Comparative Study of Erasure Code in Distributed Systems and Blockchain

Authors

  • Yuewen Xu

DOI:

https://doi.org/10.54097/b604xe74

Keywords:

Erasure Code; Distributed Systems; Blockchain.

Abstract

As the data generated by various applications continues to grow exponentially, the need for efficient methods of storage and transmission increases. Erasure codes offer a promising solution by providing redundant information without completely recreating the data. Although erasure codes have been extensively studied, their integration and effectiveness in distributed systems and blockchain networks are still being explored. This paper explores and compares the foundations and applications of erasure codes in distributed systems and blockchain networks, and provides a comprehensive literature review of erasure code implementations and their impact on data storage and transmission. This study explores the foundations of erasure codes in distributed systems, including array and RS codes, and LDPC codes. The study also explores the use of erasure codes in distributed systems and blockchain and analyzes how these codes can improve the efficiency and scalability of decentralized storage solutions. The study examines the strengths and weaknesses of different erasure codes based on analysis and comparisons. The findings highlight the potential of erasure codes to revolutionize data storage and transmission in distributed systems and blockchain networks.

Downloads

Download data is not yet available.

References

StoneFly. Understanding erasure coding and its difference with RAID. StoneFly Blog, 2023.

Liu K, Peng J, Wang J, et al. Adaptive and scalable caching with erasure codes in Distributed Cloud-edge storage systems. IEEE Transactions on Cloud Computing, 2022, 11(2): 1840–1853. DOI:10.1109/tcc.2022.3168662.

Tang D, Wang Y, Yang H. Array Erasure Codes with Preset Fault Tolerance Capability. International Jounrnal Netw. Secur., 2018, 20(1): 193-200.

Wang Z, Dimakis A G, Bruck J. Rebuilding for array codes in distributed storage systems. IEEE Globecom Workshops, 2010: 1905-1909.

Corbett P, English B, Goel A, et al. Row-diagonal parity for double disk failure correction. Proceedings of the 3rd USENIX Conference on File and Storage Technologies, 2004: 1-14.

Borwankar S, Shah D. Low Density Parity Check Code (LDPC Codes) Overview. ArXiv preprint, 2022.

Shannon C E. A mathematical theory of communication. The Bell system technical journal, 1948, 27(3): 379-423.

Vora M N. Hadoop-HBase for large-scale data. Proceedings of 2011 International Conference on Computer Science and Network Technology, 2011, 1: 601-605.

XU Dongxu. Application of erasure coding in distributed fault-tolerant storage. Computer CD Software and Application, 2013, 16(03):103-104.

Lin W K, Chiu D M, Lee Y B. Erasure code replication revisited. Proceedings. Fourth International Conference on Peer-to-Peer Computing, 2004: 90-97.

Furong Yin, Chengyu Zhu, Bin Z. Erasure code partition storage based on the CITA blockchain. Journal of East China Normal University (Natural Science), 2021, 2021(5): 48.

Perard D, Lacan J, Bachy Y, et al. Erasure code-based low storage blockchain node. IEEE International Conference on Internet of Things and IEEE Green Computing and Communications and IEEE Cyber, Physical and Social Computing and IEEE Smart Data, 2018: 1622-1627.

Balaji S B, Krishnan M N, Vajha M, et al. Erasure coding for distributed storage: An overview. Science China Information Sciences, 2018, 61: 1-45.

Downloads

Published

26-01-2024

How to Cite

Xu, Y. (2024). Comparative Study of Erasure Code in Distributed Systems and Blockchain. Highlights in Science, Engineering and Technology, 81, 512-518. https://doi.org/10.54097/b604xe74