Abstract
Block synchronization is an essential component of blockchain systems. Traditionally, blockchain systems tend to send all the transactions from one node to another for synchronization. However, such a method may lead to an extremely high network bandwidth overhead and significant transmission latency. It is crucial to speed up such a block synchronization process and save bandwidth consumption. A feasible solution is to reduce the amount of data transmission in the block synchronization process between any pair of peers. However, existing methods based on the Bloom filter or its variants still suffer from multiple roundtrips of communications and significant synchronization delay. In this paper, we propose a novel protocol named Gauze for fast block synchronization. It utilizes the Cuckoo filter (CF) to discern the transactions in the receiver’s mempool and the block to verify, providing an efficient solution to the problem of set reconciliation in the P2P (Peer-to-Peer Network) network. By up to two rounds of exchanging and querying the CFs, the sending node can acknowledge whether the transactions in a block are contained by the receiver’s mempool or not. Based on this message, the sender only needs to transfer the missed transactions to the receiver, which speeds up the block synchronization and saves precious bandwidth resources. The evaluation results show that Gauze outperforms existing methods in terms of the average processing latency (about 10× lower than Graphene) and the total synchronization space cost (about 10× lower than Compact Blocks) in different scenarios.
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This work was supported in part by the National Natural Science Foundation of China (Grant No. 62032017).
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Xiaoqiang Ding is currently pursuing his MS degree from the College of Intelligence and Computing, Tianjin University, China. His research interests include data structure, distributed networking systems, and blockchain.
Liushun Zhao received his BE degree in communications engineering from Harbin Engineering University, China in 2018. From 2018, He continues to pursue his PhD degree in the School of Computer Science and Technology, Xidian University, China. His research interest focuses on security supervision in the operation process of blockchain.
Lailong Luo received the BS, MS, and PhD degrees from the College of Systems Engineering, National University of Defense Technology, China in 2013, 2015 and 2019, respectively. He is currently a lecturer in the College of Systems Engineering, National University of Defense Technology, China. His research interests include data structure and distributed networking systems.
Junjie Xie received the BE degree in computer science and technology from the Beijing Institute of Technology, China in 2013. He received the MS and PhD degrees in management science and engineering from the National University of Defense Technology, China in 2015 and 2020, respectively. He is currently an engineer with the Institute of Systems Engineering, AMS, PLA, Beijing, China. His research interests include distributed systems, software-defined networking, and mobile edge computing.
Deke Guo received the BS degree in industry engineering from the Beihang University, China in 2001, and the PhD degree in management science and engineering from the National University of Defense Technology, China, in 2008. He is currently a professor with the College of Systems Engineering, National University of Defense Technology, China. His research interests include distributed systems, software-defined networking, data center networking, wireless and mobile systems, and interconnection networks. He is a senior member of the IEEE and a member of the ACM.
Jinxi Li is currently pursuing his MS degree from the College of Intelligence and Computing, Tianjin University, China. His research interests include edge computing and network function virtualization.
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Ding, X., Zhao, L., Luo, L. et al. Gauze: enabling communication-friendly block synchronization with cuckoo filter. Front. Comput. Sci. 17, 173403 (2023). https://doi.org/10.1007/s11704-022-1685-5
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DOI: https://doi.org/10.1007/s11704-022-1685-5