FlashDB dynamic self-tuning database for NAND flash
FlashDB is a self-tuning database optimized for sensor networks using NAND flash storage. In practical systems flash is used in different packages such as on-board flash chips, compact flash cards, secure digital cards and related formats. Our experiments reveal non-trivial differences in their acce...
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| Vydáno v: | Proceedings of the 6th international conference on Information processing in sensor networks s. 410 - 419 |
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| Hlavní autoři: | , |
| Médium: | Konferenční příspěvek |
| Jazyk: | angličtina |
| Vydáno: |
New York, NY, USA
ACM
25.04.2007
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| Edice: | ACM Conferences |
| Témata: |
Information systems
> Data management systems
> Database management system engines
> Database query processing
Information systems
> Information retrieval
> Search engine architectures and scalability
> Search engine indexing
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| ISBN: | 9781595936387, 1595936386 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | FlashDB is a self-tuning database optimized for sensor networks using NAND flash storage. In practical systems flash is used in different packages such as on-board flash chips, compact flash cards, secure digital cards and related formats. Our experiments reveal non-trivial differences in their access costs. Furthermore, databases may be subject to different types of workloads. We show that existing databases for flash are not optimized for all types of flash devices or for all workloads and their performance is thus suboptimal in many practical systems. FlashDB uses a novel self-tuning index that dynamically adapts its storage structure to workload and underlying storage device. We formalize the self-tuning nature of an index as a two-state task system and propose a 3-competitive online algorithm that achieves the theoretical optimum. We also provide a framework to determine the optimal size of an index node that minimizes energy and latency for a given device. Finally, we propose optimizations to further improve the performance of our index. We prototype and compare different indexing schemes on multiple flash devices and workloads, and show that our indexing scheme outperforms existing schemes under all workloads and flash devices we consider. |
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| ISBN: | 9781595936387 1595936386 |
| DOI: | 10.1145/1236360.1236412 |