Blockchain Fragment Expansion Scheme Based on Community Detection and MSR Code
Authors: 
Sheping Zhai, Tong Tong, Xifang BaiAuthors Info & Claims
Sheping Zhai, Tong Tong, Xifang BaiAuthors Info & ClaimsPages 1146 - 1152
Abstract
Aiming at the current performance of blockchain system can not meet the actual needs of high-frequency data interaction in the era of information explosion, a blockchain fragment expansion scheme based on community detection and MSR code is proposed. Firstly, based on the random walk community detection algorithm and the blockchain node network, a node grouping method is proposed. Each group of nodes maintains a copy of the blockchain ledger to reduce the storage redundancy of blockchain. Secondly, the block data is divided by minimum storage regenerating codes (MSR), which further reduces the storage pressure of nodes, reduces the amount of data required for block requests, and reduces network pressure. Finally, a blockchain scalable fragment storage scheme is proposed. The simulation experiment and result analysis show that the blockchain fragment expansion scheme based on community detection and MSR has improved in terms of storage scalability, response efficiency and fault tolerance.
References
[1]
Sun Zhixin, Zhang Xin, Xiang Feng, and Chen Lu. 2021. Survey of Storage Scalability on Blockchain. Journal of Software, 32, 01 (January 2021), 1-20. https://doi.org/10.13328/j.cnki.jos.006111
[2]
Jia Linpeng, Pei Qi, Wang Xin, Zhang Hanwen, Yu Lei, Zhang Jun, and Sun Yi. 2022. Survey on Off-chain Channel Routing Algorithm. Journal of Software, 33, 01, 233-253. https://doi.org/10.13328/j.cnki.jos.006219
[3]
Pan Chen, Liu Zhiqiang, Liu Zhen, and Long Yu. 2018. Research on Scalability of Blockchain Technology: Problems and Methods. Journal of Computer Research and Development, 55, 10, 2099-2110. https://doi.org/10.7544/issn1000-1239.2018.20180440
[4]
Asutosh Palai, Meet Vora, and Aashaka Shah. 2018. Empowering Light Nodes in Blockchains with Block Summarization. In Proceedings of the 9th IFIP International Conference on New Technologies, Mobility and Security. IEEE, Piscataway, NJ, 1-5. https: //doi.org/ 10.1109/NTMS.2018.8328735.
[5]
Ulfah Nadiya, Kusprasapta Mutijarsa, and Cahyo Y. Rizqi. 2018. Block Summarization and Compression in Bitcoin Blockchain. In Proceedings of the 2018 International Symposium on Electronics and Smart Devices (ISESD). IEEE, Piscataway, NJ, 1-4. https: //doi.org/10.1109/ISESD.2018.8605487.
[6]
Doriane Perard, Jérôme Lacan, Yann Bachy, and Jonathan Detchart. 2018. Erasure Code-Based Low Storage Blockchain Node. In Proceedings of the 2018 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber. IEEE, Piscataway, NJ, 1622-1627. https: //doi.org/ 10.1109/ Cybermatics_2018. 2018.00271
[7]
Ryosuke Abe, Shigeya Suzuki, and Jun Murai. 2018. Mitigating Bitcoin Node Storage Size By DHT. In Proceedings of the Proceedings of the 2018 Asian Internet Engineering Conference. ACM, New York, NY, USA, 17-23. https: //doi.org/10.1145/3289166.3289169
[8]
Yudai Kaneko and Takuya Asaka. 2018. DHT Clustering for Load Balancing Considering Blockchain Data Size. In Proceedings of the 2018 Sixth International Symposium on Computing and Networking Workshops (CANDARW). IEEE, Piscataway, NJ, 71-74. https: //doi.org/ 10.1109/CANDARW.2018.00022
[9]
Teasung Kim, Jaewon Noh, and Sunghyun Cho. 2019. SCC: Storage Compression Consensus for Blockchain in Lightweight IoT Network. In Proceedings of the 2019 IEEE International Conference on Consumer Electronics (ICCE). IEEE, Piscataway, NJ, 1-4. https: //doi.org/10.1109/ ICCE.2019.8662032
[10]
Zihuan Xu, Siyuan Han, and Lei Chen. 2018. CUB, a Consensus Unit-Based Storage Scheme for Blockchain System. In Proceedings of the 2018 IEEE 34th International Conference on Data Engineering (ICDE). IEEE, Piscataway, NJ, 173-184. https: //doi.org/10.1109/ICDE.2018.00025
[11]
Michelle Girvan, and M. E. J. Newman. 2002. Community structure in social and biological networks. Proc Natl Acad U S A, 99, 12, 7821-7826. https: //doi.org/10.1073/pnas.122653799
[12]
Vincent D. Blondel, Jean-Loup Guillaume, Renaud Lambiotte, and Etienne Lefebvre. 2008. Fast unfolding of communities in large networks. Journal of Statistical Mechanics Theory & Experiment (July 2008), 1-12. https: //doi.org/10.1088/1742-5468/2008/10/p10008
[13]
Martin Rosvall and Carl T. Bergstrom. 2008. Maps of Random Walks on Complex Networks Reveal Community Structure. Proceedings of the National Academy of Sciences, 105, 4, 1118-1123. https: //doi.org/10.1073/pnas.0706851105
[14]
Zhang Junxiang, Li Shuqin, and Liu Bin. 2020. Sparse autoencoder community recognition algorithm based on smoothed l1 norm. Application Research of Computers, 37, 4 (April 2020), 1063-1068. https: //doi.org/10.19734/j.issn.1001-3695.2018.09.0743
[15]
He Jing, Wang Zhixiao, Hou Mengnan, Rui Xiaobin, and Gao Juyuan. 2019. Incremental dynamic community detection algorithm based on topology potential. Computer Engineering and Design, 40, 1 (January 2019), 45-52. https: //doi.org/10.16208/j.issn1000-7024.2019.01.008
[16]
Michael G. Luby, Michael Mitzenmacher, M. Amin Shokrollahi, and Daniel A. Spielman. 2001. Efficient erasure correcting codes. IEEE Transactions on Information Theory, 47, 2 (February 2001), 569-584. https: //doi.org/ 10.1109/18.910575
[17]
Jeremy C W Chan, Qian Ding, Patrick P C Lee, and Helen H W Chan. 2014. Parity Logging with Reserved Space: Towards Efficient Updates and Recovery in Erasure-Coded Clustered Storage. In Proceedings of the 12th USENIX Conference on File and Storage Technologies. ACM, New York, NY, USA, 163-176. https: //doi.org/10.5555/2591305.2591321
[18]
Zhirong Shen, Patrick P. C. Lee, Jiwu Shu, and Wenzhong Guo. 2017. Correlation-Aware Stripe Organization for Efficient Writes in Erasure-Coded Storage Systems. In Proceedings of the 2017 IEEE 36th Symposium on Reliable Distributed Systems (SRDS). IEEE, Piscataway, NJ, 134-143. https: //doi.org/10.1109/SRDS.2017.18
[19]
Kyumars Sheykh Esmaili, Aatish Chiniah, and Anwitaman Datta. 2013. Efficient updates in cross-object erasure-coded storage systems. In Proceedings of the 2013 IEEE International Conference on Big Data. IEEE, Piscataway, NJ, 28-32. https: //doi.org/10.1109/BigData.2013.6691658
[20]
Li Jie, Tang Xiaohu, and Parampalli U. 2015. A framework of constructions of minimal storage regenerating codes with the optimal access/update property. IEEE Transactions on Information Theory, 61, 4 (April 2015), 1920-1932. https: //doi.org/10.1109/TIT.2015.2408600
Index Terms
- Blockchain Fragment Expansion Scheme Based on Community Detection and MSR Code
Recommendations
A Community Detection-Based Blockchain Sharding Scheme
Blockchain – ICBC 2022AbstractSharding has been considered a promising approach to improving blockchain scalability. However, multiple shards result in a large number of cross-shard transactions, which require a long confirmation time across shards and thus restrain the ...
Comments
Information & Contributors
Information
Published In
September 2022
1221 pages
ISBN:9781450396899
DOI:10.1145/3573942
Copyright © 2022 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 16 May 2023
Check for updates
Qualifiers
- Research-article
- Research
- Refereed limited
Conference
AIPR 2022
AIPR 2022: 2022 5th International Conference on Artificial Intelligence and Pattern Recognition
September 23 - 25, 2022
Xiamen, China
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 22Total Downloads
- Downloads (Last 12 months)7
- Downloads (Last 6 weeks)2
Reflects downloads up to 01 Mar 2025
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inFull Access
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderHTML Format
View this article in HTML Format.
HTML Format