Reinforcement R-learning model for time scheduling of on-demand fog placement
On the fly deployment of fog nodes near users provides the flexibility of pushing services anywhere and whenever needed. Nevertheless, taking a real-life scenario, the cloud might limit the number of fogs to place for minimizing the complexity of monitoring a large number of fogs and cost for volunt...
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| Format: | article |
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2020
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| Online Access: | http://hdl.handle.net/10725/12676 https://doi.org/10.1007/s11227-019-03032-z http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php https://link.springer.com/article/10.1007/s11227-019-03032-z |
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