Abstract
TBF presents a RAM-frugal cache replacement policy that approximates the least-recently-used (LRU) policy. It uses two in-RAM Bloom filters to maintain the recency information and leverages an on-flash key–value store to cache objects. TBF could be easily integrated with any key-value stores to provide caching functionalities. TBF requires only one additional byte of RAM per cached object while providing similar performance as LRU and its variants, thus makes it suitable for implementing a very large flash-based cache. Full-paper link: http://www.nec-labs.com/~biplob/Papers/TBF.pdf
Learning Objectives
Understanding in-RAM metadata bottleneck for a huge flash-based second-level cache
Understanding the memory overhead of an LRU-like algorithm
Understanding how Bloom filter works
Understanding how to integrate in-RAM Bloom filter with an on-flash key-value store to reduce RAM consumption