Erasure-Coding-Based Storage and Recovery for Distributed Exascale Storage Systems

Kim, Jeong-Joon

doi:10.3390/app11083298

Cited by 5 publications

(2 citation statements)

References 30 publications

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“…It has incalculable execution encoding, decoding, and input/yield corruption elements in general. Kim [29] proposes a buffering and joining method in which several I/O demands that occur during encoding are combined and treated as one. It offers four recovery options for distributing the disk input/yield loads generated during decoding.…”

Section: A Related Workmentioning

confidence: 99%

Data Recovery Approach with Optimized Cauchy Coding in Distributed Storage System

Funde¹,

Swain²

2022

IJACSA

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In the professional world, the impact of big data is pulsating to change things. Data is currently generated by a wide range of sensors that are part of smart devices. It necessitates data storage and retrieval that is fault tolerant. Data loss can be caused by natural calamities, human error, or mechanical failure. Several security threats and data degradation attacks attempt to destroy storage disks, causing partial or complete data loss. The data encoding and data recovery mechanisms is proposed in this research. To produce a set of matrices utilizing matrix heuristics, the suggested system proposes an efficient Optimized Cauchy Coding (OCC) approach. In this paper, the Cauchy matrix is used as a generator matrix in Reed Solomon (RS) code to encode data blocks with fewer XOR operations. It reduces the encoding algorithm's time complexity. Furthermore, in the event of a disk failure, missing data from any data block is made available through the Code word. In terms of data recovery, it outperforms the Optimal Weakly Secure Minimum Storage Regenerating (OWSPM-MSR) and Product-Matrix Minimum Storage Regenerating (PM-MSR) methods. For data coding, a 1024KB file with various combinations of data blocks l and parity blocks m is evaluated. In the first scenario, m is 1 and l ranges from 4 to 10. The value of l is 4 in the second scenario, while m ranges from 1 to 10. The existing OWSPM-MSR approach takes an average of 0.125 seconds to encode and 0.22 seconds to decode, whereas the PM-MSR approach takes an average of 0.045 seconds to encode and 0.16 seconds to decode. The proposed OCC approach speeds up data coding by taking an average of 0.035 seconds to encode and 0.116 seconds to decode data.

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Section: A Related Workmentioning

confidence: 99%

Data Recovery Approach with Optimized Cauchy Coding in Distributed Storage System

Funde¹,

Swain²

2022

IJACSA

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“…In other research, the applications of Reed-Solomon erasure code are for environments other than the one in this paper, showing a gap in its applications to Dicoogle PACS. In this regard, it is worth mentioning that the study carried out in [77] used values of k = 2, 4, 8 and m = 2, 2, 2. Likewise, in [78], the authors used k = 6, 10 and m = 3, 4.…”

Section: B Softwarementioning

confidence: 99%

Evaluating Erasure Codes in Dicoogle PACS

et al. 2022

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DICOM (Digital Imaging and Communication in Medicine) is a standard for image and data transmission in medical purpose hardware and is commonly used for viewing, storing, printing and transmitting images. As a part of the way that DICOM transmits files, the PACS (Picture Archiving and Communication System) platform, Dicoogle, has become one of the most in-demand image processing and viewing platforms. However, the Dicoogle PACS architecture does not guarantee image information recovery in the case of information loss. Therefore, this paper proposes a file recovery solution in the Dicoogle architecture. The proposal consists of maximizing the encoding and decoding performance of medical images through computational parallelism. To validate the proposal, the Java programming language based on the Reed-Solomon algorithm is implemented in different performance tests. The experimental results show that the proposal is optimal in terms of image processing time for the Dicoogle PACS storage system. INDEX TERMSDicoogle PACS, fault tolerance, DICOM, Reed-Solomon erasure code. RAUL H. PALACIOS received the bachelor's degree in systems engineering from the Universidad Autónoma de Tamaulipas, Mexico, in 2003, and the M.S. degree in computer and network engineering and the Ph.D. degree in information and communication technologies from the University

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