Introduce a new simulation for Age of Information (AoI) cache management, focusing on varying TTL values and eviction strategies (LRU and Random Eviction). This includes:
- New Python script for event-driven cache simulations using .
- Experiments for "No Refresh" across multiple TTL configurations (, , ..., ) with:
- Hit rate and object age tracking (, , etc.).
- Visualizations (e.g., , ).
- Updated to describe experimental setup and configurations.
- Log export file () for simulation results.
- Refactor of with detailed strategy configurations and runtime notes.
### Reason
The commit enhances the project by enabling detailed experiments with configurable cache parameters, supporting analysis of cache efficiency and AoI under varying conditions. This provides a foundation for more sophisticated simulations and insights.
### Performance
- Runtime: ~4m 29s for .
Co-authored experiments introduce structured data files and visualizations, improving clarity for future iterations.
Signed-off-by: Tuan-Dat Tran <tuan-dat.tran@tudattr.dev>
