-
Notifications
You must be signed in to change notification settings - Fork 0
Expand file tree
/
Copy pathReadme
More file actions
22 lines (19 loc) · 1.59 KB
/
Readme
File metadata and controls
22 lines (19 loc) · 1.59 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
This open-sourced project is for the paper "Multi-Traffic Resource Optimization for Real-Time Applications with 5G Configured Grant Scheduling",
which contains the main content of the "SMT solution", the heuristic approaches (CoU and Co1)
and the auxiliary function for completing the experimental process such as communication model and application model.
Important components are as follows:
1. DataGeneration: generating the test samples
1.1 application_parameter_x.py define application models
1.2 test_data_generation.py generate test samples
1.3 invoke.py generate the input sequences to the algorithms according to the output of "test_data_generation.py"
2. main.cpp: entrance of the whole project
3. Co1.cpp: algorithm Co1
4. CoU.cpp: algorithm CoU
5. SMT.cpp: algorithm SMT solutions
6. Small/LargeScaleAnalyzer.py analyze the collected results
7. SMTSolver.py & TF.py: python version of the SMT solutions [as a complementary material]
How to get started?
1. Use the scripts "application_parameter.py" and "test_data_generation.py" in "DataGeneration" to generate data samples (files are in the folder "application_info")
2. Use "invoke.py" to process the files in "application_info", obtain the input sequences that the program can read (in the name of "conf_x.cfg")
3. Run the program from main.cpp
4. Use "Small/LargeScaleAnalyzer.py" to analyze the results