Adaptive Jamming Mitigation for Clustered Energy-Efficient LoRa-BLE Hybrid Wireless Sensor Networks.

Area of Science:

• Computer Science
• Electrical Engineering
• Network Security

Background:

• Wireless sensor networks (WSNs) are crucial for Internet of Things (IoT) applications but are susceptible to jamming attacks.
• Jamming degrades WSN reliability and energy efficiency, hindering critical IoT functions.
• Heterogeneous WSNs integrating multiple communication protocols offer potential for enhanced resilience.

Purpose of the Study:

• To propose and evaluate a novel adaptive cluster-based jamming mitigation algorithm for heterogeneous WSNs.
• To enhance the resilience, energy efficiency, and data transmission reliability of WSNs against jamming attacks.
• To leverage the integration of LoRa and Bluetooth Low Energy (BLE) technologies for interference mitigation.

Main Methods:

• Developed an adaptive cluster-based algorithm for heterogeneous WSNs combining LoRa and BLE.
• Implemented dynamic switching between communication protocols based on real-time network conditions.
• Utilized real-time network topology adjustments and adaptive transmission power control for interference mitigation.

Main Results:

• Reduced energy consumption by up to 38% under jamming conditions.
• Lowered packet retransmission rates by 47% compared to single-protocol networks.
• Demonstrated superior network resilience, adaptability, and sustained data transmission of the hybrid LoRa-BLE approach over standalone configurations.

Conclusions:

• The proposed multi-protocol jamming mitigation strategy significantly improves WSN performance under attack.
• Hybrid LoRa-BLE WSNs offer a more robust and energy-efficient solution for IoT applications facing interference.
• This work paves the way for more secure and reliable WSN deployments in smart cities and industrial IoT.