feat: add cache simulation with experiments for TTL and eviction strategies
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>
This commit is contained in:
100
experiments/No_Refresh_0_5s_ttl/details.csv
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100
experiments/No_Refresh_0_5s_ttl/details.csv
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,access_count,hits,misses,mu,lambda,hit_rate
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1,664,224,440,0,1,10.38
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2,212,22,190,0,3,32.39
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3,673,218,455,0,1,34.6
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4,711,246,465,0,1,19.13
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5,345,66,279,0,2,31.74
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6,649,206,443,0,1,10.22
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7,137,14,123,0,5,32.45
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8,681,221,460,0,1,34.4
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9,689,237,452,0,1,34.18
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10,667,228,439,0,1,21.95
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11,328,72,256,0,2,34.97
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12,692,242,450,0,1,32.21
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13,683,220,463,0,1,33.62
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14,696,234,462,0,1,20.35
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15,344,70,274,0,2,18.4
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16,326,60,266,0,2,29.9
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17,689,206,483,0,1,32.85
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18,691,227,464,0,1,11.87
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19,219,26,193,0,3,34.84
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20,732,255,477,0,1,35.05
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21,739,259,480,0,1,34.55
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22,683,236,447,0,1,35.22
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23,670,236,434,0,1,19.94
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24,331,66,265,0,2,34.67
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25,724,251,473,0,1,32.08
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26,692,222,470,0,1,34.18
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27,705,241,464,0,1,8.76
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28,137,12,125,0,5,34.23
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29,672,230,442,0,1,31.7
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30,694,220,474,0,1,33.09
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31,674,223,451,0,1,9.03
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32,144,13,131,0,4,34.63
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33,670,232,438,0,1,7.09
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34,141,10,131,0,4,32.78
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35,659,216,443,0,1,32.27
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36,691,223,468,0,1,36.91
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37,737,272,465,0,1,14.16
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38,219,31,188,0,3,5.0
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39,100,5,95,0,8,32.77
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40,714,234,480,0,1,12.5
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41,184,23,161,0,4,7.45
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42,161,12,149,0,4,21.55
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43,362,78,284,0,2,32.61
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44,696,227,469,0,1,29.98
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45,627,188,439,0,1,32.56
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46,648,211,437,0,1,1.89
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47,53,1,52,0,10,31.51
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48,676,213,463,0,1,31.35
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49,638,200,438,0,1,32.69
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50,673,220,453,0,1,12.5
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51,128,16,112,0,5,3.53
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52,85,3,82,0,9,33.33
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53,747,249,498,0,1,33.0
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54,700,231,469,0,1,35.08
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55,687,241,446,0,1,37.5
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56,720,270,450,0,1,31.3
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57,690,216,474,0,1,0.0
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58,40,0,40,0,17,19.18
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59,318,61,257,0,2,31.31
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60,674,211,463,0,1,13.04
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61,23,3,20,0,26,35.22
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62,724,255,469,0,1,32.32
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63,628,203,425,0,1,24.93
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64,345,86,259,0,2,35.1
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65,681,239,442,0,1,4.11
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66,73,3,70,0,10,33.79
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67,651,220,431,0,1,0.0
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68,10,0,10,0,69,33.02
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69,636,210,426,0,1,32.77
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70,656,215,441,0,1,22.58
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71,372,84,288,0,2,33.48
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72,678,227,451,0,1,33.7
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73,638,215,423,0,1,33.28
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74,685,228,457,0,1,10.45
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75,201,21,180,0,3,20.35
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76,344,70,274,0,2,21.16
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77,345,73,272,0,2,17.24
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78,261,45,216,0,3,4.26
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79,47,2,45,0,15,33.79
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80,660,223,437,0,1,30.28
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81,634,192,442,0,1,5.84
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82,137,8,129,0,5,18.45
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83,309,57,252,0,2,34.11
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84,686,234,452,0,1,32.99
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85,682,225,457,0,1,19.25
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86,322,62,260,0,2,32.99
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87,676,223,453,0,1,20.92
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88,325,68,257,0,2,35.27
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89,689,243,446,0,1,32.95
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90,695,229,466,0,1,21.91
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91,324,71,253,0,2,20.47
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92,337,69,268,0,2,13.96
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93,222,31,191,0,3,31.78
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94,686,218,468,0,1,19.94
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95,351,70,281,0,2,33.89
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96,717,243,474,0,1,32.53
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97,664,216,448,0,1,0.0
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98,23,0,23,0,37,11.6
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99,181,21,160,0,4,22.85
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experiments/No_Refresh_0_5s_ttl/hit_age.csv
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experiments/No_Refresh_0_5s_ttl/hit_age.csv
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obj_id,hit_rate,avg_age
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1,0.3373493975903614,0.25892857142857145
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2,0.10377358490566038,0.36363636363636365
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3,0.32392273402674593,0.24311926605504589
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4,0.3459915611814346,0.25609756097560976
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5,0.19130434782608696,0.24242424242424243
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6,0.31741140215716485,0.24757281553398058
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7,0.10218978102189781,0.21428571428571427
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8,0.3245227606461087,0.2579185520361991
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9,0.3439767779390421,0.23628691983122363
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10,0.34182908545727136,0.2236842105263158
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11,0.21951219512195122,0.2361111111111111
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12,0.34971098265895956,0.30578512396694213
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13,0.32210834553440704,0.22727272727272727
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14,0.33620689655172414,0.2692307692307692
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15,0.20348837209302326,0.2
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16,0.18404907975460122,0.2
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17,0.29898403483309144,0.2524271844660194
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18,0.32850940665701883,0.24669603524229075
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19,0.1187214611872146,0.2692307692307692
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20,0.3483606557377049,0.25882352941176473
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21,0.35047361299052776,0.21235521235521235
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22,0.34553440702781846,0.288135593220339
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23,0.3522388059701492,0.19915254237288135
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27,0.34184397163120567,0.23651452282157676
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28,0.08759124087591241,0.16666666666666666
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29,0.34226190476190477,0.24782608695652175
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33,0.34626865671641793,0.24568965517241378
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34,0.07092198581560284,0.3
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36,0.3227206946454414,0.29596412556053814
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37,0.36906377204884666,0.22058823529411764
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38,0.1415525114155251,0.3870967741935484
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39,0.05,0.2
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40,0.3277310924369748,0.27350427350427353
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41,0.125,0.30434782608695654
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42,0.07453416149068323,0.25
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43,0.2154696132596685,0.32051282051282054
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46,0.3256172839506173,0.27014218009478674
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47,0.018867924528301886,0.0
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48,0.3150887573964497,0.23943661971830985
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49,0.31347962382445144,0.27
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50,0.32689450222882616,0.22727272727272727
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51,0.125,0.25
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52,0.03529411764705882,0.3333333333333333
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54,0.33,0.24675324675324675
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57,0.3130434782608696,0.2638888888888889
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58,0.0,0.0
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68,0.0,0.0
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69,0.330188679245283,0.32857142857142857
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82,0.058394160583941604,0.125
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84,0.34110787172011664,0.2905982905982906
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86,0.19254658385093168,0.3064516129032258
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87,0.32988165680473375,0.20179372197309417
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88,0.20923076923076922,0.25
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89,0.35268505079825835,0.22633744855967078
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93,0.13963963963963963,0.25806451612903225
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94,0.3177842565597668,0.2889908256880734
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95,0.19943019943019943,0.3142857142857143
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96,0.3389121338912134,0.2139917695473251
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98,0.0,0.0
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99,0.11602209944751381,0.3333333333333333
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100,0.228486646884273,0.24675324675324675
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experiments/No_Refresh_0_5s_ttl/lambda_distribution.pdf
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experiments/No_Refresh_0_5s_ttl/lambda_distribution.pdf
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experiments/No_Refresh_0_5s_ttl/objects_in_cache_over_time.pdf
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experiments/No_Refresh_0_5s_ttl/objects_in_cache_over_time.pdf
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experiments/No_Refresh_0_5s_ttl/overall_hit_age.csv
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experiments/No_Refresh_0_5s_ttl/overall_hit_age.csv
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,hit_rate,avg_age
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count,100.0,100.0
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mean,0.24997190226308422,0.24085664637735987
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std,0.10967384888958667,0.07537398148292249
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min,0.0,0.0
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25%,0.1843617845017571,0.21978900255754474
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50%,0.3172071420007726,0.25
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75%,0.3351579188281965,0.2796906689079315
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max,0.375,0.3870967741935484
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