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Erschienen in:
Biomimetic Materials and Structures for Sensor Applications Kapitel lesen Erstes Kapitel lesen

2017 | OriginalPaper | Buchkapitel

6. NVRAM-Assisted Optimization Techniques for Flash Memory Management in Embedded Sensor Nodes

verfasst von : Duo Liu, Kan Zhong

Erschienen in: Smart Sensors and Systems

Verlag: Springer International Publishing

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Abstract

Embedded sensor nodes are sensitize to battery lifetime and evidences show that DRAM-based main memory subsystem is the major contributor of the energy consumption of embedded sensor nodes. Due to the high density, byte-addressability, and low standby power consumption, non-volatile random access memories (NVRAMs), such as PRAM and STT-RAM, become promising main memory alternatives in embedded sensor nodes. On the other hand, NAND flash memory is widely adopted for storing collected data in embedded sensor nodes. However, both NVRAM and NAND flash memory have limited lifetime, how to optimize the management of NAND flash memory in NVRAM-based embedded sensor nodes while considering the endurance issue becomes quite important. In this chapter, we introduce a write-actively-aware NAND flash memory management scheme to effectively manage NAND flash memory while reducing the write activities to NVRAM-based main memory in embedded sensor nodes. The basic idea is to preserve each bit in flash mapping table, which is stored in NVRAM, from being inverted frequently during the mapping table update process. To achieve this, a two-level mapping mechanism is employed while considering the access behavior of IO requests, and a customized wear-leveling scheme is developed to evenly distribute the writes across the whole mapping table. Evaluation results show that the proposed technique can reduce the write activities significantly and achieve an even distribution of writes in NVRAM with low overhead.

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Metadaten
Titel
NVRAM-Assisted Optimization Techniques for Flash Memory Management in Embedded Sensor Nodes
verfasst von
Duo Liu
Kan Zhong
Copyright-Jahr
2017
Buch
Smart Sensors and Systems

Print ISBN: 978-3-319-33200-0

Electronic ISBN: 978-3-319-33201-7

Copyright-Jahr: 2017

DOI
https://doi.org/10.1007/978-3-319-33201-7_6

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