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Enabling Large-Scale Storage in Sensor Networks with the Coffee File System ISPN 2009 Lawrence
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Introduction Motivation Existing storage systems access the flash memory directly and ad hoc, or use too much RAM to handle large flash memories. Storage abstractions Meet the need for a generic, high speed, flash- based file system that is feasible for a wide rage of sensor devices.
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Storage In Sensor Network Storage Centricity From communication-centric to storage-centric Batching data for saving energy Delay-tolerant v.s. delay-sensitive(ex. fire alarm) Storage-centric sensor net require storage facilities.
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Storage In Sensor Network(Cont.) Using Storage as Virtual Memory Use the flash as swap area. VM requires faster storage systems. Require storage manage application: 1. Wear leveling 2. Garbage collection 3. Space allocation In this paper, there is a storage abstraction allocation that suit for above requirements.
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Storage In Sensor Network(Cont.) Flash memory semantics Some part (called erase sectors) must be erased before overwriting. Flash memory: 1.NOR flash (good for read) 2.NAND flash (good for storage)
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COFFEE Coffee is a portable, high-speed file system for sensor device equipped with flash memories. Micro logs to handle file modifications. Use a small footprint: each open file O(1) RAM.
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COFFEE (Cont.) Design principles Memory and code size constraints. Small memory footprints-regardless of the file sizes. Rule: 1.divided into erase sectors of size 2.Erease sets all bits to 1 3.Programming switches a subset of the bits in a page from 1 to 0.
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COFFEE (Cont.)
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Page Structure A file is stored as a contiguous group Page Allocation Algorithm: first-fit policy.
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Minimizing metadata in the RAM (metadata in first page of file)
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Locating File File cache for locations. If not in cache => cache miss (sequentially scan)
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Garbage Collection
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Wear Leveling Policy What is wear leveling Erase too much -> memory corrupt Method: delay garbage collection until a space reservation request cannot be fulfilled.
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Evaluation
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Conclusion Coffee’s high throughput and low latency make it a suitable underlying layer for storage abstractions.
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