Power Efficiency Evaluation of Low-Cost IoT Repeater in Indoor Wireless Networks: Politeknik Aceh Selatan Campus Case Study
DOI:
https://doi.org/10.62671/gaset.v1i2.252Keywords:
ESP8266; IoT repeater; power efficiency; energy consumption; indoor wireless networks; smart campus;Abstract
Low-cost Wi-Fi repeaters are increasingly deployed in smart campus environments to enhance indoor wireless coverage; however, their energy performance under realistic traffic conditions remains insufficiently quantified. This paper presents a comprehensive experimental evaluation of the power efficiency of an ESP8266-based IoT repeater operating in simultaneous Access Point and Station (AP+STA) mode over IEEE 802.11n (2.4 GHz). Unlike prior studies focusing primarily on protocol-level optimization or simulation-based relay models, this work provides hardware-level, real-time power characterization under controlled multi-client traffic scenarios. Experimental measurements demonstrate that average power consumption increases from 0.26 W (78 mA) in idle mode to 0.60 W (182 mA) with a single active client and up to 0.87 W (264 mA) under five-client high-load conditions. The maximum observed throughput reaches 18.4 Mbps, while energy per transmitted bit degrades from 0.032 µJ/bit to 0.047 µJ/bit as traffic intensity increases, revealing a measurable efficiency loss due to simultaneous packet reception and retransmission. A near-linear correlation (R² > 0.94) between traffic load and power consumption is identified, enabling the derivation of an empirical energy–performance model. The findings provide quantitative insight into the trade-off between coverage extension and energy demand in low-cost IoT repeaters. The proposed evaluation framework and empirical model support energy-aware deployment strategies for smart campus
References
Forenbacher, I., Husnjak, S., Jovović, I., & Bobić, M. (2021). Throughput of an IEEE 802.11 Wireless Network in the Presence of Wireless Audio Transmission: A Laboratory Analysis. In Sensors (Vol. 21, Issue 8, p. 2620). https://doi.org/10.3390/s21082620
Kamaludin, K. H., & Ismail, W. (2026). Energy-efficient architecture for perception layer of IoT system. Scientific Reports, 16(1), 2760. https://doi.org/10.1038/s41598-025-32641-3
Lee, S., Baek, C. M., Kim, G. H., Pattipaka, S., Song, H., Jang, J., Hwang, G.-T., & Ryu, J. (2024). Driving Wi-Fi IoT Sensors by a Hybrid Magneto-Mechano-Electric Energy Generator Extracting a Power of over 50 mW. Advanced Science, 11(44), 2405526. https://doi.org/https://doi.org/10.1002/advs.202405526
Lee, S., Park, J., Choi, H., & Oh, H. (2023). Energy-Efficient AP Selection Using Intelligent Access Point System to Increase the Lifespan of IoT Devices. In Sensors (Vol. 23, Issue 11, p. 5197). https://doi.org/10.3390/s23115197
Liu, R., & Choi, N. (2023). A First Look at Wi-Fi 6 in Action: Throughput, Latency, Energy Efficiency, and Security. Proceedings of the ACM on Measurement and Analysis of Computing Systems, 7, 1–25. https://doi.org/10.1145/3579451
Makhetha, M. J., Markus, E. D., & Abu-Mahfouz, A. M. (2024). Integration of wireless power transfer and low power wide area networks in IoT applications—A review. Sensors International, 5, 100284. https://doi.org/https://doi.org/10.1016/j.sintl.2024.100284
Masood, Z., Ardiansyah, & Choi, Y. (2021). Energy-Efficient Optimal Power Allocation for SWIPT Based IoT-Enabled Smart Meter. In Sensors (Vol. 21, Issue 23, p. 7857). https://doi.org/10.3390/s21237857
Robinsha S, D., & Amutha, B. (2025). Edge Computing for Energy-Efficient Internet of Things: Concepts, Technologies, and Applications (pp. 209–230). https://doi.org/10.4018/979-8-3373-2802-7.ch009
Sanchez-Vital, R., Gomez, C., & Garcia-Villegas, E. (2024). Exploring the boundaries of energy-efficient Wireless Mesh Networks with IEEE 802.11ba. Internet of Things, 28, 101366. https://doi.org/https://doi.org/10.1016/j.iot.2024.101366
Sharma, A., Li, J., Mishra, D., Jha, S., & Seneviratne, A. (2024). Towards Energy Efficient Wireless Sensing by Leveraging Ambient Wi-Fi Traffic. In Energies (Vol. 17, Issue 2, p. 485). https://doi.org/10.3390/en17020485
Skrastins, V., Medvedevs, V., Orlovs, D., Ormanis, J., & Judvaitis, J. (2026). Experimental Evaluation of NB-IoT Power Consumption and Energy Source Feasibility for Long-Term IoT Deployments. In IoT (Vol. 7, Issue 1, p. 7). https://doi.org/10.3390/iot7010007
Sridevi, & Kolhar, A. (2025). Energy-Efficiency Strategies for Wireless Sensor Networks in IoT (pp. 167–192). https://doi.org/10.4018/979-8-3373-0300-0.ch006
Xu, F., Wang, Y., Zhang, X., Xie, Y., & Samy, R. (2025). Statistical energy consumption analysis and optimization for relaying transmission with wireless power transfer. Digital Communications and Networks. https://doi.org/https://doi.org/10.1016/j.dcan.2025.06.012
Xu, Z., Kane, L., Liu, V., Mckague, M., & Li, Y. (2025). Energy Consumption Modeling for Wi-Fi HaLow Networks. IEEE Open Journal of the Communications Society, PP, 1. https://doi.org/10.1109/OJCOMS.2025.3578864
Yuksel, M. (2020). Power Consumption Analysis of a Wi-Fi-based IoT Device. Electrica, 20, 62–70. https://doi.org/10.5152/electrica.2020.19081
Zhang, Y., Liu, Y., Wang, C., & Dong, J. (2026). Link Performance Prediction of Power Fiber Optic Communication System Based on Attention Mechanism and Convolutional Neural Network Fusion. ELECTRICA, 26, 1–15. https://doi.org/10.5152/electrica.2026.25162



