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

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 formulate...

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Bibliographic Details
Published in:Quantum information processing Vol. 22; no. 1
Main Authors: Vista, Francesco, Iacovelli, Giovanni, Grieco, Luigi Alfredo
Format: Journal Article
Language:English
Published: New York Springer US 18.01.2023
Subjects:
Data Structures and Information Theory
Mathematical Physics
Physics
Physics and Astronomy
Quantum Computing
Quantum Information Technology
Quantum Physics
Spintronics
Quantum computing
Internet of drones
IoT networks
Quantum optimization
Quantum annealer
ISSN:1573-1332, 1573-1332
Online Access:Get full text
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Summary: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.
ISSN:1573-1332
1573-1332
DOI:10.1007/s11128-022-03805-1