Design of an Efficient Fan-Shaped Clustered Trust-Based Routing Model with QoS & Security-Aware Side-Chaining for IoV Deployments

Abstract

The rapid expansion of Internet of Vehicles (IoV) deployments has necessitated the creation of efficient and secure routing models to manage the massive data traffic generated by interconnected devices & vehicles. For IoV deployments, we propose a novel fan-shaped trust-based routing model with Quality of Service (QoS) and security-aware side-chaining. Our method employs temporal levels of delay, throughput, Packet Delivery Ratio (PDR), and energy consumption to determine optimal routing paths, thereby ensuring efficient data transmissions. We employ the Bacterial Foraging Optimizer (BFO) algorithm to manage side-chains within the network, which dynamically adjusts side-chain configurations to optimize system performance. The technique of fan-shaped clustering is used to group nodes into efficient clusters, allowing for more efficient communication and resource utilization sets. Extensive experimentation and performance analysis are utilized to evaluate the proposed model. Existing blockchain-based security models have been significantly improved by our findings. Our model achieves a remarkable 9.5% reduction in delay, a 10.5% improvement in throughput, a 2.9% improvement in PDR, and a 4.5% reduction in energy consumption compared to alternative approaches. In addition, we evaluate the model's resistance to Sybil, Masquerading, and Flooding attacks, which are prevalent security threats for IoV deployments. Even under these attack scenarios, our model provides consistently higher QoS levels compared to existing solutions, ensuring uninterrupted and reliable data transmissions. In IoV deployments, the proposed routing model and side-chaining management approach have numerous applications and use-cases like Smart cities, industrial automation, healthcare systems, transportation networks, and environmental monitoring.