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We consider a real-world problem of military intelligence unit equipped with identical unmanned aerial vehicles producing real-time imagery and responsible for heterogeneous regions (with requests of real-time jobs) required to be under nonstop surveillance. Under certain assumptions these real-time systems can be treated as queueing networks.The use of the system involving unmanned aerial vehicles relies on the principle of availability, namely on its ability to process the maximal portion of real-time tasks. We show that even very large number of vehicles does not guarantee the maximal system availability without proper choice of routing probabilities. We compute analytically (for exponentially distributed service and maintenance times) and via simulation using Cross-Entropy method (for generally distributed service times) optimal routing probabilities which maximize system availability. Notations and abbreviationsCE Cross Entropy CMC Crude Monte Carlo RTS Real-Time System UAV Unmanned Aerial Vehicle N Number of identical UAVs/servers r Number of heterogeneous regions/channels r kNumber of real-time tasks/jobs in k-th region at any instant (r k ≥ 1) λThe maintenance rate (exponential distribution)

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