Modeling and performance of MEMS-based storage devices
Proceedings of the 2000 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Designing computer systems with MEMS-based storage
ASPLOS IX Proceedings of the ninth international conference on Architectural support for programming languages and operating systems
Using MEMS-Based Storage to Boost Disk Performance
MSST '05 Proceedings of the 22nd IEEE / 13th NASA Goddard Conference on Mass Storage Systems and Technologies
Algorithms and data structures for flash memories
ACM Computing Surveys (CSUR)
Optimizing Probe-Based Storage
FAST '03 Proceedings of the 2nd USENIX Conference on File and Storage Technologies
Building MEMS-based storage systems for streaming media
ACM Transactions on Storage (TOS)
On efficient wear leveling for large-scale flash-memory storage systems
Proceedings of the 2007 ACM symposium on Applied computing
Workload-based configuration of MEMS-based storage devices for mobile systems
EMSOFT '08 Proceedings of the 8th ACM international conference on Embedded software
Probe-based ultrahigh-density storage technology
IBM Journal of Research and Development
Nanoscale PtSi Tips for Conducting Probe Technologies
IEEE Transactions on Nanotechnology
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Probes (read/write heads) in a MEMS storage device are susceptible to wear. We study probe wear, and analyze the causes of uneven wear. We show that under real-world workloads some probes can wear one order of magnitude faster than others. This premature expiry has severe consequences for reliability, timing performance, energy efficiency, and lifetime. Wear leveling precludes premature expiry and is thus necessary. We discuss the fundamental differences between probe wear in MEMS storage and medium wear in Flash, calling for a different treatment. We devise three policies to level probe wear. The policies provide a spectrum between best lifetime and least influence on the response time and energy efficiency of a MEMS storage device. We make the case that data migration can be prevented by augmenting the policies with a simple rule. We study the influence of the data layout configuration on the leveling performance of the policies.