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BlockP2P: Enabling Fast Blockchain Broadcast with Scalable Peer-to-Peer Network Topology

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Green, Pervasive, and Cloud Computing (GPC 2019)

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Abstract

Blockchain technology offers an intelligent amalgamation of distributed ledger, Peer-to-Peer (P2P), cryptography, and smart contracts to enable trustworthy applications without any third parties. Existing blockchain systems have successfully either resolved the scalability issue by advancing the distributed consensus protocols from the control plane, or complemented the security issue by updating the block structure and encryption algorithms from the data plane. Yet, we argue that the underlying P2P network plane remains as an important but unaddressed barrier for accelerating the overall blockchain system performance. Our key insights from comparative assessments reveal the fact that P2P topology highly affects the broadcast speed of blockchain data, leading to poor performance and vulnerable to double spending attacks. In this paper, we introduce BlockP2P, a novel optimization design to accelerate broadcast efficiency and meanwhile retain the security. BlockP2P first operates the geographical proximity sensing clustering, which leverages K-Means algorithm for gathering proximity peer nodes into clusters. It follows by the hierarchical topological structure that ensures strong connectivity and small diameter based on node attribute classification. We finally propose the parallel spanning tree broadcast algorithm to enable fast data broadcast among nodes both in the intra- and inter- clusters. To clarify the influence of each tier, we carefully design and implement a blockchain network simulator. Evaluation results show that BlockP2P can exhibit promising performance compared to Bitcoin and Ethereum.

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Correspondence to Jiang Xiao .

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Hao, W. et al. (2019). BlockP2P: Enabling Fast Blockchain Broadcast with Scalable Peer-to-Peer Network Topology. In: Miani, R., Camargos, L., Zarpelão, B., Rosas, E., Pasquini, R. (eds) Green, Pervasive, and Cloud Computing. GPC 2019. Lecture Notes in Computer Science(), vol 11484. Springer, Cham. https://doi.org/10.1007/978-3-030-19223-5_16

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  • DOI: https://doi.org/10.1007/978-3-030-19223-5_16

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-19222-8

  • Online ISBN: 978-3-030-19223-5

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