HFA: A Hint Frequency-based Approach to Enhance the I/O Performance of Multi-level Cache Storage Systems

With the enormous and increasing user demand, I/O performance is one of the primary considerations to build a data center. Several new technologies in data centers, such as tiered storage [33], prompt the widespread usage of multi-level cache techniques. In these storage systems, the upper level storage typically serves as a cache for the lower level, which forms a distributed multi-level cache system. However, although many excellent multi-level cache algorithms are proposed to improve the I/O performance, they still have potential to be enhanced by investigating the history information of hints [28]. To address this challenge, in this paper, we propose a novel Hint Frequency-based Approach (HFA), to improve the overall multi-level cache performance of storage systems. The main idea of HFA is using hint frequencies (the total number of demotions/promotions by employing demote/promote hints) to efficiently explore the valuable history information of data blocks among multiple levels. HFA can be applied with several popular multi-level cache algorithms, such as Demote, Promote, Hint-K, etc. Simulation results show that, compared to original multi-level cache algorithms such as Demote, Promote and Hint-K, HFA can improve the I/O performance by up to 20% under different I/O workloads.