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Predictive Caching Other caches we've tested have been largely passive: they retrieve content at browser request, augmented by scheduled download of sites deemed popular by the administrator. Scheduled downloads are notably absent from the CacheFlow because they are irrelevant. The CacheOS attempts to identify and pre-fetch popular content so that it will be fresh when the next request arrives. An "adaptive refresh algorithm" monitors the frequency of change and use for each stored object; it predicts when the object will become stale and proactively refreshes the object before the next hit is likely. Adaptive refresh jumped to our attention right away: at first, our CacheFlow didn't store objects generated by Polygraph. CacheFlow re-fetched objects without TTL or Last-Modified tags to determine update frequency, and Polygraph's random content made these objects appear changed every time. The CacheOS decided these ever-changing objects were not useful to store. Since we wanted to vend stored objects, we added TTL to our Polygraph workload. It wasn't intentional, but this test clearly demonstrated how adaptive refresh works to ensure delivery of fresh objects.
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