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FPSblo: A Blockchain Network Transmission Model Utilizing Farthest Point Sampling.

Authors :
Longle Cheng
Xiru Li
Shiyu Fang
Wansu Pan
He Zhao
Haibo Tan
Xiaofeng Li
Source :
Computers, Materials & Continua; 2024, Vol. 78 Issue 2, p2491-2509, 19p
Publication Year :
2024

Abstract

Peer-to-peer (P2P) overlay networks provide message transmission capabilities for blockchain systems. Improving data transmission efficiency in P2P networks can greatly enhance the performance of blockchain systems. However, traditional blockchain P2P networks face a common challenge where there is often amismatch between the upperlayer traffic requirements and the underlying physical network topology. This mismatch results in redundant data transmission and inefficient routing, severely constraining the scalability of blockchain systems. To address these pressing issues, we propose FPSblo, an efficient transmission method for blockchain networks. Our inspiration for FPSblo stems from the Farthest Point Sampling (FPS) algorithm, a well-established technique widely utilized in point cloud image processing. In this work, we analogize blockchain nodes to points in a point cloud image and select a representative set of nodes to prioritizemessage forwarding so that messages reach the network edge quickly and are evenly distributed. Moreover, we compare ourmodel with theKadcast transmissionmodel, which is a classic improvementmodel for blockchain P2P transmission networks, the experimental findings show that the FPSblo model reduces 34.8% of transmission redundancy and reduces the overload rate by 37.6%. By conducting experimental analysis, the FPS-BTmodel enhances the transmission capabilities of the P2P network in blockchain. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15462218
Volume :
78
Issue :
2
Database :
Complementary Index
Journal :
Computers, Materials & Continua
Publication Type :
Academic Journal
Accession number :
175815023
Full Text :
https://doi.org/10.32604/cmc.2024.047166