Traffic Scheduling for Time Sensitive Networks
Run the program schedulegenwithdeadline.py
Overview of the approach
Traffic_Scheduling-GeneticAlgoApproach.pdf
A brief description of code structure
Scheduling being an NPHard problem many methods have been applied. Genetic Algorithms, Metaheuristics all have found its advantages. I found it easier with Genetic algorithms as finally all you do is try creating different populations and check the fitness (whether rules or constraints are met) more relatable. This is the approach in Genetic.
Inline image
An initial flow sequence is provided by JSON for 10 Links
The Traffic Model is here. The flows (4) are described in code here
Main method
Include calls to prepare initial polpulation
Multiple Iterations involved to find the best
Perform mutations (rearrangements) and check fitness
Identifying the best schedule by checking makespan. The Shortest Makespan is considered best
Here is where we check deadline. Main rule here is deadline
