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Effective Recovery of Flash memory Utilizing FTL and Shadow Paging
  • ALAHMADI ABDULHADI ABDULGHAFUR M
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dc.contributor.advisorTae Sun Chung-
dc.contributor.authorALAHMADI ABDULHADI ABDULGHAFUR M-
dc.date.issued2024-02-
dc.identifier.other33242-
dc.identifier.urihttps://aurora.ajou.ac.kr/handle/2018.oak/38803-
dc.description학위논문(박사)--컴퓨터공학과,2024. 2-
dc.description.abstractThe 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-
dc.description.tableofcontentsChapter 1 INTRODUCTION 1_x000D_ <br> 1.1 Background 1_x000D_ <br> 1.2 Flash Translation Layer (FTL) Motivation 5_x000D_ <br> 1.2.1 Significant Considerations in the Design of Power-Off Recovery with FTL 7_x000D_ <br> 1.3 Significance shadow paging in recovery of flash memory 8_x000D_ <br> 1.4 Improving the search operations of TCAM Memory with Effective selection of Memory Technologies 10_x000D_ <br> 1.5 Research Contribution 12_x000D_ <br> 1.5.1 Crash Recovery Techniques for Flash Storage Devices Leveraging Flash Translation Layer: A Review 12_x000D_ <br> 1.5.2 An Effective Recovery Scheme for Flash Memory Leveraging Shadow Paging 13_x000D_ <br> 1.5.3 An Effective Selection of Memory Technologies for TCAM to Improve the Search Operations 13_x000D_ <br> 1.6 Organization of the Dissertation 14_x000D_ <br>Chapter 2 Crash Recovery Techniques for Flash Storage Devices Leveraging FTL 16_x000D_ <br> 2.1 Preliminaries 16_x000D_ <br> 2.1.1 NAND Flash Memory 16_x000D_ <br> 2.1.2 SSDs 18_x000D_ <br> 2.1.3 Flash Drive 19_x000D_ <br> 2.1.4 HDD 19_x000D_ <br> 2.1.5 Flash Translation Layer 20_x000D_ <br> 2.1.6 Flash Memory Operations Charachteristics 21_x000D_ <br> 2.2 Taxonomy of the FTL Algorithm 22_x000D_ <br> 2.2.1 Sector mapping approach 22_x000D_ <br> 2.2.2 Block Mapping Strategy 23_x000D_ <br> 2.2.3 Hybrid Mapping Methodology 24_x000D_ <br> 2.2.4 Log Block Method 25_x000D_ <br> 2.2.5 BAST 26_x000D_ <br> 2.2.6 FAST 27_x000D_ <br> 2.3 Motivation for using FTL in Crash Recovery 28_x000D_ <br> 2.4 The FTL-Based Crash Recovery Schemes and Discussion 29_x000D_ <br> 2.4.1 Machine Learning-Based Methods for Crash Recovery 30_x000D_ <br> 2.4.2 Various Flash Types Leveraging FTL in Crash Recovery and Parameters of Evaluation 32_x000D_ <br> 2.4.3 Mapping Mechanisims i.e., Sector, Block and Hybrid Mapping Schemes in FTL Crash Recovery 40_x000D_ <br> 2.4.4 Summary of chapter 45_x000D_ <br>Chapter 3 RSLSP: An Effective Recovery Scheme for Flash Memory Leveraging Shadow Paging 46_x000D_ <br> 3.1 Research background and Contributions 46_x000D_ <br> 3.1 Flash Translation Layer (FTL) 49_x000D_ <br> 3.1.1 FTL Characteristics 49_x000D_ <br> 3.1.2 Characteristics of FTL Algorithms 50_x000D_ <br> 3.1.3 Characteristics of Flash Memory Operations 50_x000D_ <br> 3.2 Background and Motivation of the Proposed Scheme 51_x000D_ <br> 3.2.1 Address Mapping Schemes 51_x000D_ <br> 3.2.2 The Bast Scheme Overview 54_x000D_ <br> 3.2.3 Merge Operations 57_x000D_ <br> 3.2.4 Memory Reoptimized 58_x000D_ <br> 3.3 Map Block Method 58_x000D_ <br> 3.4 Proposed Technique (RSLSP) 59_x000D_ <br> 3.4.1 Revisit Map Block Method 61_x000D_ <br> 3.4.2 Revisit Shadow Paging 62_x000D_ <br> 3.4.3 RSLSP 64_x000D_ <br> 3.5 RSLSP Approach 66_x000D_ <br> 3.5.1 Shadow Paging Protocol 66_x000D_ <br> 3.5.2 BAST Protocol 68_x000D_ <br> 3.6 Experimental Results, Comparison and Discussion 69_x000D_ <br> 3.7 Summary of Chapter 77_x000D_ <br>Chapter 4 An Effective Selection of Memory Technologies for TCAM to Improve the Search Operations: Demonstration in SDN Recovery 78_x000D_ <br> 4.1 TCAM Memory Technologies and Features significance for search Operations 78_x000D_ <br> 4.2 Problem statement 80_x000D_ <br> 4.3 ANP Mathematical model for ranking the TCAM memory alternatives 82_x000D_ <br> 4.3.1 TCAM memories (alternatives) and features Pairwise comparison 86_x000D_ <br> 4.3.2 Pairwise Comparison Matrix (A) 88_x000D_ <br> 4.3.3 Calculate the Consistency Ratio (CR) 91_x000D_ <br> 4.3.4 Weighted Supermatrix 91_x000D_ <br> 4.3.5 Limit Supermatrix 92_x000D_ <br> 4.4 Simulations and Results 93_x000D_ <br> 4.5 Summary of the Chapter 98_x000D_ <br>Chapter 5 Conclusion 100_x000D_ <br>References 103_x000D_-
dc.language.isoeng-
dc.publisherThe Graduate School, Ajou University-
dc.rights아주대학교 논문은 저작권에 의해 보호받습니다.-
dc.titleEffective Recovery of Flash memory Utilizing FTL and Shadow Paging-
dc.typeThesis-
dc.contributor.affiliation아주대학교 대학원-
dc.contributor.department일반대학원 컴퓨터공학과-
dc.date.awarded2024-02-
dc.description.degreeDoctor-
dc.identifier.urlhttps://dcoll.ajou.ac.kr/dcollection/common/orgView/000000033242-
dc.subject.keywordANP-
dc.subject.keywordFTL-
dc.subject.keywordMemory management-
dc.subject.keywordNAND-
dc.subject.keywordRecovery-
dc.subject.keywordSDN-
dc.subject.keywordSoftware-defined Module-
dc.subject.keywordStorage Management-
dc.subject.keywordTCAM-
dc.subject.keywordpower failure-
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