Energy Efficient Trust-Aware Aqua Raptor Optimization Algorithm (TA-ARO) for Secure Routing in VANETs

Vehicular ad hoc networks (VANETs) play a vital role in enabling intelligent transportation systems; however, their high
dynamic topology and limited resources are significant challenges to energy-efficient and secure communication. To
address these issues, an energy-efficient and trust-aware clustering and routing framework, termed FCKOA-TA-AROA
has been proposed and it employs Optimized Fuzzy C-Means (OFCM) clustering to form stable vehicle groups, while
the Modified Kookaburra Optimization Algorithm (MKOA) selects optimal cluster heads based on energy and mobility characteristics. Secure and efficient routing is achieved using a Trust-Aware Aqua Raptor Optimization Algorithm
(TA-AROA) by incorporating trust evaluation and energy-aware path selection. In addition, homomorphic encryption is
utilized to protect trust-related information during data transmission. Simulation results indicate that the proposed framework substantially outperforms the existing routing schemes in terms of energy efficiency, security, and communication
reliability by making it a promising solution for secure VANET communications. Specifically, the proposed algorithm
achieves superior performance compared to the Graph-Based Trust-Enabled Routing (GBTR), Bionic Remora Optimization Algorithm (BROA), Adaptive Binary Bird Swarm Optimization integrated with Adaptive Golden Eagle Optimization
(ABBSOA-AGEOA), and Falcon Optimization Algorithm-based Energy Efficient Communication Protocol for Clusterbased Routing (FOA-EECPCR). The simulation results demonstrate that the proposed method attains the throughput of
99 Kbps, packet delivery ratio of 88%, and energy consumption of 42 J, outperforming all compared schemes across all
key metrics.