Age Caching Simulation

Client -> TTL Cache -> Database Capacity C (C = n (example: 100))

TTL increases on cache hit Age of information / Age of the entry in the cache Database has latest object, cache entry may be old (we don't know)

Age of entry should have low age of information

Update function from cache to refresh based on mu (refresh rate)

Loss function based on TTL and age in cache called beta(i)

Event based simulation

lambda(i) is zipf distribution describing the rate the client requests the object "i"

Inter arrival time of each object => exponential

Hit rate and the average age of the object based on TTL