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Effective Recovery of Flash memory Utilizing FTL and Shadow Paging

초록/요약

The flash storage is a type of nonvolatile semiconductor device that is operated continuously and has been substituting the hard disk or secondary memory in several storage markets, such as PC/laptop computers, mobile devices, and is also used as an enterprise server. Moreover, it offers a number of benefits, including compact size, low power consumption, quick access, easy mobility, heat dissipation, shock tolerance, data preservation during a power outage, and random access. Different embedded system products, including digital cameras, smartphones, personal digital assistants (PDA), along with sensor devices, are currently integrating flash memory. However, as flash memory requires unique capabilities such as “erase before write” as well as “wear-leveling”, a FTL (flash translation layer) is added to the software layer. The FTL software module overcomes the problem of performance that arises from the erase before write operation and wear-leveling, i.e., flash memory does not allow for an in-place update, and therefore a block must be erased prior to overwriting upon the present data. In the meantime, flash storage devices face challenges of failure and thus they must be able to recover metadata (as well as address mapping information), including data after a crash. The FTL layer is responsible for and intended for use in crash recovery. Although the power-off recovery technique is essential for portable devices, most FTL algorithms do not take this into account. Firstly, we review various schemes of crash recovery leveraging FTL for flash storage devices. We illustrate the classification of the FTL algorithms. Moreover, we also discuss the various metrics and parameters evaluated for comparison with other approaches by each scheme, along with the flash type. In addition, we made an analysis of the FTL schemes. We also describe meaningful considerations which play a critical role in the design development for power-off recovery employing FTL. Secondly, we propose an effective scheme for the recovery of flash memory leveraging the shadow paging concept for storage devices using flash memory. To combat the sudden power off problem, the suggested RSLSP approach saves and keeps the map block data as a combination of two tables, i.e., first is the original block and the second block is a replica for the original one. Our proposed strategy not only improves the capacity of a flash memory device as compared to the state- of-the-art schemes suggested in the literature, but is also compatible with the existing FTL-based schemes. Thirdly, When considering which flash memory technology is to be used in conjunction with ternary content addressable memory (TCAM), we need to balance several factors to ensure optimal performance, speed, endurance, reliability, integration complexity, and cost-effectiveness. Hence, it leads to a multi-criteria decision-making problem regarding the selection of other memory technologies such as 3D XPoint, Magnetoresistive RAM, Resistive RAM and Ferroelectric RAM. In this paper, we use the analytical network process (ANP) method to select the suitable technology in conjunction with TCAM considering the features of the memory technologies for SD-IoT. We provide a comprehensive numerical model leveraging ANP to rank the memory technologies regarding their weights. The highest weights identify the most suitable technology for TCAM. We perform simulations to show the effectiveness of the mathematical model utilizing ANP. The results show that suggested methodology reduces the recovery delay, improve the packets received ratio, decrease the jitter and increase the throughput. Keywords: Storage Management, Software-defined Module, power failure, FTL, Recovery, NAND, Memory management, ANP, SDN, TCAM

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목차

Chapter 1 INTRODUCTION 1
1.1 Background 1
1.2 Flash Translation Layer (FTL) Motivation 5
1.2.1 Significant Considerations in the Design of Power-Off Recovery with FTL 7
1.3 Significance shadow paging in recovery of flash memory 8
1.4 Improving the search operations of TCAM Memory with Effective selection of Memory Technologies 10
1.5 Research Contribution 12
1.5.1 Crash Recovery Techniques for Flash Storage Devices Leveraging Flash Translation Layer: A Review 12
1.5.2 An Effective Recovery Scheme for Flash Memory Leveraging Shadow Paging 13
1.5.3 An Effective Selection of Memory Technologies for TCAM to Improve the Search Operations 13
1.6 Organization of the Dissertation 14
Chapter 2 Crash Recovery Techniques for Flash Storage Devices Leveraging FTL 16
2.1 Preliminaries 16
2.1.1 NAND Flash Memory 16
2.1.2 SSDs 18
2.1.3 Flash Drive 19
2.1.4 HDD 19
2.1.5 Flash Translation Layer 20
2.1.6 Flash Memory Operations Charachteristics 21
2.2 Taxonomy of the FTL Algorithm 22
2.2.1 Sector mapping approach 22
2.2.2 Block Mapping Strategy 23
2.2.3 Hybrid Mapping Methodology 24
2.2.4 Log Block Method 25
2.2.5 BAST 26
2.2.6 FAST 27
2.3 Motivation for using FTL in Crash Recovery 28
2.4 The FTL-Based Crash Recovery Schemes and Discussion 29
2.4.1 Machine Learning-Based Methods for Crash Recovery 30
2.4.2 Various Flash Types Leveraging FTL in Crash Recovery and Parameters of Evaluation 32
2.4.3 Mapping Mechanisims i.e., Sector, Block and Hybrid Mapping Schemes in FTL Crash Recovery 40
2.4.4 Summary of chapter 45
Chapter 3 RSLSP: An Effective Recovery Scheme for Flash Memory Leveraging Shadow Paging 46
3.1 Research background and Contributions 46
3.1 Flash Translation Layer (FTL) 49
3.1.1 FTL Characteristics 49
3.1.2 Characteristics of FTL Algorithms 50
3.1.3 Characteristics of Flash Memory Operations 50
3.2 Background and Motivation of the Proposed Scheme 51
3.2.1 Address Mapping Schemes 51
3.2.2 The Bast Scheme Overview 54
3.2.3 Merge Operations 57
3.2.4 Memory Reoptimized 58
3.3 Map Block Method 58
3.4 Proposed Technique (RSLSP) 59
3.4.1 Revisit Map Block Method 61
3.4.2 Revisit Shadow Paging 62
3.4.3 RSLSP 64
3.5 RSLSP Approach 66
3.5.1 Shadow Paging Protocol 66
3.5.2 BAST Protocol 68
3.6 Experimental Results, Comparison and Discussion 69
3.7 Summary of Chapter 77
Chapter 4 An Effective Selection of Memory Technologies for TCAM to Improve the Search Operations: Demonstration in SDN Recovery 78
4.1 TCAM Memory Technologies and Features significance for search Operations 78
4.2 Problem statement 80
4.3 ANP Mathematical model for ranking the TCAM memory alternatives 82
4.3.1 TCAM memories (alternatives) and features Pairwise comparison 86
4.3.2 Pairwise Comparison Matrix (A) 88
4.3.3 Calculate the Consistency Ratio (CR) 91
4.3.4 Weighted Supermatrix 91
4.3.5 Limit Supermatrix 92
4.4 Simulations and Results 93
4.5 Summary of the Chapter 98
Chapter 5 Conclusion 100
References 103

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