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                    Hyperledger Fabric共識機制優化方案

                    孟吳同 張大偉

                    孟吳同,  張大偉.  Hyperledger fabric共識機制優化方案.  自動化學報,  2021,  47(8): 1885?1898 doi: 10.16383/j.aas.c190516
                    引用本文: 孟吳同,  張大偉.  Hyperledger fabric共識機制優化方案.  自動化學報,  2021,  47(8): 1885?1898 doi: 10.16383/j.aas.c190516
                    Meng Wu-Tong,  Zhang Da-Wei.  Optimization scheme for hyperledger fabric consensus mechanism.  Acta Automatica Sinica,  2021,  47(8): 1885?1898 doi: 10.16383/j.aas.c190516
                    Citation: Meng Wu-Tong,  Zhang Da-Wei.  Optimization scheme for hyperledger fabric consensus mechanism.  Acta Automatica Sinica,  2021,  47(8): 1885?1898 doi: 10.16383/j.aas.c190516

                    Hyperledger Fabric共識機制優化方案

                    doi: 10.16383/j.aas.c190516
                    基金項目: 國家留學基金(201807095023)資助
                    詳細信息
                      作者簡介:

                      孟吳同:北京交通大學碩士研究生. 2017年獲得河北大學網絡工程學士學位. 主要研究方向為區塊鏈.E-mail: mengwt@bjtu.edu.cn

                      張大偉:北京交通大學計算機與信息技術學院副教授. 2004年獲得北京航空航天大學通信與信息系統專業博士學位. 主要研究方向為區塊鏈, 安全協議, 可信計算. 本文通信作者.E-mail: dwzhang@bjtu.edu.cn

                    Optimization Scheme for Hyperledger Fabric Consensus Mechanism

                    Funds: Supported by China Scholarship Council (201807095023)
                    More Information
                      Author Bio:

                      MENG Wu-Tong Master student at the School of Computer and Information Technology, Beijing Jiaotong University. He received his bachelor degree in network engineering from Hebei University in 2017. His main research interest is blockchain

                      ZHANG Da-Wei Associate professor at the School of Computer and Information Technology, Beijing Jiaotong University. He received his Ph. D. degree in communication and information system from Beihang University in 2004. His research interest covers blockchain, security protocol and trusted computing. Corresponding author of this paper

                    • 摘要:

                      針對Hyperledger Fabric使用固定背書節點處理交易所帶來的安全風險和性能瓶頸問題, 提出了一種非交互、可驗證的隨機化背書節點優化方案. 基于“背書?排序?驗證”的Hyperledger fabric共識模型, 引入背書節點候選集, 使用可驗證隨機函數隨機抽取背書節點進行交易背書, 實現了背書節點的非交互式可驗證隨機選取和背書過程的并行處理. 分析和實驗表明, 優化后的共識機制具有更高的安全性和更快的交易處理速度.

                    • 圖  1  Hyperledger fabric共識機制

                      Fig.  1  Hyperledger fabric consensus mechanism

                      圖  2  優化后的Hyperledger fabric共識機制

                      Fig.  2  Optimized hyperledger fabric consensus mechanism

                      圖  3  敵手攻擊成功的概率

                      Fig.  3  Probability of successful enemy attack

                      圖  4  實驗網絡拓撲圖

                      Fig.  4  Network topology of experiment

                      圖  5  原有方案與優化方案交易時間對比

                      Fig.  5  The comparison of transaction time between original scheme and optimized scheme

                      圖  6  原有方案與優化方案交易延遲對比

                      Fig.  6  The comparison of transaction delay between original scheme and optimized scheme

                      圖  7  原有方案與優化方案通信成本對比

                      Fig.  7  The comparison of communication cost between original scheme and optimization scheme

                      表  1  優化方案與其他共識機制的對比

                      Table  1  Comparison of optimization scheme with other consensus mechanisms

                      共識機制 VRF 的作用 共識原理 資源消耗 容錯能力
                      Algorand 出塊節點的選取 VRF + PBFT $3f+1$
                      Definity 出塊節點的選取 VRF + PoS 較高 $2f+1$
                      Ouroboros Praos 出塊節點的選取 VRF + PoS 較高 $2f+1$
                      優化方案 背書節點的選取 VRF + 背書 + 排序 + 驗證 F($m,t$)
                      下載: 導出CSV

                      表  2  敵手攻擊成功次數

                      Table  2  Number of successful attacks by adversary

                      交易次數 敵手成功次數 攻擊成功概率
                      原始方案 1 000 1 000 100 %
                      優化方案 100 000 686 6.86 %
                      下載: 導出CSV

                      表  3  無背書節點情況發生次數

                      Table  3  Frequency of nonoccurence of endorsing peer

                      交易次數 是否使用計時重傳 無背書節點情況發生次數
                      1 000 2
                      100 000 17
                      1 000 0
                      100 000 0
                      下載: 導出CSV

                      表  4  可驗證隨機函數各部分算法運行時間

                      Table  4  Running time of each part of the VRF algorithm

                      算法 次數 總時間 (ms) 平均時間 (ms)
                      生成密鑰 10000 2878.3546 0.2878
                      生成隨機數和證明 10000 10395.3927 1.0395
                      驗證隨機數和證明 10000 12874.6190 1.2875
                      下載: 導出CSV
                      360彩票
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                    • 收稿日期:  2019-07-07
                    • 錄用日期:  2019-12-15
                    • 網絡出版日期:  2020-01-20
                    • 刊出日期:  2021-08-20

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