Hybrid BLE–LoRa architectures for energy-efficient and resilient wireless sensor networks: Experimental validation and adaptive clustering strategies
Journal
Peer-to-Peer Networking and Applications
Date Issued
2026-06-03
Author(s)
Del-Valle-Soto, Carolina
Briseño, Ramon A.
Valdivia, Leonardo J.
Visconti, Paolo
Type
Article
Abstract
Wireless Sensor Networks are increasingly deployed in mission-critical scenarios where resilience and energy efficiency are paramount. This paper presents a hybrid architecture combining Bluetooth Low Energy (BLE) and Long Range (LoRa) technologies to enhance both robustness and energy-aware performance in adversarial environments characterized by reactive jamming attacks. A comprehensive experimental testbed was developed, integrating BLE and LoRa nodes, a dual-protocol gateway, and a reactive jammer emulator. We introduce an adaptive clustering algorithm that performs energy-aware role assignment and jamming mitigation based on signal anomaly detection and multi-metric routing. To validate its effectiveness, we conducted an extensive time-series analysis on energy consumption, retransmission rates, and signal resilience under both mitigated and non-mitigated conditions across BLE-only, LoRa-only, and hybrid BLE-LoRa networks. The results show protocol-dependent performance trade-offs under the proposed mitigation algorithm. While LoRa-only and hybrid BLE–LoRa networks exhibit consistent reductions in energy consumption, retransmissions, and variability, the BLE-only configuration demonstrates improved resilience at the cost of a moderate increase in energy usage and retransmission activity due to clustering and control overhead. Notably, the BLE-LoRa architecture balances delivery assurance and energy efficiency while maintaining communication even under interference. Furthermore, we provide statistical modeling and hypothesis testing confirming the mitigation algorithm’s significant impact. These findings offer a critical empirical contribution to the design of resilient and energy-aware heterogeneous WSNs and demonstrate the viability of real-time adaptive mitigation strategies for emerging smart environments