# Adaptive Jamming Mitigation for Clustered Energy-Efficient LoRa-BLE Hybrid Wireless Sensor Networks
## 4 Results and Discussion
### Scenario 2: LoRa-Based Communication with Cluster-Based Mitigation and a Jammer Node  
In this experiment, the network operates solely on LoRa communication, where CC1352P sensors use LoRaWAN to transmit data to the Laird Sentirius Gateway. Each CH aggregates data from its cluster members and relays them to the gateway via long-range LoRa links. A LoRa jammer is introduced near one CH, causing high interference levels in the sub-GHz spectrum. The mitigation strategy relies on alternative CH selection and rerouting through neighboring CHs. Key metrics evaluated:  
* Retransmission Rate: The number of attempts needed before successful data reception at the gateway. Figure 4: Impact of the proposed mitigation algorithm on BLE resilience under jamming conditions. Figure 3: Impact of the proposed mitigation algorithm on BLE retransmissions under jamming conditions. Figure 2: Impact of the proposed mitigation algorithm on BLE energy consumption under jamming conditions. * Energy Consumption: The impact of increased LoRa transmissions due to jamming. * Routing Resilience: The time required for affected nodes to reroute their packets through an alternative CH. The results depicted in Figures 5-7 provide a comprehensive evaluation of the impact of jamming on LoRa-based communication and the effectiveness of the proposed cluster-based mitigation algorithm. Figure 5 highlights the energy consumption trend in a LoRa network under jamming conditions, comparing scenarios with and without the mitigation algorithm. In the absence of mitigation, energy consumption steadily increases due to frequent retransmissions caused by interference in the sub-GHz spectrum. This trend demonstrates the inefficiency of conventional LoRa communication when facing external attacks, as nodes continuously attempt to transmit unsuccessfully, leading to excessive power drain. However, with the mitigation algorithm in place, the network dynamically reorganizes itself, redistributing transmission responsibilities among the most resilient nodes and optimizing power usage. This results in a significant reduction in overall energy consumption, proving the efficiency of adaptive cluster selection and routing adjustments in preserving energy resources. Figure 6 presents a comparative analysis of retransmission rates under jamming conditions. In the unmitigated scenario, retransmissions remain persistently high due to continuous interference, leading to packet delivery failures and network congestion. This behavior severely impacts communication reliability, increasing latency and causing unnecessary power expenditure. When the proposed mitigation strategy is implemented, retransmission rates drop substantially as the algorithm promptly identifies affected nodes and reconfigures communication paths accordingly. This intelligent rerouting reduces failed transmission attempts and alleviates congestion, leading to a more stable and efficient network. Finally, Figure 7 illustrates the resilience of the LoRa network, measured by the recovery time required for the network to reestablish stable communication after a jamming attack. Without mitigation, recovery time is significantly prolonged due to the lack of an adaptive response mechanism, leaving affected nodes in a persistent state of communication failure. Conversely, with the mitigation algorithm, network recovery is expedited through proactive cluster reconfiguration and adaptive transmission adjustments. This rapid adaptation ensures that alternative routes are established efficiently, reducing downtime and maintaining network continuity. Collectively, these results underscore the effectiveness of the cluster-based mitigation approach in enhancing the robustness and energy efficiency of LoRa communication in jamming-prone environments. The findings emphasize the critical need for adaptive routing and network reconfiguration mechanisms to counteract the detrimental effects of interference, ensuring resilient long-range wireless communication in real-world IoT deployments.