, pp. 5432–5445, 2025, doi: 10.1109/TWC.2025.3547045.
[13] M. Schelles, W. Lievens, L. Goyvaerts, F. Ceyssens, R. Muller, and M. Kraft, “Comparison and System Development of a Two-Coil and Three-Coil Inductive Link for Transcutaneous Power Transfer,” IEEE Access, vol. 13, pp. 109219–109233, 2025, doi: 10.1109/ACCESS.2025.3581460.
[14] V. K. Prajapati, T. P. Sharma, and L. K. Kumar Awasthi, “Data Dissemination Framework for Optimizing Overhead in IoT-Enabled Systems Using Tabu-RPL,” SN Comput. Sci., vol. 5, no. 4, 2024, doi: 10.1007/s42979-024-02694-8.
[15] A. B. Benfradj Guiloufi, S. E. El Khediri, N. Nasri, and A. Kachouri, “A comparative study of energy efficient algorithms for IoT applications based on WSNs,” Multimed. Tools Appl., vol. 82, no. 27, pp. 42239–42275, 2023, doi: 10.1007/s11042-023-14813-3.
[16] A. Parmar, K. Shah, K. M. Captain, M. López-Benítez, and J. R. Patel, “Gaussian Mixture Model-Based Anomaly Detection for Defense Against Byzantine Attack in Cooperative Spectrum Sensing,” IEEE Trans. Cogn. Commun. Netw., vol. 10, no. 2, pp. 499–509, 2024, doi: 10.1109/TCCN.2023.3342409.
[17] Y. Bai et al., “UAV Path Planning for Data Collection From Wireless Sensor Network With Matrix-Based Evolutionary Computation,” IEEE Trans. Intell. Transp. Syst., vol. 26, no. 9, pp. 13672–13687, 2025, doi: 10.1109/TITS.2025.3568359.
[18] J. Wang, S. Lu, and C. Li, “UNEVEN CLUSTERING ROUTING PROTOCOLS FOR MULTI-HOP COGNITIVE RADIO SENSOR NETWORKS: GENERAL DESIGN PRINCIPLES AND AN ILLUSTRATIVE EXAMPLE,” Int. J. Innov. Comput. Inf. Control, vol. 21, no. 1, pp. 153–172, 2025, doi: 10.24507/ijicic.21.01.153.
[19] Y. Long et al., “Room-temperature, self-powered hydrogel-based flexible chemosensors for nitrogen dioxide detection enabled by zinc-air batteries,” Biosens. Bioelectron., vol. 290, 2025, doi: 10.1016/j.bios.2025.117941.
[20] D. Chatzoulis, C. Chaikalis, A. Xenakis, D. Kosmanos, and K. E. Anagnostou, “Channel Coding QoS Analysis in 5G V2X Dynamic Propagation Models,” IEEE Access, vol. 13, pp. 80149–80173, 2025, doi: 10.1109/ACCESS.2025.3566607.
[21] K. Zhang et al., “All-Wood-Based Ionic Power Generator with Dual Functions for Alkaline Wastewater Reuse and Energy Harvesting,” ACS Nano, vol. 18, no. 14, pp. 10259–10269, 2024, doi: 10.1021/acsnano.4c00990.
[22] S. Sellamuthu, R. Krithiga, M. Revathi, G. Gajendran, and R. M. Bhavadharini, “Energy aware optimal routing model for wireless multimedia sensor networks using modified Voronoi assisted prioritized double deep Q-learning,” Concurr. Comput. Pract. Exp., vol. 36, no. 6, 2024, doi: 10.1002/cpe.7945.
[23] Y. Dai, X. Jiang, K. Wang, and K. Li, “A phototunable self-oscillatory bistable seesaw via liquid crystal elastomer fibers,” Chaos, Solitons and Fractals, vol. 200, 2025, doi: 10.1016/j.chaos.2025.117041.
[24] Y. Hou, H. He, X. Jiang, S. Chen, and J. Yang, “Deep-Reinforcement-Learning-Aided Loss-Tolerant Congestion Control for 6LoWPAN Networks,” IEEE Internet Things J., vol. 10, no. 21, pp. 19125–19140, 2023, doi: 10.1109/JIOT.2023.3281482.
[25] R. L. Bruun, C. Morejon Santiago Garcia, T. B. Sørensen, N. K. Pratas, T. K. Madsen, and P. Mogensen, “Signaling Design for Cooperative Resource Allocation and Its Impact to Message Reliability,” IEEE Access, vol. 11, pp. 103569–103584, 2023, doi: 10.1109/ACCESS.2023.3317269.
[26] X. Chen, Y. Lin, B. Chen, R. Duan, Z. Zhou, and C. Lu, “Enhancing the Thermoelectric Performance of Sustainable Cellulose-Based Ionogels Through Water Content Regulation,” Small, vol. 21, no. 11, 2025, doi: 10.1002/smll.202412336.
[27] B. Fang, X. Li, G. Han, and J. He, “Rethinking Pseudo-Labeling for Semi-Supervised Facial Expression Recognition With Contrastive Self-Supervised Learning,” IEEE Access, vol. 11, pp. 45547–45558, 2023, doi: 10.1109/ACCESS.2023.3274193.
[28] S. Mohsen Hassan, M. M. Mohamad, and F. Binti Muchtar, “Enhancing MANET Security Through Long Short-Term Memory-Based Trust Prediction in Location-Aided Routing Protocols,” IEEE Access, vol. 13, pp. 120142–120168, 2025, doi: 10.1109/ACCESS.2025.3572619.
[29] F. F. Jurado-Lasso, M. Barzegaran, J. F. Jurado, and X. Fafoutis, “ELISE: A Reinforcement Learning Framework to Optimize the Slotframe Size of the TSCH Protocol in IoT Networks,” IEEE Syst. J., vol. 18, no. 2, pp. 1068–1079, 2024, doi: 10.1109/JSYST.2024.3371429.
[30] A. Pandey, S. Shekhar, A. Nandi, and B. Basu, “On lifetime enhancement of wireless sensor network using particle swarm optimisation,” Int. J. Adv. Intell. Paradig., vol. 25, no. 1–2, pp. 51–67, 2023, doi: 10.1504/IJAIP.2023.130817.
[31] C. Reuter, A. Hughes, and C. Buntain, “Combating information warfare: state and trends in user-centred countermeasures against fake news and misinformation,” Behav. Inf. Technol., vol. 44, no. 13, pp. 3348–3361, 2025, doi: 10.1080/0144929X.2024.2442486.
[32] L. Zhang, S. C. Liew, and H. Chen, “A Just-in-Time Networking Framework for Minimizing Request-Response Latency of Wireless Time-Sensitive Applications,” IEEE Internet Things J., vol. 10, no. 8, pp. 7126–7142, 2023, doi: 10.1109/JIOT.2022.3229125.
[33] K. Abedi, R. Ansari, and M. K. Hassanzadeh-Aghdam, “Effects of aspect ratio and arrangement of PZT-7A piezoelectric fillers on energy harvesting performance of PVDF composite cantilevers,” Proc. Inst. Mech. Eng. Part C J. Mech. Eng. Sci., vol. 239, no. 17 Special Issue: Materials, processes, and procedures: looking for a more sustainable world, pp. 6968–6982, 2025, doi: 10.1177/09544062251343709.
[34] L. Zhai et al., “High-sensitivity blue-energy-shuttle and in-situ electrical behaviors in ocean,” Nano Energy, vol. 125, 2024, doi: 10.1016/j.nanoen.2024.109546.
[35] B. Zeng, S. Li, and X. Gao, “Threshold-driven K-means sector clustering algorithm for wireless sensor networks,” Eurasip J. Wirel. Commun. Netw., vol. 2024, no. 1, 2024, doi: 10.1186/s13638-024-02403-2.
[36] S. Anand and A. V Ananthanarayanan, “Addressing Rogue Nodes and Trust Management: Leveraging Deep Learning-Enhanced Hybrid Trust to Optimize Wireless Sensor Networks Management,” J. Robot. Control, vol. 6, no. 2, pp. 846–861, 2025, doi: 10.18196/jrc.v6i2.25600.
[37] D. Devarajan, “Experimental and numerical study on energy harvesting performance thermoelectric generator applied to a screw compressor,” Energy Harvest. Syst., vol. 11, no. 1, 2024, doi: 10.1515/ehs-2022-0119.
[38] J. Simon, N. Kapileswar, P. Polasi, and M. Elaveini, “Improved geographic opportunistic routing protocol for void hole elimination in underwater IoTs: Parameter tuning by TSA optimization,” Int. J. Commun. Syst., vol. 37, no. 3, 2024, doi: 10.1002/dac.5659.
[39] S. E. Elgharbi, M. Iturralde, Y. Dupuis, and A. Gaugue, “Maritime monitoring through LoRaWAN: Resilient decentralised mesh networks for enhanced data transmission,” Comput. Commun., vol. 241, 2025, doi: 10.1016/j.comcom.2025.108276.
[40] S. Hemelatha, S. Shalini, U. Sathya, P. Kumaravel, S. V Krishna, and P. H. Kulkarni, “AI BASED CLUSTER HEAD BASED MOBILE ADHOC NETWORK FOR PERFORMANCE IMPROVEMENT,” J. Theor. Appl. Inf. Technol., vol. 102, no. 23, pp. 8818–8826, 2024, [Online]. Available: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85212852891&partnerID=40&md5=423ca23062772741ec4fe6fc796b915b
[41] L. Sheng, H. Li, Y. Qi, and M. Shi, “Real Time Screening and Trajectory Optimization of UAVs in Cluster Based on Improved Particle Swarm Optimization Algorithm,” IEEE Access, vol. 11, pp. 81838–81851, 2023, doi: 10.1109/ACCESS.2023.3300377.
[42] R. Nakamura, K. Ebisawa, H. Hayashi, T. Fujiwara, and T. Okuzawa, “Exploiting SRv6 for Stateless and Per-Connection-Consistent Load Balancing,” IEEE Access, vol. 12, pp. 83525–83537, 2024, doi: 10.1109/ACCESS.2024.3413016.
[43] S. Ratheesh and A. A. Breethi, “Deep learning based Non-Local k-best renyi entropy for classification of white blood cell subtypes,” Biomed. Signal Process. Control, vol. 90, 2024, doi: 10.1016/j.bspc.2023.105812.
[44] Q. Yao, D. Meng, H. Yang, N. Feng, and J. Zhang, “Efficient O-type mapping and routing of large-scale neural networks to torus-based ONoCs,” J. Opt. Commun. Netw., vol. 16, no. 9, pp. 918–928, 2024, doi: 10.1364/JOCN.525666.
[45] H. Chen, G. Zu, Q. Ju, and X. Yang, “Hydrogel-based sandwich-structured triboelectric nanogenerator energy harvesting storage system for multi-functional sensing and monitoring,” Chem. Eng. J., vol. 523, 2025, doi: 10.1016/j.cej.2025.168739.
[46] T. Micallef, X. Gu, and K. Wu, “Electric Field Energy Harvesting From High-Voltage Power Lines for Consumer Batteryless Wireless Sensor Networks,” IEEE Trans. Consum. Electron., vol. 71, no. 1, pp. 2322–2331, 2025, doi: 10.1109/TCE.2024.3503492.
[47] A. C. Grilo, P. Oliveira, and R. Valadas, “Hard-state Protocol Independent Multicast—Source-Specific Multicast (HPIM-SSM),” IET Networks, vol. 13, no. 5–6, pp. 486–512, 2024, doi: 10.1049/ntw2.12133.
[48] H. Liu, Z. Yang, N. Zhao, Y. Gu, and C. Yuen, “Interference-Aware Multihop Routing in UAV Networks: A Harmonic-Function-Based Potential Field Approach,” IEEE Internet Things J., vol. 11, no. 11, pp. 19406–19420, 2024, doi: 10.1109/JIOT.2024.3366580.
[49] W. Wang, Y. Gong, H. Zhang, X. Yuan, and Y. Zhang, “Quantitative Assessment of Fall Risk in the Elderly Through Fusion of Millimeter-Wave Radar Imaging and Trajectory Features,” IEEE Access, vol. 12, pp. 13370–13385, 2024, doi: 10.1109/ACCESS.2024.3355927.
[50] L. Bian, Y. Zhou, L. Liu, D. Li, N. Shi, and J. Shi, “Low-latency data routing method based on an AI-constructed line-of-sight map,” Xi’an Dianzi Keji Daxue Xuebao/Journal Xidian Univ., vol. 52, no. 3, pp. 188–201, 2025, doi: 10.19665/j.issn1001-2400.20250508.
[51] I. Ali, S. Hong, and T. Cheung, “Quality of Service and Congestion Control in Software-Defined Networking Using Policy-Based Routing,” Appl. Sci., vol. 14, no. 19, 2024, doi: 10.3390/app14199066.
[52] X. Yu, “Exploiting data transmission for route discoveries in mobile ad hoc networks,” Wirel. Networks, vol. 31, no. 2, pp. 1337–1359, 2025, doi: 10.1007/s11276-024-03796-0.
[53] M. M. H. Alkalsh and A. Kliks, “Scalable Mobility Proactive-Reactive Load Balancing (PRLB) Algorithm for High-Density Environments of Future Wireless Networks,” IEEE Access, vol. 13, pp. 140028–140045, 2025, doi: 10.1109/ACCESS.2025.3596682.
[54] T. Ishizaki and T. Matsumuro, “Development of an Active Integrated Antenna for 24-GHz Wireless Power Transfer System,” IEEE Trans. Microw. Theory Tech., vol. 73, no. 3, pp. 1396–1405, 2025, doi: 10.1109/TMTT.2024.3430893.
[55] A. P. Tchinda, B. Shala, A. Lehmann, B. Ghita, D. Walker, and U. Trick, “Energy-Efficient Placement of Virtual Network Functions in a Wireless Mesh Network,” IEEE Access, vol. 12, pp. 64807–64822, 2024, doi: 10.1109/ACCESS.2024.3394907.
Published
Issue
Section
License
Copyright (c) 2025 Abd Rosyid, Akmal Maulana (Penulis)
This work is licensed under a Creative Commons Attribution 4.0 International License.
