A delay-tolerant network architecture for edge computing with applications in narrow band internet of things

Ethical ref# 204520231/2023/3

The research involved designing and testing a narrow-band IoT Delay-Tolerant Network (NB-IoTDTN) to enhance resilience against Distributed Denial-of-Service (DDoS) attacks. The data consisted of simulated network traffic and performance metrics collected from a testbed environment, which was built using Raspberry Pi nodes connected in a K3s edge cluster. The nodes were configured to run containerized environments using Cilium CNI for secure and observable networking.

• Type of Data: The collected data included network performance metrics such as latency, jitter, packet loss, throughput, and system logs detailing DDoS attack attempts and mitigations. This data was captured using monitoring tools like Grafana and Prometheus.
• Data Collection: Network traffic, including normal and DDoS-attack scenarios, was simulated using UERANSIM and Open5GS to replicate the interaction between NB-IoT devices and the core network. Data was collected continuously during these simulations to monitor the network's ability to maintain performance under attack conditions.
• Usage of Data: The data was used to evaluate the effectiveness of the NB-IoTDTN architecture in mitigating the impact of DDoS attacks. Key metrics such as system uptime, data packet delivery rates, and service continuity under attack conditions were analyzed.
• Outcome: The findings from this data indicated that the NB-IoTDTN architecture significantly improved the network's resilience by maintaining service continuity during DDoS scenarios. The lightweight security protocols designed for resource-constrained devices showed effectiveness with minimal computational overhead. The data demonstrated improved performance in maintaining network functionality even under high-traffic conditions caused by DDoS attacks.