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Drone Swarm as Mobile Relaying System: A Hybrid Optimization Approach

Giovanni Iacovelli, Luigi Alfredo Grieco

2021IEEE Transactions on Vehicular Technology18 citationsDOI

Abstract

Drones are increasingly employed in several application domains thanks to their inherent versatility. This work envisions a scenario in which a swarm of Unmanned Aerial Vehicles (UAVs) enables the communication between a set of Sensor Nodes (SNs) and a control center. Considering a general fading channel model, a Mixed-Integer Non-Linear Programming (MINLP) problem is formulated to maximize the overall amount of relayed data by jointly optimizing trajectory and scheduling plan of each drone. Combining convex optimization and Ant Colony Optimization (ACO) algorithm, a quasi-optimal solution is obtained. Finally, numerical results demonstrate the effectiveness of the proposed solution in different parameter configurations and with respect to a benchmark algorithm.

Topics & Concepts

DroneMathematical optimizationBenchmark (surveying)Computer scienceAnt colony optimization algorithmsFadingScheduling (production processes)Swarm behaviourOptimization problemInteger programmingChannel (broadcasting)EngineeringMathematicsComputer networkBiologyGeodesyGeographyGeneticsUAV Applications and OptimizationDistributed Control Multi-Agent SystemsVehicle Routing Optimization Methods
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