6e8a742705
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>