Accurate Probabilistic Miss Ratio Curve Approximation for Adaptive Cache Allocation in Block Storage Systems

Rongshang Li, Yingtian Tang, Qiquan Shi, Hui Mao, Lei Chen, Jikun Jin, Peng Lu, Zhuo Cheng

Abstract: Cache plays an important role in storage systems. With better allocation of cache space to each storage device, total I/O latency can be reduced remarkably. To achieve this goal, we propose an Accurate Probabilistic miss ratio curve approximation for Adaptive Cache allocation (APAC) system. APAC can obtain near-optimal performance for allocating cache space with low overhead. Specifically, with a linear-time probabilistic approximation of reuse distance of all blocks inside each device, APAC can accurately estimate the miss ratio curve (MRC). Furthermore, APAC utilizes the MRCs to obtain the near-optimal configuration of cache allocation by dynamic programming. Experimental results show that APAC achieves higher accuracy in MRC approximation compared to the state-of-the-art methods, leading to higher hit ratio and lower latency of the block storage systems.