FlashDB is a self-tuning database optimized for sensor networks using NAND \ufb02ash storage. In practical systems \ufb02ash is used in different packages such as on-board \ufb02ash chips, compact \ufb02ash 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 \ufb02ash are not optimized for all types of \ufb02ash 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 \ufb02ash devices and workloads, and show that our indexing scheme outperforms existing schemes under all workloads and \ufb02ash devices we consider.<\/p>\n","protected":false},"excerpt":{"rendered":"
FlashDB is a self-tuning database optimized for sensor networks using NAND \ufb02ash storage. In practical systems \ufb02ash is used in different packages such as on-board \ufb02ash chips, compact \ufb02ash 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. 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