Topology-Aware Grey Wolf Optimization for Energy-Efficient and Stable Routing in 6G Cyber Defense Networks

Abstract

6G cyber defense networks have many challenges that make it difficult to ensure safe and efficient routing. These challenges come from the topology that changes constantly, the very dense connectivity that exists, the strict requirements for latency, the limited resources for energy, and the continuous exposure to various cyber threats which include jamming, spoofing, malicious relays, and denial-of-service attacks. Traditional routing protocols such as AODV, DSR, OLSR, and DYMO can be used to establish communication routes, but they are often not very effective in environments that are highly dynamic and dangerous. This study examines the integration of conventional routing protocols with metaheuristic optimization techniques. The project's goal is to improve communication routing more dependable, robust, and energy-efficient. Simulations are done in OMNeT++ platform to record different transmission times and scenarios impacted by security issues in 6G networks. The proposed TA-GWO framework reaches a packet delivery ratio of 98.7%, a delay of 84 milliseconds, and a throughput of 589 kbps when OLSR is used during long transmission intervals. The results from the experiments show that this model provides optimal routing performance. Additionally, the suggested method reduces network lifetime to 472 seconds, normalized routing load to 0.34, routing overhead to 0.22, and energy consumption to 38.9 J. These results suggest that the TA-GWO-based 6G cybersecurity routing architecture provides significant improvements in energy efficiency, routing stability, and communication that can withstand threats when compared to existing metaheuristic techniques.