Asynchronous Consensus Algorithm Integrating Dynamic Weight Sharding Strategy

XIONG Ao; ZHANG Wang; SONG Yu; WANG Dong; LI Da; GUO Qinglei; BAI Desheng

doi:10.23919/cje.2023.00.313

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Ao XIONG, Wang ZHANG, Yu SONG, et al., “Asynchronous Consensus Algorithm Integrating Dynamic Weight Sharding Strategy,” Chinese Journal of Electronics, vol. 33, no. 6, pp. 1–12, 2024 doi: 10.23919/cje.2023.00.313

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Ao XIONG, Wang ZHANG, Yu SONG, et al., “Asynchronous Consensus Algorithm Integrating Dynamic Weight Sharding Strategy,” Chinese Journal of Electronics, vol. 33, no. 6, pp. 1–12, 2024 doi: 10.23919/cje.2023.00.313

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Asynchronous Consensus Algorithm Integrating Dynamic Weight Sharding Strategy

doi: 10.23919/cje.2023.00.313

XIONG Ao^1
,,
ZHANG Wang^1
,,
SONG Yu^{1
,
,},
WANG Dong^2
,,
LI Da^2
,,
GUO Qinglei^2
,,
BAI Desheng^2
,

1.
State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China
2.
State Grid Blockchain Technology (Beijing) Co., Ltd, Beijing 100032, China

More Information

Author Bio:
Ao XIONG was born in Jiujiang, Jiangxi Province, China, in 1974. He received the Ph.D. degree in Computer Science from the Beijing University of Posts and Telecommunications (BUPT), Beijing, China, in 2013. He is currently an associate professor of the State Key Laboratory of Networking and Switching Technology in BUPT. He has authored about 30 SCI/EI index papers and received 14 national and provincial scientific and technical awards. His research interests include communication network and communication software, Internet routing and applications, and network management. (Email: xiongao@bupt.edu.cn)

Wang ZHANG was born in Siping, China, in 1997. He received the B.E degree in communication engineering from Central South University, China, in 2019, and a M.S degree in computer technology from Beijing University of Posts and Telecommunications, China, in 2023. He currently works at an artificial intelligence company in Beijing, China. His research interests include blockchain, consensus algorithms, and artificial intelligence. (Email: zhwang1997@bupt.cn)

Yu SONG was born in Henan Province, China, in 2000. She received her B.E degree from Beijing Information Science and Technology University in 2022. She is currently pursuing the Ph.D degree at Beijing University of Posts and Telecommunications. Her research interests include blockchain, and blockchain performance optimization. (Email: songyu@bupt.edu.cn)

Dong WANG received the master degree in Computer Science from the Beijing University of Posts and Telecommunications (BUPT), Beijing, China, in 2010. He is currently a director of Digital Innovation Department of State Grid Digital Technology Holding Co., Ltd., and a general manager of State Grid Blockchain Technology (Beijing) Co., Ltd. He has authored about 36 SCI/EI index papers and received 28 national and provincial scientific and technical awards. His research interests include electric power information communication, and blockchain. (Email: wangdong@sgdt.sgcc.com.cn)

Da LI received the M.S. degree in Computer Science from the Beijing University of Posts and Telecommunications (BUPT), Beijing, China, in 2010. He is currently a director of Digital Innovation Department of State Grid Digital Technology Holding Co., Ltd., and a general manager of State Grid Blockchain Technology (Beijing) Co., Ltd. He has authored about 36 SCI/EI index papers and received 28 national and provincial scientific and technical awards. His research interests include electric power information communication, and blockchain. (Email: lida@sgdt.sgcc.com.cn)

Qinglei GUO received the Ph.D. degree in Electrical Engineer from the Korea University, Seoul, Korea, in 2016. He is currently a senior engineer in the Blockchain Application Technology Laboratory of State Grid Corporation of China (SGCC). He has authored more than 40 SCI/EI index papers and received 10 national and provincial scientific and technical awards. His research interests include power system and its automation, digitalization of power grid, blockchain, etc.. (Email: guoqinglei@sgdt.sgcc.com.cn)

Desheng BAI received the B.S. degree in Electrical Engineer from the Zhejiang University, Zhejiang, China, in 2009. He is currently a senior engineer in the Blockchain Application Technology Laboratory of State Grid Corporation of China (SGCC). He has authored more than 30 SCI/EI index papers and received 10 national and provincial scientific and technical awards. His research interests include power system and its automation, digitalization of power grid, blockchain, etc.. (Email: baidesheng@sgdt.sgcc.com.cn)
Corresponding author: Email: songyu@bupt.edu.cn
Received Date: 2023-09-24
Accepted Date: 2024-02-21

Available Online: 2024-03-30

Abstract

Abstract

Blockchain technology has broad application prospects in many fields due to its unique characteristics such as decentralization, traceability, and non-tampering, and has become a research hotspot in recent years. As a key component of blockchain technology, the consensus algorithm is one of the important factors affecting blockchain performance. However, many consensus algorithms currently used in consortium chains are based on time assumptions and lack horizontal expansion capabilities. That is to say, the consensus algorithm cannot reach a consensus in an asynchronous network where the receiving time of network packets is uncertain, and its efficiency will decrease as the number of nodes increases, which hinders the large-scale application of the alliance chain. In order to solve the above problems, this paper proposes the DS-Dumbo algorithm, an asynchronous consensus algorithm that integrates dynamic sharding strategies, based on the currently excellent DumboBFT asynchronous consensus algorithm. The main work of this paper revolves around how to fragment and optimize the consensus process. This paper designs a node asynchronous sharding model based on multi-dimensional weights, so that the re-sharding work of each blockchain node can be executed concurrently with the asynchronous consensus algorithm, reducing the conflict between blockchain sharding and asynchronous consensus algorithms. We also designed an intelligent transaction placement strategy, which calculates the relevance score of each transaction for all shards to determine which shard the transaction is processed in order to reduce the number of complex cross-shard transactions. We optimized the execution process of the DumboBFT algorithm, converted its internal synchronous working mode to an asynchronous working mode, and reduced the consumption of consensus work to a certain extent. The experimental evaluation shows that the DS-Dumbo algorithm has higher throughput and lower delay than the DumboBFT algorithm, can increase the throughput with the increase of nodes, and has the ability of horizontal expansion.
- Blockchain,
- sharding technology,
- Asynchronous consensus

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References(26)

References

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