Experimental Performance Comparison of Hierarchical Multi-Hub and Single-Hop Multi-Node LoRa Networks Using Sequential Polling

Authors

  • Sahid Ridho Telecommunication Engineering, Politeknik Negeri Padang, Indonesia
  • Yustini Politeknik Negeri Padang, Indonesia

DOI:

https://doi.org/10.47709/brilliance.v6i4.9632

Keywords:

hierarchical LoRa network, multi-hub communication, multi-node communication, sequential polling, report delivery ratio, round completion time

Abstract

LoRa networks commonly employ direct single-hop communication between end devices and a gateway; however, this architecture depends on reliable gateway connectivity for every node. A hierarchical multi-hub architecture provides an intermediate data collection layer but introduces additional communication transactions. This study experimentally compares hierarchical multi-hub and single-hop multi-node LoRa architectures using sequential polling under equivalent report-source counts. Four configurations were evaluated: A1 and A2 represented multi-hub communication with two and four report sources, respectively, while B1 and B2 represented equivalent single-hop multi-node configurations. Each configuration was tested for 30 rounds at distances of 10, 50, and 100 m using identical radio parameters. Performance was evaluated using report delivery ratio (PDR), gateway-facing received signal strength indicator (RSSI), round completion time, timeout events, and successful-round ratio. All configurations achieved a PDR of 100% at every distance. A1, B1, and B2 completed all rounds successfully, whereas A2 achieved a successful-round ratio of 96.67% because one timeout occurred at each distance. The mean round completion times were 4.211–4.228 s for A1, 9.208–9.253 s for A2, 1.970–1.974 s for B1, and 3.889–3.897 s for B2. Gateway-facing RSSI decreased with distance, but this reduction did not cause report loss within the tested range. These results demonstrate that single-hop multi-node communication provides faster data collection when direct links are reliable, whereas multi-hub communication provides a structured hierarchical collection path at the cost of higher round completion time.

References

Alahmadi, H., Bouabdallah, F., & Al-Dubai, A. (2022). A novel time-slotted LoRa MAC protocol for scalable IoT networks. Future Generation Computer Systems, 134, 287–302. https://doi.org/10.1016/j.future.2022.04.003

Alhomyani, H., Fadel, M., Dimitriou, N., Bakhsh, H., & Aldabbagh, G. (2024). Modeling the performance of a multi-hop LoRaWAN linear sensor network for energy-efficient pipeline monitoring systems. Applied Sciences, 14(20), Article 9391. https://doi.org/10.3390/app14209391

Álamos, J., Kietzmann, P., Schmidt, T. C., & Wählisch, M. (2022). DSME-LoRa: Seamless long-range communication between arbitrary nodes in the constrained IoT. ACM Transactions on Sensor Networks, 18(4), Article 69, 1–43. https://doi.org/10.1145/3552432

Asteriou, V., Valkanis, A., Beletsioti, G., Kantelis, K., Papadimitriou, G., & Nicopolitidis, P. (2022). LoRaWAN-based adaptive MACs for event response applications. IEEE Access, 10, 97465–97480. https://doi.org/10.1109/ACCESS.2022.3204654

Banti, K., Karampelia, I., Dimakis, T., Boulogeorgos, A.-A. A., Kyriakidis, T., & Louta, M. (2022). LoRaWAN communication protocols: A comprehensive survey under an energy efficiency perspective. Telecom, 3(2), 322–357. https://doi.org/10.3390/telecom3020018

Beletsioti, G. A., Kantelis, K. F., Valkanis, A., Nicopolitidis, P., Papadimitriou, G. I., & Louta, M. (2025). Gateway energy-oriented TDMA for LoRa networks. Electronics, 14(22), Article 4496. https://doi.org/10.3390/electronics14224496

Choi, R., Lee, S., & Lee, S. (2020). Reliability improvement of LoRa with ARQ and relay node. Symmetry, 12(4), Article 552. https://doi.org/10.3390/sym12040552

Fahmida, S., Jain, A., Modekurthy, V. P., Ismail, D., & Saifullah, A. (2024). RTPL: A real-time communication protocol for LoRa network. ACM Transactions on Embedded Computing Systems, 24(1), Article 17, 1–31. https://doi.org/10.1145/3702209

García, L., Cancimance, C., Asorey-Cacheda, R., Zúñiga-Cañón, C.-L., García-Sánchez, A.-J., & García-Haro, J. (2025). Compliant and seamless hybrid (star and mesh) network topology coexistence for LoRaWAN: A proof of concept. Applied Sciences, 15(7), Article 3487. https://doi.org/10.3390/app15073487

Li, C., & Cao, Z. (2022). LoRa networking techniques for large-scale and long-term IoT: A down-to-top survey. ACM Computing Surveys, 55(3), Article 52, 1–36. https://doi.org/10.1145/3494673

Ridho, S., Dahlan, A. A., Yustini, Y., Rusfandi, R., & Ferdiansyah, F. (2025). Evaluasi kinerja eksperimental mekanisme Gateway-Polled Sequential Access (GPSA) pada jaringan LoRa multi-node single-hop untuk aplikasi Internet of Things (IoT). Jurnal Teknologi, 25(3), 258–271. https://doi.org/10.30811/teknologi.v25i3.8301

Sahoo, S. R., Gamage, A., Kumar, N., & Easwaran, A. (2025). LoRaHART: Hardware-aware real-time scheduling for LoRa. In R. Mancuso (Ed.), 37th Euromicro Conference on Real-Time Systems (ECRTS 2025) (Leibniz International Proceedings in Informatics, Vol. 335, Article 10, pp. 10:1–10:28). Schloss Dagstuhl–Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.ECRTS.2025.10

Strzoda, A., & Grochla, K. (2024). A nature-inspired approach to energy-efficient relay selection in low-power wide-area networks (LPWAN). Sensors, 24(11), Article 3348. https://doi.org/10.3390/s24113348

Sun, Z., Yang, H., Liu, K., Yin, Z., Li, Z., & Xu, W. (2022). Recent advances in LoRa: A comprehensive survey. ACM Transactions on Sensor Networks, 18(4), Article 67, 1–44. https://doi.org/10.1145/3543856

Wong, A. W.-L., Goh, S. L., Hasan, M. K., & Fattah, S. (2024). Multi-hop and mesh for LoRa networks: Recent advancements, issues, and recommended applications. ACM Computing Surveys, 56(6), Article 136, 1–43. https://doi.org/10.1145/3638241

Downloads

Published

2026-11-01

How to Cite

Ridho, S., & Yustini, Y. (2026). Experimental Performance Comparison of Hierarchical Multi-Hub and Single-Hop Multi-Node LoRa Networks Using Sequential Polling. Brilliance: Research of Artificial Intelligence, 6(4), 733–746. https://doi.org/10.47709/brilliance.v6i4.9632

Citation Tracker

Citation data is temporarily unavailable.

Source: OpenAlex