Benchmarking Trust Path Traversal in Swarm Drones: DID + GraphDB vs. RDB Approaches

In mission-critical swarm drone operations, verifying the trustworthiness of command and control flows is essential for resilience and security. While traditional Public Key Infrastructure (PKI) and relational database (RDB) systems have served as the foundation for authentication and trust validation, they often face performance bottlenecks when applied to dynamic, large-scale swarm environments. This paper presents a benchmark-driven evaluation of decentralized identity (DID)-based trust path traversal implemented using a property graph model (GraphDB), comparing it against two conventional models: (A) PKI + RDB and (B) DID + RDB. Using a simulated swarm of 1,000 drone nodes and multihop delegation chains (depths 2 to 8), we measure latency (P50/P95/P99) and throughput (TPS) across each scenario. Our results show that the GraphDB-based implementation (C) consistently outperforms RDB-based models in both latency and throughput. Specifically, scenario C achieves up to 40% lower P95 latency and $1.5 \times$ higher throughput on average compared to RDB-based counterparts. These improvements become more prominent as delegation depth increases, confirming the scalability advantage of GraphDB for trust verification workloads. This study demonstrates that property graph traversal using Cypher queries is a practical and high-performance alternative for Web-of-Trust style validation in swarm drone networks. We conclude by recommending GraphDB as a viable trust framework for real-time, mission-critical drone operations, particularly in scenarios involving node compromise, revocation, and redelegation.