This work investigates a scenario in which a swarm of unmanned aerial vehicles serves a set of sensor nodes, adopting the time division multiple access scheme. To ensure fair resource allocation and derive an optimal scheduling plan, a combinatorial problem subject to binary constraints is formulated. Thanks to its inherent capabilities, quantum annealing can be used to solve this class of optimization problems. As a result, the original problem is mapped to quadratic unconstrained binary optimization form, in order to be processed by a quantum processing unit. Since state-of-the-art quantum annealers have a limited number of quantum bits (qubits) and limited inter-qubit connectivity, the scheduling plan is obtained by employing a hybrid quantum-classical approach. Then, a comparison with two classical solvers is performed in terms of acquired data, objective function values, and execution time.

Hybrid quantum-classical scheduling optimization in UAV-enabled IoT networks / Vista, F; Iacovelli, Giovanni; Grieco, La. - In: QUANTUM INFORMATION PROCESSING. - ISSN 1570-0755. - 22:1(2023). [10.1007/s11128-022-03805-1]

Hybrid quantum-classical scheduling optimization in UAV-enabled IoT networks

Vista, F;Giovanni Iacovelli;Grieco, LA
2023-01-01

Abstract

This work investigates a scenario in which a swarm of unmanned aerial vehicles serves a set of sensor nodes, adopting the time division multiple access scheme. To ensure fair resource allocation and derive an optimal scheduling plan, a combinatorial problem subject to binary constraints is formulated. Thanks to its inherent capabilities, quantum annealing can be used to solve this class of optimization problems. As a result, the original problem is mapped to quadratic unconstrained binary optimization form, in order to be processed by a quantum processing unit. Since state-of-the-art quantum annealers have a limited number of quantum bits (qubits) and limited inter-qubit connectivity, the scheduling plan is obtained by employing a hybrid quantum-classical approach. Then, a comparison with two classical solvers is performed in terms of acquired data, objective function values, and execution time.
2023
Hybrid quantum-classical scheduling optimization in UAV-enabled IoT networks / Vista, F; Iacovelli, Giovanni; Grieco, La. - In: QUANTUM INFORMATION PROCESSING. - ISSN 1570-0755. - 22:1(2023). [10.1007/s11128-022-03805-1]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/249502
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