Web Cache Replacement Method Based on Access Density
A technology for access density and cache replacement, applied in memory systems, instruments, electrical digital data processing, etc., can solve problems such as low cache hit rate and low cache byte hit rate
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specific Embodiment approach 1
[0032] Specific embodiment one: the access density-based web cache replacement method of this embodiment is implemented in the following steps:
[0033] (1) Whether the cache object already exists in the cache pool, otherwise jump into step (2), if yes, jump into step (5);
[0034] (2) Whether the buffer pool is full, jump to step (3) if it is full, and jump to step (4) if not;
[0035] (3) Delete the cache object with the lowest access density value, add the new cache object to the cache pool, initialize the access density, last access location, access frequency, and average access interval of the cache object, and jump into step (10);
[0036] (4) Add the new cache object to the cache pool, initialize the access density of the cache object, the last access location, the frequency of access, the average access interval, and jump into step (10);
[0037] (5) Already exists in the cache pool, calculate the current access interval;
[0038] (6) Whether it is the second visit, ...
specific Embodiment approach 2
[0048] Embodiment 2: This embodiment differs from Embodiment 1 in that: the access interval in step (3) is the difference between the number of cache accesses between the cache object hit this time and the cache object hit last time. Other steps and parameters are the same as those in Embodiment 1.
specific Embodiment approach 3
[0049] Embodiment 3: The difference between this embodiment and Embodiment 1 or 2 is that the access density in step (3) is the ratio of the number of cached object accesses to the total number of cached accesses within a period of time. Other steps and parameters are the same as those in Embodiment 1 or Embodiment 2.
[0050] Verify the beneficial effects of the present invention by the following examples:
[0051] 1. First analyze the life cycle of the cache object in the cache space;
[0052] 2. Secondly, analyze the behavior of web access and the distribution of URLs: study the distribution characteristics of web requests, and extract 427,936 user requests from the network logs of the campus gateway for three consecutive days, including 167,981 different URLs;
[0053] 3. Finally, according to the change trend of the cached objects, it is found that the replacement algorithm using density has better predictive ability: due to the locality of LRU and the cache pollution pr...
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