Workload-Based Configuration of MEMS-Based Storage Devices for Mobile Systems

Because of its small form factor, high capacity, and expected low cost, MEMS-based storage is a suitable storage technology for mobile systems. However, flash memory may outperform MEMS-based storage in terms of performance, and energy-efficiency. The problem is that MEMS-based storage devices have a large number (i.e., thousands) of heads, and to deliver peak performance, all heads must be deployed simultaneously to access each single sector. Since these devices are mechanical and thus some housekeeping information is needed for each head, this results in a huge capacity loss and increases the energy consumption of MEMS-based storage with respect to flash. We solve this problem by proposing new techniques to lay out data in MEMS-based storage devices. Data layouts represent optimizations in a design space spanned by three parameters: the number of active heads, sector parallelism, and sector size. We explore this design space and show that by exploiting knowledge of the expected workload, MEMS-based devices can employ all heads, thus delivering peak performance, while decreasing the energy consumption and compromising only a little on the capacity. Our exploration shows that MEMS-based storage is competitive with flash in most cases, and outperforms flash in a few cases

Using MEMS-based storage in disk arrays

Current disk arrays, the basic building blocks of high-performance storage systems, are built around two memory technologies: magnetic disk drives, and non-volatile DRAM caches. Disk latencies are higher by six orders of magnitude than non-volatile DRAM access times, but cache costs over 1000 times more per byte. A new storage technology based on microelectromechanical systems (MEMS) will soon offer a new set of performance and cost characteristics that bridge the gap between disk drives and the caches. We evaluate potential gains in performance and cost by incorporating MEMS-based storage in disk arrays. Our evaluation is based on exploring potential placements of MEMS-based storage in a disk array. We used detailed disk array simulators to replay I/O traces of real applications for the evaluation. We show that replacing disks with MEMS-based storage can improve the array performance dramatically, with a cost performance ratio several times better than conventional arrays even if MEMS storage costs ten times as much as disk. We also demonstrate that hybrid MEMS/disk arrays, which cost less than purely MEMS-based arrays, can provide substantial improvements in performance and cost/performance over conventional arrays