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- W4387042244 abstract "In this paper, we model a futuristic factory floor equipped with Automated Guided Vehicles (AGVs), cameras, and a Virtual Reality (VR) surveillance system; and connected to a 5G network for communication purposes. Motion planning of AGVs and VR applications is offloaded to an edge server for computational flexibility and reduced hardware on the factory floor. Decisions on the edge server are made using the video feed provided by the cameras in a controlled manner. Our objectives are to ensure factory floor safety and provide smooth VR experience in the surveillance room. Providing proper and timely allocation of network resources is of utmost importance to maintain the end-to-end delay necessary to achieve these objectives. We provide a statistical analysis to estimate the bandwidth required by a factory to satisfy the delay requirements 99.999 percent of the time. We formulate a nonconvex integer nonlinear problem aiming to minimize the safety and delay violations. To solve it, we propose a real-time network resource allocation algorithm that has linear time complexity in terms of the number of components connected to the wireless network. Our algorithm significantly outperforms existing solvers (genetic algorithm, surrogate optimizer) and meets the objectives using less bandwidth compared to existing methods." @default.
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- W4387042244 date "2023-01-01" @default.
- W4387042244 modified "2023-09-27" @default.
- W4387042244 title "Network Resource Allocation for Industry 4.0 with Delay and Safety Constraints" @default.
- W4387042244 doi "https://doi.org/10.1109/tccn.2023.3319529" @default.
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