Enabling Large-Scale Storage in Sensor Networks with the Coffee File System ISPN 2009 Lawrence

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.

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.

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.

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)

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.

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.

COFFEE (Cont.)

 Page Structure  A file is stored as a contiguous group  Page Allocation Algorithm: first-fit policy.

 Minimizing metadata in the RAM  (metadata in first page of file)

 Locating File  File cache for locations.  If not in cache => cache miss (sequentially scan)

 Garbage Collection

 Wear Leveling Policy  What is wear leveling  Erase too much -> memory corrupt  Method: delay garbage collection until a space reservation request cannot be fulfilled.

Evaluation

Conclusion  Coffee’s high throughput and low latency make it a suitable underlying layer for storage abstractions.