Pengoptimalan Daya Tahan Baterai: Strategi Duty Cycling Untuk Memperpanjang Umur Node Sensor Pada jaringan IoT
Keywords:
duty cycling, IoT, node sensor, efisiensi energi, bateraiAbstract
Kajian ini membahas masalah keterbatasan sumber daya pada node sensor yang merupakan komponen penting dalam jaringan Internet of Things (IoT). Permintaan energi yang tinggi, terutama untuk komunikasi tanpa kabel, secara langsung memperpendek umur perangkat yang menggunakan baterai. Penelitian ini fokus pada pengembangan mekanisme pengaturan siklus kerja yang adaptif, yaitu penyesuaian waktu aktif dan mode hemat daya secara dinamis dengan memperhitungkan sisa energi dan kebutuhan pertukaran data. Metodologi yang digunakan adalah kuantitatif melalui eksperimen, meliputi pembuatan skenario pengujian, penerapan algoritma yang adaptif, pengukuran konsumsi energi, serta perbandingan kinerja dengan metode statis dan tanpa pengelolaan sleep-wake.Hasil penelitian menunjukkan bahwa pendekatan adaptif dapat secara signifikan mengurangi penggunaan energi, menjaga kestabilan penurunan daya, dan memperpanjang masa pakai baterai dibandingkan dengan metode umum. Selain itu, mekanisme ini lebih fleksibel dalam menghadapi perubahan keadaan jaringan dan volume data. Walaupun peningkatan durasi mode tidur dapat menyebabkan penundaan dalam komunikasi, dampaknya masih dapat diterima untuk aplikasi IoT yang tidak membutuhkan respons waktu yang sangat ketat.Secara keseluruhan, penelitian ini memberikan kontribusi konseptual dalam pengelolaan energi pada sistem IoT serta menawarkan solusi praktis yang efisien untuk digunakan di lapangan. Temuan ini juga membuka peluang untuk penelitian lebih lanjut pada jaringan berskala besar dan kemungkinan integrasi dengan sumber energi alternatif.
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References
[1] S. Pawar, “IoT Solutions in Agriculture: Enhancing Efficiency and Productivity,” International Journal of Innovative Science and Research Technology (IJISRT), pp. 3388–3390, Jun. 2024, doi: 10.38124/ijisrt/IJISRT24MAY2442.
[2] S. Lu, J. Lu, K. An, X. Wang, and Q. He, “Edge Computing on IoT for Machine Signal Processing and Fault Diagnosis: A Review,” IEEE Internet Things J, vol. 10, no. 13, pp. 11093–11116, Jul. 2023, doi: 10.1109/JIOT.2023.3239944.
[3] B. Rana, Y. Singh, P. Kumar Singh, and W.-C. Hong, “A Priority Based Energy-Efficient Metaheuristic Routing Approach for Smart Healthcare System (SHS),” IEEE Access, vol. 12, pp. 85694–85708, 2024, doi: 10.1109/ACCESS.2024.3411564.
[4] S. Hudda, K. Haribabu, and R. Barnwal, “Energy efficient data communication for WSN based resource constrained IoT devices,” Internet of Things, vol. 27, p. 101329, Oct. 2024, doi: 10.1016/j.iot.2024.101329.
[5] M. Saleem et al., “Integrating Smart Energy Management System with Internet of Things and Cloud Computing for Efficient Demand Side Management in Smart Grids,” Energies (Basel), vol. 16, no. 12, p. 4835, Jun. 2023, doi: 10.3390/en16124835.
[6] L. Wu, P. Liu, J. Qu, C. Zhang, and B. Zhang, “Duty Cycle Scheduling in Wireless Sensor Networks Using an Exploratory Strategy-Directed MADDPG Algorithm,” International Journal of Sensors and Sensor Networks, vol. 12, no. 1, pp. 1–12, Feb. 2024, doi: 10.11648/j.ijssn.20241201.11.
[7] T. S. Tagare and R. Narendra, “Design and implementation of duty cycle-based futuristic clustering technique in WSN,” Indonesian Journal of Electrical Engineering and Computer Science, vol. 34, no. 2, p. 951, May 2024, doi: 10.11591/ijeecs.v34.i2.pp951-959.
[8] K. H. V. Prasad and S. Periyasamy, “Secure-Energy Efficient Bio-Inspired Clustering and Deep Learning-Based Routing Using Blockchain for Edge Assisted WSN Environment,” IEEE Access, vol. 11, pp. 145421–145440, 2023, doi: 10.1109/ACCESS.2023.3345218.
[9] O. Khalifa et al., “Energy-Efficient Aerial Data Aggregation for IoT: From Prototyping to Large-Scale Implementation,” IEEE Trans Instrum Meas, vol. 74, pp. 1–18, 2025, doi: 10.1109/TIM.2024.3497061.
[10] S. Arisdakessian, O. A. Wahab, A. Mourad, H. Otrok, and M. Guizani, “A Survey on IoT Intrusion Detection: Federated Learning, Game Theory, Social Psychology, and Explainable AI as Future Directions,” IEEE Internet Things J, vol. 10, no. 5, pp. 4059–4092, Mar. 2023, doi: 10.1109/JIOT.2022.3203249.
[11] M. Albeladi, K. Jambi, F. E. Eassa, and M. Khemakhem, “Optimizing Energy Efficiency and Increasing Scalability in 6G-IoT Networks Through SDN, Duty Cycling, and AI-Driven Slicing,” International Journal of Advanced Computer Science and Applications, vol. 16, no. 9, 2025, doi: 10.14569/IJACSA.2025.0160988.
[12] S. Safiuddin and F. P. E. Putra, “Strategi Efisiensi Wireless Sensor Network (WSN),” INFORMATICS FOR EDUCATORS AND PROFESSIONAL : Journal of Informatics, vol. 8, no. 1, p. 52, Jul. 2023, doi: 10.51211/itbi.v8i1.2441.
[13] A. Heidari, M. A. J. Jamali, N. J. Navimipour, and S. Akbarpour, “A QoS-Aware Technique for Computation Offloading in IoT-Edge Platforms Using a Convolutional Neural Network and Markov Decision Process,” IT Prof, vol. 25, no. 1, pp. 24–39, Jan. 2023, doi: 10.1109/MITP.2022.3217886.
[14] C. Deng, X. Fang, and X. Wang, “UAV-Enabled Mobile-Edge Computing for AI Applications: Joint Model Decision, Resource Allocation, and Trajectory Optimization,” IEEE Internet Things J, vol. 10, no. 7, pp. 5662–5675, Apr. 2023, doi: 10.1109/JIOT.2022.3151619.
[15] F. P. E. Putra, M. Surur, M. Mahendra, and G. Arifin, “Internet Network QOS Analysis at Yala Kopitiam pamekasan Using Wireshak,” Brilliance: Research of Artificial Intelligence, vol. 5, no. 1, pp. 190–200, Jun. 2025, doi: 10.47709/brilliance.v5i1.5940.
[16] N. Kumar and R. Beniwal, “Energy-Efficient Techniques in IoT-based Software-Defined Wireless Sensor Networks: A Systematic Review,” in 2025 7th International Conference on Energy, Power and Environment (ICEPE), IEEE, May 2025, pp. 1–6. doi: 10.1109/ICEPE65965.2025.11139460.
[17] F. P. E. Putra, U. Ubaidi, D. Mayangsari, and N. Hasanah, “Netvista Public Wireless Network Quality Analysis Using Quality Of Service Parameters,” Brilliance: Research of Artificial Intelligence, vol. 4, no. 1, pp. 443–452, Aug. 2024, doi: 10.47709/brilliance.v4i1.4388.
[18] S. Visishta, G. L. Krishna, M. U. Prabhas, A. Karthikeyan, and V. Srividhya, “Energy and Bandwidth Efficient Cluster Based Data Aggregation for Lifetime Improvement of IoT based Wireless Sensor Networks,” in 2024 3rd International Conference on Artificial Intelligence For Internet of Things (AIIoT), IEEE, May 2024, pp. 1–6. doi: 10.1109/AIIoT58432.2024.10574698.
[19] F. P. E. Putra, M. Surur, M. Mahendra, and G. Arifin, “Internet Network QOS Analysis at Yala Kopitiam pamekasan Using Wireshak,” Brilliance: Research of Artificial Intelligence, vol. 5, no. 1, pp. 190–200, Jun. 2025, doi: 10.47709/brilliance.v5i1.5940.
[20] A. Patil and J. Kendule, “IoT-based Battery Health Monitoring and Its Remaining Useful Life Prediction using Artificial Neural Network,” in 2024 IEEE International Students’ Conference on Electrical, Electronics and Computer Science (SCEECS), IEEE, Feb. 2024, pp. 1–5. doi: 10.1109/SCEECS61402.2024.10481911.
[21] S. Chakravarty and T. Acharya, “Sleep Scheduling Based Protocol design for delay tolerant traffic in RF energy harvesting IoT network,” in 2022 IEEE 19th International Conference on Smart Communities: Improving Quality of Life Using ICT, IoT and AI (HONET), IEEE, Dec. 2022, pp. 157–159. doi: 10.1109/HONET56683.2022.10019123.
[22] S. A. Latif, M. Drieberg, S. Sarang, A. Abd Aziz, R. Ahmad, and G. M. Stojanović, “A Reinforcement Learning-Based Intelligent Duty Cycle MAC Protocol for Internet of Things,” IEEE Access, vol. 13, pp. 156170–156187, 2025, doi: 10.1109/ACCESS.2025.3606053.
[23] S. Sarang, G. M. Stojanović, M. Drieberg, S. Stankovski, K. Bingi, and V. Jeoti, “Machine Learning Prediction Based Adaptive Duty Cycle MAC Protocol for Solar Energy Harvesting Wireless Sensor Networks,” IEEE Access, vol. 11, pp. 17536–17554, 2023, doi: 10.1109/ACCESS.2023.3246108.
[24] N. Charef, M. Abdelhafidh, A. Ben Mnaouer, K. Andersson, and S. Cherkaoui, “RL-Based Adaptive Duty Cycle Scheduling in WSN-Based IoT Nets,” in GLOBECOM 2023 - 2023 IEEE Global Communications Conference, IEEE, Dec. 2023, pp. 3777–3782. doi: 10.1109/GLOBECOM54140.2023.10437207.
[25] P. Bulić, G. Kojek, and A. Biasizzo, “Data Transmission Efficiency in Bluetooth Low Energy Versions,” Sensors, vol. 19, no. 17, p. 3746, Aug. 2019, doi: 10.3390/s19173746.
[26] S. Gautam and S. Kumar, “BLE Extended Advertisements for Energy Efficient and Reliable Transfer of Large Sensor Data in Monitoring Applications,” IEEE Transactions on Green Communications and Networking, vol. 9, no. 3, pp. 1092–1106, Sep. 2025, doi: 10.1109/TGCN.2024.3523673.
[27] A. Vatankhah and R. Liscano, “QoS-Aware Energy-Efficient Time-Slotted Channel Hopping Scheduling Algorithm,” in ICC 2025 - IEEE International Conference on Communications, IEEE, Jun. 2025, pp. 3538–3544. doi: 10.1109/ICC52391.2025.11161043.
[28] S. Safiuddin and F. P. E. Putra, “Strategi Efisiensi Wireless Sensor Network (WSN),” INFORMATICS FOR EDUCATORS AND PROFESSIONAL : Journal of Informatics, vol. 8, no. 1, p. 52, Jul. 2023, doi: 10.51211/itbi.v8i1.2441.
[29] B. Ji, H. Tang, J. Yao, and F. Hong, “A Full Duty Cycle Range Soft-Switching High Frequency and High-Efficiency Dual-Buck-ZVT Inverter,” IEEE Transactions on Industrial Electronics, vol. 72, no. 12, pp. 12706–12718, Dec. 2025, doi: 10.1109/TIE.2025.3569968.
[30] G. R. R. Dewa, C. Park, and I. Sohn, “Priority-Aware Scheduling for High-Dense Healthcare IoT (H-IoT) Networks Using Message-Passing Algorithm,” IEEE Internet Things J, vol. 11, no. 12, pp. 21604–21619, Jun. 2024, doi: 10.1109/JIOT.2024.3375322.
[31] A. Rani, R. Kumar, and A. Ram, “An Energy Efficiency Enhanced through Duty Cycle based on Clusters in Wireless Body Area Network,” in 2024 3rd International conference on Power Electronics and IoT Applications in Renewable Energy and its Control (PARC), IEEE, Feb. 2024, pp. 47–51. doi: 10.1109/PARC59193.2024.10486791.
[32] S. khan, T. Mazhar, T. Shahzad, Y. Y. Ghadi, and H. Hamam, “Integrating IoT and WSN: Enhancing quality of service through energy efficiency, scalability, and secure communication in smart systems,” Peer Peer Netw Appl, vol. 18, no. 5, p. 249, Sep. 2025, doi: 10.1007/s12083-025-02070-0.
[33] A. M. Jadhav, P. Ranpise, and O. Jadhav, “Optimizing Power Consumption in IoT Sensor Systems through Adaptive Duty Cycling with Intelligent Automated Switching,” International Journal of Environment and Climate Change, vol. 15, no. 4, pp. 119–133, Apr. 2025, doi: 10.9734/ijecc/2025/v15i44797.
[34] K. Das, N. N. Devi, and S. Moulik, “EADA: Energy-Aware Adaptive Duty-Cycle Adjustment in Superframe for IEEE 802.15.6-Based Wireless Body Area Networks,” IEEE Sens Lett, vol. 8, no. 8, pp. 1–4, Aug. 2024, doi: 10.1109/LSENS.2024.3432161.
[35] P. Kumar, R. Kumar, A. Kumar, A. A. Franklin, S. Garg, and S. Singh, “Retracted: Blockchain and Deep Learning for Secure Communication in Digital Twin Empowered Industrial IoT Network,” IEEE Trans Netw Sci Eng, vol. 10, no. 5, pp. 2802–2813, Sep. 2023, doi: 10.1109/TNSE.2022.3191601.
[36] W. He, M. J. A. Baig, and M. T. Iqbal, “An Internet of Things—Supervisory Control and Data Acquisition (IoT-SCADA) Architecture for Photovoltaic System Monitoring, Control, and Inspection in Real Time,” Electronics (Basel), vol. 14, no. 1, p. 42, Dec. 2024, doi: 10.3390/electronics14010042.
[37] F. P. Eka Putra, Ach. M. Ubaidillah Solichin, Moh. N. Wildanul Hakim, and M. T. Ramadhan, “Pemanfaatan Teknologi Wireless dan Mobile Network Berbasis 5G Untuk Pemerataan Akses Jaringan di Indonesia,” Infotek: Jurnal Informatika dan Teknologi, vol. 8, no. 2, pp. 415–425, Jul. 2025, doi: 10.29408/jit.v8i2.30559.
[38] M. Saban et al., “A Smart Agricultural System Based on PLC and a Cloud Computing Web Application Using LoRa and LoRaWan,” Sensors, vol. 23, no. 5, p. 2725, Mar. 2023, doi: 10.3390/s23052725.
[39] F. P. Eka Putra, A. Baidawi, A. A. Mubarok, and Frediyanto, “Merancang Jaringan Sensor Nirkabel dan IoT untuk Kota Pintar Pamekasan,” Jurnal Informasi dan Teknologi, pp. 138–145, Jul. 2023, doi: 10.37034/jidt.v5i2.331.
[40] Md. N. Mowla, N. Mowla, A. F. M. S. Shah, K. M. Rabie, and T. Shongwe, “Internet of Things and Wireless Sensor Networks for Smart Agriculture Applications: A Survey,” IEEE Access, vol. 11, pp. 145813–145852, 2023, doi: 10.1109/ACCESS.2023.3346299.
[41] X. Deng, J. Yin, P. Guan, N. N. Xiong, L. Zhang, and S. Mumtaz, “Intelligent Delay-Aware Partial Computing Task Offloading for Multiuser Industrial Internet of Things Through Edge Computing,” IEEE Internet Things J, vol. 10, no. 4, pp. 2954–2966, Feb. 2023, doi: 10.1109/JIOT.2021.3123406.
[42] F. P. E. Putra, U. Ubaidi, R. N. Saputra, F. M. Haris, and S. N. R. Barokah, “Application of Internet of Things Technology in Monitoring Water Quality in Fishponds,” Brilliance: Research of Artificial Intelligence, vol. 4, no. 1, pp. 356–361, Jul. 2024, doi: 10.47709/brilliance.v4i1.4231.
[43] S. He, Q. Li, M. Khishe, A. Salih Mohammed, H. Mohammadi, and M. Mohammadi, “The optimization of nodes clustering and multi-hop routing protocol using hierarchical chimp optimization for sustainable energy efficient underwater wireless sensor networks,” Wireless Networks, vol. 30, no. 1, pp. 233–252, Jan. 2024, doi: 10.1007/s11276-023-03464-9.
[44] S. Khriji, R. Chéour, and O. Kanoun, “Dynamic Voltage and Frequency Scaling and Duty-Cycling for Ultra Low-Power Wireless Sensor Nodes,” Electronics (Basel), vol. 11, no. 24, p. 4071, Dec. 2022, doi: 10.3390/electronics11244071.
[45] F. P. E. Putra, U. Ubaidi, M. A. Huda, H. Hasbullah, and A. Rohman, “Computer Network Management Optimization Through Big Data Analysis Using Time Series Analysis Method,” Brilliance: Research of Artificial Intelligence, vol. 4, no. 1, pp. 434–442, Aug. 2024, doi: 10.47709/brilliance.v4i1.4373.
[46] X. Huang et al., “Lithium-Ion Battery Lifetime Extension With Positive Pulsed Current Charging,” IEEE Transactions on Industrial Electronics, vol. 71, no. 1, pp. 484–492, Jan. 2024, doi: 10.1109/TIE.2023.3250850.
[47] F. P. Eka Putra, I. N. Sudana Degeng, S. Ulfa, and W. Kamdi, “The Evolution of Quality Education: Impacts and Challenges of Using Open Educational Resources (OER) and Open Educational Practices (OEP) in the Conceive - Design - Implement - Operate (CDIO) Framework,” TEM Journal, pp. 386–395, Feb. 2024, doi: 10.18421/TEM131-40.
[48] F. P. Eka Putra, L. Fitriyah, Z. Naimah, and S. A. Rofika, “Evaluasi Kinerja Aplikasi Wireshark Dalam Monitoring Jaringan Kecil Dengan Topologi Star dan Bus,” Jurnal Ilmiah ILKOMINFO - Ilmu Komputer & Informatika, vol. 8, no. 2, pp. 164–176, Jul. 2025, doi: 10.47324/ilkominfo.v8i2.343.
[49] V. Nkemeni, F. Mieyeville, and P. Tsafack, “Energy Consumption Reduction in Wireless Sensor Network-Based Water Pipeline Monitoring Systems via Energy Conservation Techniques,” Future Internet, vol. 15, no. 12, p. 402, Dec. 2023, doi: 10.3390/fi15120402.
[50] C. Portillo, J. Martinez-Bauset, V. Pla, and V. Casares-Giner, “Energy Consumption Modeling for Heterogeneous Internet of Things Wireless Sensor Network Devices: Entire Modes and Operation Cycles Considerations,” Telecom, vol. 5, no. 3, pp. 723–746, Aug. 2024, doi: 10.3390/telecom5030036.
[51] G. Kaur, V. Balyan, and S. H. Gupta, “Experimental analysis of low-duty cycle campus deployed IoT network using LoRa technology,” Results in Engineering, vol. 23, p. 102844, Sep. 2024, doi: 10.1016/j.rineng.2024.102844.
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