J-DEAS: A Jamming-Driven Exponential Adaptive Sleeping Technique for Energy-Aware Mitigation in LoRa Networks
Journal
Journal of Sensor and Actuator Networks
Date Issued
2026-07-02
Author(s)
Del-Valle-Soto, Carolina
Mex-Perera, Carlos
Velazquez, Eduard
Valdivia, Leonardo J.
Montoya-Márquez, Orlando
Type
Article
Abstract
Low-Power Wide-Area Networks based on LoRa are widely deployed in smart city, agricultural, and environmental monitoring, where their constrained energy budget makes them vulnerable to radio-frequency jamming. (1) Background: a node that keeps transmitting into a jammed channel wastes energy on undeliverable packets, yet detection and energy management are usually treated separately. (2) Methods: we present J-DEAS, a Jamming-Driven Exponential Adaptive Sleeping technique that couples a lightweight, threshold-based detector with an exponential sleep back-off scheduler. The detector uses only the RSSI and SNR reported by commodity transceivers, and a single exponentially weighted confidence variable drives the sleep interval; we analyze the decision boundary, confidence dynamics, steady-state duty cycle, and latency–energy trade-off in closed form. (3) Results: on a measurement dataset the detector reaches an AUC of 0.985 and an F1 of 0.969; under sustained jamming, J-DEAS cuts the duty cycle from 100% to 5.5% and wasted transmissions from 94.3% to 8.3%, with a single-slot median latency and a sub-2% false-sleep rate on clean channels. (4) Conclusions: the technique needs no training and no extra hardware, making it suitable for resource-constrained end devices. © 2026 by the authors.