Declustering Two-Dimensional Datasets over MEMS-Based Storage

Yu, Hailing; Agrawal, Divyakant; Abbadi, Amr El

doi:10.1007/978-3-540-24741-8_29

Cited by 4 publications

(3 citation statements)

References 8 publications

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“…The enhancement part, on the other hand, investigates enhancing the performance and reducing the energy consumption of MEMS-based storage devices. Techniques for the data layout [12], [17], [5], scheduling policies [18], and techniques to estimate the physical dimensions [19] have been proposed.…”

Section: Related Workmentioning

confidence: 99%

Policies for probe-wear leveling in MEMS-based storage devices

Khatib

Hartel

2009

2009 IEEE International Symposium on Modeling, Analysis &Amp; Simulation of Computer and Telecommunication Systems

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Probes (or read/write heads) in MEMS-based storage devices are susceptible to wear. We study probe wear, and analyze the causes of probe uneven wear. We show that under real-world traces some probes can wear one order of magnitude faster than other probes leading to premature expiry of some probes. Premature expiry has severe consequences for the reliability, timing performance, energy-efficiency, and the lifetime of MEMS-based storage devices. Therefore, wear-leveling is a must to preclude premature expiry.We discuss how probe wear in MEMS-based storage is different from medium wear in Flash, calling for a different treatment. We present three policies to level probe wear. By simulation against three real-world traces, our work shows that an inevitable trade-off exists between lifetime, timing performance, and energy efficiency. The policies differ in the size of the trade-off. One of the policies maximizes the lifetime, so that it is optimal; and the other two are less optimal, and are used based on the configuration of the device.

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Section: Related Workmentioning

confidence: 99%

Policies for probe-wear leveling in MEMS-based storage devices

Khatib

Hartel

2009

2009 IEEE International Symposium on Modeling, Analysis &Amp; Simulation of Computer and Telecommunication Systems

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“…They show that using MEMS storage can improve IO utilization and cache performance for relational data. In a recent study, the authors have also demonstrated data placement techniques on the MEMS device for the general problem of declustering two-dimensional data [Yu et al 2004]. recently proposed using MEMS storage as an aid to boost disk performance as a read cache as well as write buffer for disk IOs.…”

Section: Related Workmentioning

confidence: 99%

Building MEMS-based storage systems for streaming media

et al. 2007

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The performance of streaming media servers has been limited by the dual requirements of high disk throughput (to service more clients simultaneously) and low memory use (to decrease system cost). To achieve high disk throughput, disk drives must be accessed with large IOs to amortize disk access overhead. Large IOs imply an increased requirement of expensive DRAM, and, consequently, greater overall system cost. MEMS-based storage, an emerging storage technology, is predicted to offer a price-performance point between those of DRAM and disk drives. In this study, we propose storage architectures that use the relatively inexpensive MEMS-based storage devices as an intermediate layer (between DRAM and disk drives) for temporarily staging large disk IOs at a significantly lower cost. We present data layout mechanisms and synchronized IO scheduling algorithms for the real-time storage and retrieval of streaming data within such an augmented storage system. Analytical evaluation suggests that MEMS-augmented storage hierarchies can reduce the cost and improve the throughput of streaming servers significantly.

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“…They map logical addresses onto physical sectors such that mechanical overheads are reduced for sequential access patterns. Yu et al [47,48] leverage the parallel probes in MEMS-based storage devices to support performance-efficient accesses to relational databases. They show that, unlike disk drives, MEMS-based storage devices enable the access of two-dimensional data sets in both row-wise and column-wise fashions, elevating the I/O utilization as well as the cache performance.…”

Section: Enhancementmentioning

confidence: 99%

MEMS-based storage devices

Khatib¹

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Declustering Two-Dimensional Datasets over MEMS-Based Storage

Cited by 4 publications

References 8 publications

Policies for probe-wear leveling in MEMS-based storage devices

Policies for probe-wear leveling in MEMS-based storage devices

Building MEMS-based storage systems for streaming media

MEMS-based storage devices

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