Dual Greedy: Adaptive Garbage Collection for Page-Mapping Solid-State Disks

Abstract

In the recent years, commodity solid-state disks have started adopting powerful controllers and implemented page-level mapping for flash management. However, many of these models still use primitive garbage-collection algorithms, because prior approaches do not scale up with the dramatic increase of flash capacity. This study introduces Dual Greedy for garbage collection in page-level mapping. Dual Greedy identifies page-accurate data hotness using only block-level information, and adaptively switches its preference of victim selection between block space utilization and block stability. It can run in constant time and use very limited RAM space. Our experimental results show that Dual Greedy outperforms existing approaches in terms of garbage-collection overhead, especially with large flash blocks.