age_cache_simulation/export.csv at 6e8a742705bc1f47fff9399a7a6bc0675a09cb1c

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Tuan-Dat Tran 6e8a742705 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>

2024-11-27 16:31:46 +01:00

4.0 KiB

Raw Blame History

1		access_count	hits	misses	mu	lambda	hit_rate
2	1	1053	968	85	2.7571868901824006	1	68.51
3	2	362	248	114	7.502069037353548	3	90.93
4	3	1047	952	95	3.526951261967702	1	98.1
5	4	1107	1086	21	1.2188436978830846	1	78.25
6	5	538	421	117	6.80925066316451	2	92.7
7	6	1124	1042	82	2.5939961146634403	1	55.61
8	7	205	114	91	9.464127259176228	5	85.77
9	8	1075	922	153	9.585357193023286	1	86.16
10	9	1084	934	150	9.233779511984036	1	89.6
11	10	1106	991	115	4.331428302298999	1	95.9
12	11	536	514	22	1.1391095487598069	2	85.53
13	12	1009	863	146	9.354867063289529	1	88.57
14	13	1076	953	123	4.8536573348558285	1	86.6
15	14	1097	950	147	9.699893371393026	1	76.43
16	15	543	415	128	9.672579793803276	2	76.4
17	16	517	395	122	8.677085099206241	2	90.62
18	17	1087	985	102	3.6500400286262713	1	89.63
19	18	1090	977	113	4.465879557417328	1	72.41
20	19	377	273	104	8.660230043651712	3	90.34
21	20	1128	1019	109	3.852298046406499	1	93.49
22	21	1137	1063	74	2.5254347201748324	1	87.43
23	22	1042	911	131	6.0112113621251515	1	86.9
24	23	1137	988	149	9.425392967447028	1	77.88
25	24	547	426	121	7.264268170074757	2	88.12
26	25	1027	905	122	6.1305505308042845	1	95.64
27	26	1054	1008	46	1.8745884439369167	1	87.89
28	27	1140	1002	138	6.535065040292528	1	53.92
29	28	204	110	94	9.91048465093837	5	94.17
30	29	1080	1017	63	2.260756137128716	1	89.02
31	30	1138	1013	125	5.664966871273631	1	86.26
32	31	1048	904	144	8.8963576473516	1	64.55
33	32	268	173	95	7.66691755978784	4	86.83
34	33	1071	930	141	7.273141668957412	1	62.7
35	34	252	158	94	7.322356755883983	4	90.78
36	35	1085	985	100	4.2354203609777965	1	91.22
37	36	1059	966	93	3.64232659838044	1	87.16
38	37	1067	930	137	8.284250399306622	1	69.41
39	38	353	245	108	8.291020552112627	3	43.75
40	39	128	56	72	8.803650867220934	8	86.82
41	40	1077	935	142	9.219164973008242	1	65.84
42	41	281	185	96	5.60208158974844	4	63.97
43	42	247	158	89	5.513646652184796	4	78.62
44	43	594	467	127	8.184656610700976	2	88.03
45	44	1145	1008	137	6.849675376999887	1	88.24
46	45	1131	998	133	7.31770189531933	1	86.75
47	46	1087	943	144	8.16213402492491	1	46.15
48	47	130	60	70	9.010048076358096	10	90.53
49	48	1067	966	101	4.041956411663822	1	89.66
50	49	1102	988	114	4.380246573759496	1	95.39
51	50	1106	1055	51	1.845837458567821	1	57.4
52	51	223	128	95	6.204521268965566	5	89.08
53	52	119	106	13	1.3234804641706788	9	88.1
54	53	1101	970	131	5.190382163192141	1	87.69
55	54	1064	933	131	5.883801712368189	1	89.78
56	55	1067	958	109	3.5788712691545594	1	88.12
57	56	1094	964	130	6.317499345121097	1	97.01
58	57	1038	1007	31	1.2745022494514449	1	67.12
59	58	73	49	24	1.3361336987429298	17	77.12
60	59	555	428	127	8.403405045936925	2	89.38
61	60	1073	959	114	4.241715772701366	1	36.0
62	61	50	18	32	2.143544613866963	26	87.54
63	62	1027	899	128	5.700189340493239	1	86.95
64	63	1050	913	137	7.9299419778874976	1	85.48
65	64	544	465	79	2.9423892474715885	2	88.14
66	65	1071	944	127	6.606014282371002	1	73.28
67	66	116	85	31	1.768127184943912	10	96.89
68	67	1094	1060	34	1.4651354905174694	1	20.0
69	68	10	2	8	5.782191684113332	69	88.47
70	69	1110	982	128	5.865716094490959	1	87.52
71	70	1026	898	128	6.736869113483859	1	78.7
72	71	554	436	118	7.534822003503954	2	87.38
73	72	1125	983	142	9.782668715162812	1	88.33
74	73	1088	961	127	5.646703134710758	1	90.57
75	74	1082	980	102	3.9066082564712135	1	71.39
76	75	346	247	99	8.156675752918332	3	82.14
77	76	515	423	92	3.437490261358668	2	80.9
78	77	602	487	115	4.950742786350725	2	89.05
79	78	347	309	38	1.7061074320803935	3	69.09
80	79	55	38	17	1.2281566907391177	15	85.73
81	80	1093	937	156	9.663835732101326	1	85.45
82	81	1010	863	147	8.523821084609853	1	55.03
83	82	189	104	85	7.263767854843282	5	82.06
84	83	602	494	108	4.680576499728429	2	92.34
85	84	1044	964	80	2.559648880637612	1	93.88
86	85	1078	1012	66	2.4079333840397745	1	83.67
87	86	539	451	88	3.252186083481358	2	87.74
88	87	1028	902	126	5.943039982355084	1	77.05
89	88	549	423	126	7.431363304300561	2	87.84
90	89	1069	939	130	6.941776390459581	1	91.73
91	90	1113	1021	92	3.5194050725134858	1	76.14
92	91	528	402	126	9.593787525968747	2	76.1
93	92	544	414	130	7.641072250261916	2	70.49
94	93	349	246	103	5.989186472602606	3	88.21
95	94	1077	950	127	6.5054867161091705	1	79.77
96	95	519	414	105	4.776400561850109	2	90.72
97	96	1035	939	96	3.229578905510417	1	90.06
98	97	1066	960	106	4.2037541078613545	1	27.59
99	98	29	8	21	7.820614994179322	37	92.96
100	99	270	251	19	1.1295413976678028	4	88.95

4.0 KiB Raw Blame History

4.0 KiB

Raw Blame History