Low-AoI data collection in integrated UAV-UGV-assisted IoT systems based on deep reinforcement learning

Computer Networks, Journal Year: 2025, Volume and Issue: unknown, P. 111044 - 111044

Published: Jan. 1, 2025

Language: Английский

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Joint resource scheduling and flight path planning of UAV-assisted IoTs in response to emergencies

Computer Networks, Journal Year: 2024, Volume and Issue: 253, P. 110731 - 110731

Published: Aug. 23, 2024

Language: Английский

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Window Method: A Plug-in-Style Large-Scale Handling Technique for Evolutionary Algorithm

Published: Jan. 1, 2025

Large-scale optimization constitutes a pivotal characteristic of numerous real-world problems, where large-scale evolutionary algorithms emerge as potent instrument for addressing such intricacies. However, existing methods are typically tailored to address only particular class problems and lack the versatility be readily adapted other or generalized across diverse problem domains. To issue above, this paper proposes window method, simple yet effective enhancement that can seamlessly integrated into low-dimensional bolster their performance in optimization. Specifically, method involves grouping subset randomly selected dimensions during each iteration, restricting population's evolution within window. Furthermore, effectiveness is analyzed, improved based on insights gained, including isometric segmentation individual-level length neural network-guided element. Extensive experiments single-objective, multi-objective, constrained discrete test with attributes demonstrate proposed significantly mitigates curse dimensionality enhances EAs settings.

Language: Английский

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Constrained Multiobjective Optimization for UAV-assisted Mobile Edge Computing in Smart Agriculture: Minimizing Delay and Energy Consumption

IEEE Transactions on Sustainable Computing, Journal Year: 2024, Volume and Issue: 9(6), P. 948 - 957

Published: May 17, 2024

With the development of technology, unmanned aerial vehicles (UAVs) and Internet Things devices are widely used in smart agriculture, resulting significant energy consumption. In this paper, optimization problem for UAV-assisted mobile computing agriculture is modeled as a constrained multi-objective problem. By jointly optimizing deployment position UAVs, offloading location tasks, transmit power devices, resource allocation two objectives (total delay consumption) minimized simultaneously. view complex constraints, multiobjective algorithm named JO-DPTS proposed. The adopts dual-population two-stage approach to improve population convergence diversity. simulation results substantiate that exhibits superior performance compared other three state-of-the-art evolutionary algorithms.

Language: Английский

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The Meta-Heuristic routing method by integrating index parameters to optimize energy consumption and real execution time using FANET

Computer Networks, Journal Year: 2024, Volume and Issue: unknown, P. 110869 - 110869

Published: Oct. 1, 2024

Language: Английский

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Enhancing UAV-based edge computing: a study on nonhovering operations and two-stage optimization strategies

Applied Intelligence, Journal Year: 2024, Volume and Issue: 54(21), P. 10780 - 10801

Published: Aug. 27, 2024

Language: Английский

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