2024-11-13 12:00:18 +01:00
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# Age Caching Simulation
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2024-11-08 21:38:45 +01:00
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Client -> TTL Cache -> Database
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2024-11-13 12:00:18 +01:00
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Capacity C (C = n (example: 100))
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2024-11-08 21:38:45 +01:00
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TTL increases on cache hit
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Age of information / Age of the entry in the cache
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Database has latest object, cache entry may be old (we don't know)
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Age of entry should have low age of information
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Update function from cache to refresh based on mu (refresh rate)
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Loss function based on TTL and age in cache called beta(i)
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Event based simulation
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lambda(i) is zipf distribution describing the rate the client requests the object "i"
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Inter arrival time of each object => exponential
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2024-11-13 12:00:18 +01:00
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Hit rate and the average age of the object based on TTL
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