When a disaster disables terrestrial infrastructure, the command, control and situational-awareness traffic of the response teams loses its network. Fleets of unmanned aerial vehicles can restore connectivity within minutes, but most designs treat clustering, medium access, energy and failure recovery as separate problems, so a gain obtained in one layer is often lost in another once aircraft start to fail. This paper presents the Resilient Adaptive Clustering and Access Engine (RACE), a cross-layer control loop for multi-UAV emergency networks in the beyond-5G setting. At every control epoch, RACE places cluster heads with a greedy rule that maximizes the end-to-end availability offered to the fleet while accounting for residual energy, associates members with the head that serves them best without overloading any cluster and protects an availability-responsive share of capacity for mission-control traffic. The evaluation uses a matched-scenario Monte Carlo model with correlated mobility, air-to-air and air-to-ground link availability, co-channel interference, energy depletion, degraded propagation, prioritized traffic and injected aircraft losses, and it charges the signaling, failure-detection delay and reconfiguration transients of the control loop. RACE is compared with a flat multichannel access profile and with three clustering schemes from the literature, both as designed and with every scheme given the same control allocation. For dense fleets, RACE delivers the most traffic and the widest robust coverage and keeps mission-control delivery near 0.9 across all failure bursts. The protected share removes the long control-delay tail of any clustering rule, and with the same share the placement and association rules of RACE still add traffic, coverage and a shorter estimated delay tail, with a margin that grows as the network becomes more fragile. Ablations, a long-mission energy study and sensitivity sweeps confirm that these conclusions are stable.
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KAYA et al. (2026) studied this question.
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