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Published April 2009 | public
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Universal Rewriting in Constrained Memories

Abstract

A constrained memory is a storage device whose elements change their states under some constraints. A typical example is flash memories, in which cell levels are easy to increase but hard to decrease. In a general rewriting model, the stored data changes with some pattern determined by the application. In a constrained memory, an appropriate representation is needed for the stored data to enable efficient rewriting. In this paper, we define the general rewriting problem using a graph model. This model generalizes many known rewriting models such as floating codes, WOM codes, buffer codes, etc. We present a novel rewriting scheme for the flash-memory model and prove it is asymptotically optimal in a wide range of scenarios. We further study randomization and probability distributions to data rewriting and study the expected performance. We present a randomized code for all rewriting sequences and a deterministic code for rewriting following any i.i.d. distribution. Both codes are shown to be optimal asymptotically.

Additional Information

This work was supported in part by the NSF CAREER Award CCF-0747415, the NSF grant ECCS-0802107, the ISF grant 480/08, the GIF grant 2179-1785.10/2007, and the Caltech Lee Center for Advanced Networking.

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Created:
August 20, 2023
Modified:
October 24, 2023