davidtw0320 / Resources-Allocation-in-The-Edge-Computing-Environment-Using-Reinforcement-Learning

Simulated the scenario between edge servers and users with a clear graphic interface. Also, implemented the continuous control with Deep Deterministic Policy Gradient (DDPG) to determine the resources allocation (offload targets, computational resources, migration bandwidth) in the edge servers

davidtw0320
davidtw0320
Date Created 2020-01-15 (5 years ago)
Commits 24 (last one 4 years ago)
Stargazers 350 (0 this week)
Watchers 3 (0 this week)
Forks 103
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RepositoryStats indexes 637,312 repositories, of these davidtw0320/Resources-Allocation-in-The-Edge-Computing-Environment-Using-Reinforcement-Learning is ranked #125,014 (80th percentile) for total stargazers, and #419,770 for total watchers. Github reports the primary language for this repository as Python, for repositories using this language it is ranked #21,751/130,523.

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davidtw0320/Resources-Allocation-in-The-Edge-Computing-Environment-Using-Reinforcement-Learning has 1 open pull request on Github, 0 pull requests have been merged over the lifetime of the repository.

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updated: 2025-04-03 @ 12:52pm, id: 234117993 / R_kgDODfRbaQ