Stochastic modeling of large-scale solid-state storage systems

Yongkun Li, Patrick P.C. Lee, John C.S. Lui
2013 Proceedings of the ACM SIGMETRICS/international conference on Measurement and modeling of computer systems - SIGMETRICS '13  
Solid state drives (SSDs) have seen wide deployment in mobiles, desktops, and data centers due to their high I/O performance and low energy consumption. As SSDs write data out-of-place, garbage collection (GC) is required to erase and reclaim space with invalid data. However, GC poses additional writes that hinder the I/O performance, while SSD blocks can only endure a finite number of erasures. Thus, there is a performance-durability tradeoff on the design space of GC. To characterize the
more » ... al tradeoff, this paper formulates an analytical model that explores the full optimal design space of any GC algorithm. We first present a stochastic Markov chain model that captures the I/O dynamics of large-scale SSDs, and adapt the mean-field approach to derive the asymptotic steady-state performance. We further prove the model convergence and generalize the model for all types of workload. Inspired by this model, we propose a randomized greedy algorithm (RGA) that can operate along the optimal tradeoff curve with a tunable parameter. Using trace-driven simulation on DiskSim with SSD addons, we demonstrate how RGA can be parameterized to realize the performance-durability tradeoff.
doi:10.1145/2465529.2465546 dblp:conf/sigmetrics/LiLL13 fatcat:ucqucgqxjrh6rdk7zb4z4gzh3i