Online Paging for Flash Memory Devices

We propose a variation of online paging in two-level memory systems where pages in the fast cache get modified and therefore have to be explicitly written back to the slow memory upon evictions. For increased performance, up to 驴 arbitrary pages can be moved from the cache to the slow memory within a single joint eviction, whereas fetching pages from the slow memory is still performed on a one-by-one basis. The main objective in this new 驴-paging scenario is to bound the number of evictions. After providing experimental evidence that 驴-paging can improve the performance of flash-memory devices in the context of translation layers we turn to the theoretical connections between 驴-paging and standard paging. We give lower bounds for deterministic and randomized 驴-paging algorithms. For deterministic algorithms, we show that an adaptation of LRU is strongly competitive, while for the randomized case we show that by adapting the classical Mark algorithm we get an algorithm with a competitive ratio larger than the lower bound by a multiplicative factor of approximately 1.7.