Repair and Restoration of Corrupted LZSS Files

Wang, Gang; Hua, Peng; Tang, Yongwang

doi:10.1109/access.2019.2891764

Cited by 5 publications

(3 citation statements)

References 24 publications

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“…Benefiting from the redundancy, the encoded results can always be decoded correctly as long as the errors (such as data loss or forgery) do not exceed the upper limits of the capabilities for error detection and correction, which improve with more redundancy [27]. Thus, error-correcting coding is widely used in data backup and distributed storage [28,29].…”

Section: Reed-solomon Codementioning

confidence: 99%

Cuckoo-Store Engine: A Reed–Solomon Code-Based Ledger Storage Optimization Scheme for Blockchain-Enabled IoT

et al. 2023

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As the distributed ledger technology underlying cryptocurrencies such as Bitcoin and Ethereum, blockchain has empowered various industries, such as supply chain management, healthcare, government services, e-voting, etc. However, the ever-growing ledger on each node has been the main bottleneck for blockchain scalability as the network scale expands, which worsens in blockchain-enabled IoT scenarios with resource-limited devices. With the support of the Reed–Solomon (RS) code, the Cuckoo-Store (CS), a ledger storage optimization engine, is proposed in this paper to dramatically decrease the storage burden on each node by encoding the ledger as data segments with redundancy and distributing them to multiple nodes. These distributed data segments can be collected and decoded using RS code to recover the original ledger. Furthermore, the Cuckoo filter (CF) is used to guarantee the integrity of the encoded segments, which helps detect the forged segments and facilitates the process of ledger recovery. Theoretical analysis and simulation results show that the CS engine can decrease the storage in each node by more than 94%, and the original ledger can be recovered efficiently with acceptable communication overheads.

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Section: Reed-solomon Codementioning

confidence: 99%

Cuckoo-Store Engine: A Reed–Solomon Code-Based Ledger Storage Optimization Scheme for Blockchain-Enabled IoT

et al. 2023

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“…Many applications and algorithms create the dictionary dynamically, hence, when there is an input, the dictionary can be updated as needed. There are more than 19 algorithms support dictionary-based algorithms such as Byte pair encoding [ 105 ], Lz77 [ 87 , 106 , 107 ], Lz78 [ 74 ], (LZW) Lempel–Ziv–Welch [ 108 ], (LZSS) Lempel–Ziv–Storer–Szymanski [ 103 , 109 , 110 , 111 ], (LZS) Lempel–Ziv–Stac [ 112 ], (LZO) Lempel–Ziv–Oberhumer [ 113 , 114 ], Snappy [ 115 , 116 ], Brotli [ 117 , 118 ], Deflate [ 119 ], Deflate64 [ 120 ], LZ4 [ 121 , 122 , 123 ], (LZFSE) Lempel–Ziv Finite State Entropy [ 124 , 125 ], (LZJB) Lempel Ziv Jeff Bonwick [ 108 ], (LZMA) Lempel-Ziv-Markov chain-Algorithm [ 108 ], (LZRW) Lempel–Ziv Ross Williams [ 108 , 121 , 126 ], LZWL [ 127 , 128 ], LZX [ 129 ].…”

Section: Compressionmentioning

confidence: 99%

The Deep Learning Solutions on Lossless Compression Methods for Alleviating Data Load on IoT Nodes in Smart Cities

Nasif

Othman

Sani

2021

Sensors

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Networking is crucial for smart city projects nowadays, as it offers an environment where people and things are connected. This paper presents a chronology of factors on the development of smart cities, including IoT technologies as network infrastructure. Increasing IoT nodes leads to increasing data flow, which is a potential source of failure for IoT networks. The biggest challenge of IoT networks is that the IoT may have insufficient memory to handle all transaction data within the IoT network. We aim in this paper to propose a potential compression method for reducing IoT network data traffic. Therefore, we investigate various lossless compression algorithms, such as entropy or dictionary-based algorithms, and general compression methods to determine which algorithm or method adheres to the IoT specifications. Furthermore, this study conducts compression experiments using entropy (Huffman, Adaptive Huffman) and Dictionary (LZ77, LZ78) as well as five different types of datasets of the IoT data traffic. Though the above algorithms can alleviate the IoT data traffic, adaptive Huffman gave the best compression algorithm. Therefore, in this paper, we aim to propose a conceptual compression method for IoT data traffic by improving an adaptive Huffman based on deep learning concepts using weights, pruning, and pooling in the neural network. The proposed algorithm is believed to obtain a better compression ratio. Additionally, in this paper, we also discuss the challenges of applying the proposed algorithm to IoT data compression due to the limitations of IoT memory and IoT processor, which later it can be implemented in IoT networks.

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“…LZ77 [9] and LZ78 [16] are the most famous algorithms. LZSS is the most popular versions of LZ77 [17][18][19]. There are many researches works on LZ design for data compression.…”

Section: Related Workmentioning

confidence: 99%

FPGA implementation of Lempel-Ziv data compression

Mostafa

Zekry

Zakaria

2021

IJRES

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When transmitting the data in digital communication, it is well desired that the transmitting data bits should be as minimal as possible, so many techniques are used to compress the data. In this paper, a Lempel-Ziv algorithm for data compression was implemented through VHDL coding. One of the most lossless data compression algorithms commonly used is Lempel-Ziv. The work in this paper is devoted to improve the compression rate, space-saving, and utilization of the Lempel-Ziv algorithm using a systolic array approach. The developed design is validated with VHDL simulations using Xilinx ISE 14.5 and synthesized on Virtex-6 FPGA chip. The results show that our design is efficient in providing high compression rates and space-saving percentage as well as improved utilization. The Throughput is increased by 50% and the design area is decreased by more than 23% with a high compression ratio compared to comparable previous designs.

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Repair and Restoration of Corrupted LZSS Files

Cited by 5 publications

References 24 publications

Cuckoo-Store Engine: A Reed–Solomon Code-Based Ledger Storage Optimization Scheme for Blockchain-Enabled IoT

Cuckoo-Store Engine: A Reed–Solomon Code-Based Ledger Storage Optimization Scheme for Blockchain-Enabled IoT

The Deep Learning Solutions on Lossless Compression Methods for Alleviating Data Load on IoT Nodes in Smart Cities

FPGA implementation of Lempel-Ziv data compression

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