673302a6b2
- Added `aoi_cache_experiment_eval.ipynb`: A Jupyter notebook evaluating cache performance based on TTL (Time-to-Live) with hit rate and average age analysis. It includes visualizations and experiment results. - Removed the unused `experiment_name` variable in `aoi_cache_simulation.ipynb`. - Added `experiments/hr_and_age_vs_ttl.png`: A plot visualizing the relationship between hit rate and TTL, complementing the cache evaluation experiments. ### Reason The new notebook enhances experiment evaluation by providing a detailed analysis of cache behavior over different TTL values. The image file adds a visualization of the results. The removal of the `experiment_name` variable cleans up the simulation code, as it was not being utilized. Signed-off-by: Tuan-Dat Tran <tuan-dat.tran@tudattr.dev>
Experiments: No Refresh with variable TTL
Explanation for files in each experiment:
details.csv: Access Count, Hit, Miss, Mu, Lambda and Hit Rate for each objecthit_age.csv: Shows hit rate/average age at time of request for each object.lambda_distribution.pdf: Lambda Distribution across all objects/discrete values of the Zipf distributionobjects_in_cache_over_time.pdf: Amount of cache entries at given time.overall_hit_age.csv: Cumulative description ofhit_age.csv
Length of simulation doesn't change much since we're not touching the request
rate across the simulations.
Break condition for the simulation is when the each database object has been
requested at least ACCESS_COUNT_LIMIT (i.e. 10) times.