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- W4312423360 abstract "As being clear that the joint optimization of caching, computing, and communication (3C) can significantly improve vehicular network performance, this paper investigates the quality-aware 3C optimization for video delivery in vehicular networks. By incorporating the quality-awareness into 3C models, we formulate both the quality-aware joint 3C optimization problem and the quality-aware joint computing and communication (2C) optimization problem with predetermined caching. By observing that the proposed 2C and 3C problems can be interpreted as submodular maximization problems with constraints, we propose a solution methodology using the submodularity and knapsack interpretation. Based on the proposed methodology, we then propose efficient solution approaches assuming batch input and streaming input, respectively. Complexity of the proposed solution approaches is analyzed. In addition, extensive simulations are conducted to evaluate the proposed solution approaches. Results show that our proposed approaches can outperform the reference schemes and improve the video delivery of vehicular networks." @default.
- W4312423360 created "2023-01-04" @default.
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- W4312423360 date "2023-04-01" @default.
- W4312423360 modified "2023-09-30" @default.
- W4312423360 title "Quality-Aware Joint Caching, Computing and Communication Optimization for Video Delivery in Vehicular Networks" @default.
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- W4312423360 doi "https://doi.org/10.1109/tvt.2022.3226764" @default.
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