Trajectory Codes for Flash Memory

TL;DR

This paper introduces trajectory codes for flash memory that enable efficient multiple data rewrites without erasures, extending existing models and achieving asymptotic optimality in various scenarios.

Contribution

It proposes a novel trajectory coding scheme for flash memories, generalizing previous models and demonstrating asymptotic optimality for multiple rewriting scenarios.

Findings

Trajectory codes enable multiple rewrites without block erasures.

The scheme is asymptotically optimal in many scenarios.

Randomized codes optimize expected rewriting performance.

Abstract

Flash memory is well-known for its inherent asymmetry: the flash-cell charge levels are easy to increase but are hard to decrease. In a general rewriting model, the stored data changes its value with certain patterns. The patterns of data updates are determined by the data structure and the application, and are independent of the constraints imposed by the storage medium. Thus, an appropriate coding scheme is needed so that the data changes can be updated and stored efficiently under the storage-medium's constraints. In this paper, we define the general rewriting problem using a graph model. It extends many known rewriting models such as floating codes, WOM codes, buffer codes, etc. We present a new rewriting scheme for flash memories, called the trajectory code, for rewriting the stored data as many times as possible without block erasures. We prove that the trajectory code is asymptotically optimal in a wide range of scenarios. We also present randomized rewriting codes optimized for expected performance (given arbitrary rewriting sequences). Our rewriting codes are shown to be asymptotically optimal.