Slime-Mould-Inspired Resilient Topology Construction Algorithm for UVC/RF Heterogeneous UAV Swarms

Addressing the demand for highly reliable communication in unmanned aerial vehicle (UAV) swarms operating in extreme environments, this paper proposes a slime mold-inspired resilient topology construction algorithm for UVC/RF heterogeneous UAV networks, termed UVC-SMA. To overcome the limitations of conventional bio-inspired algorithms in UVC/RF heterogeneous network scenarios—including insufficient heterogeneous modeling, weak dynamic adaptability, long passive repair latency, and inadequate single-path reliability—the proposed algorithm integrates three core mechanisms. First, it constructs an energy-aware joint cost model for heterogeneous links and uses an exponential energy penalty factor to suppress energy hotspots in the network. Second, it designs a network state-driven parameter adaptation mechanism to dynamically balance the capabilities of global exploration and local exploitation. Third, it establishes an active key node protection framework with a hybrid degree-betweenness weighting, which shifts resilience optimization from post-failure reconfiguration to proactive pre-failure reinforcement and develops a K-shortest multipath routing method (K = 3) based on the reciprocal of conductivity to achieve millisecond-level path switching. The simulation results show that compared with the traditional slime mould algorithm (SMA), the UVC-SMA improves network robustness from 0.75 to 1.00, increases average residual energy by 19.5%, and reduces average node degree by 16.8%. The algorithm adopts a distributed architecture with a single iteration complexity of O(n2), which theoretically supports low-cost on-board deployment and is applicable to UAV swarm communication in highly dynamic and highly adversarial extreme environments. The reported robustness improvement from 0.75 to 1.00 is obtained under the baseline 50-node simulation configuration and cannot be guaranteed under arbitrary network or mobility conditions.