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<p>This paper presents a novel and unified cross-layer optimization framework, SFOptSec, specifically designed for LoRaWAN-based IoT environments. Unlike conventional studies that treat communication efficiency and data security as separate goals, SFOptSec holistically integrates adaptive spreading factor (SF) optimization with AES-128-based encryption modeling within a lightweight and energy-aware architecture. The framework dynamically balances energy consumption, reliability, and security by embedding cryptographic overhead directly into the optimization process, achieving real-time adaptation to changing network conditions. A multi-objective optimization model minimizes the combined cost of transmission and encryption energy, subject to reliability and security constraints. Furthermore, a feedback-based gateway adaptation mechanism iteratively refines SF and encryption parameters using observed metrics such as energy, latency, and packet delivery ratio (PDR). Simulation results demonstrate that SFOptSec significantly enhances network efficiency, reducing overall energy consumption and delay while maintaining robust data confidentiality. By unifying physical-layer optimization, link-layer encryption, and feedback-driven adaptation, SFOptSec establishes a scalable, secure, and energy-efficient solution for next-generation low-power IoT communication in dynamic LoRaWAN deployments.</p>

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Energy-efficient spreading factor adaptation with security-constrained closed-loop feedback for dense LoRaWAN deployments

  • 期刊论文

  • 发表日期：

    2026年3月17日

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  • Kumar Vaibhav Bhatnagar,
  • Rashmi Kushwah

摘要

This paper presents a novel and unified cross-layer optimization framework, SFOptSec, specifically designed for LoRaWAN-based IoT environments. Unlike conventional studies that treat communication efficiency and data security as separate goals, SFOptSec holistically integrates adaptive spreading factor (SF) optimization with AES-128-based encryption modeling within a lightweight and energy-aware architecture. The framework dynamically balances energy consumption, reliability, and security by embedding cryptographic overhead directly into the optimization process, achieving real-time adaptation to changing network conditions. A multi-objective optimization model minimizes the combined cost of transmission and encryption energy, subject to reliability and security constraints. Furthermore, a feedback-based gateway adaptation mechanism iteratively refines SF and encryption parameters using observed metrics such as energy, latency, and packet delivery ratio (PDR). Simulation results demonstrate that SFOptSec significantly enhances network efficiency, reducing overall energy consumption and delay while maintaining robust data confidentiality. By unifying physical-layer optimization, link-layer encryption, and feedback-driven adaptation, SFOptSec establishes a scalable, secure, and energy-efficient solution for next-generation low-power IoT communication in dynamic LoRaWAN deployments.