Journal of Jilin University(Engineering and Technology Edition) ›› 2022, Vol. 52 ›› Issue (3): 684-692.doi: 10.13229/j.cnki.jdxbgxb20200005

Previous Articles    

Optimization of consensus algorithm for drug detection block chain based on cultural genetic algorithm

Bin-xiang JIANG1,2,3(),Tong-tong JIANG1,Yong-lei WANG4   

  1. 1.School of Information and Electrical Engineering,Shandong Jianzhu University,Jinan 250101,China
    2.Juvenile Crime & Justice Research Center,China University of Political Science & Law,Beijing 100088,China
    3.Institute of Computational Psychology,Shandong University,Jinan 250101,China
    4.AI Research Institute of Hunan Enht Technology Co. ,Ltd. ,Qingdao 266000,China
  • Received:2020-12-31 Online:2022-03-01 Published:2022-03-08

Abstract:

At present, China's drug testing laboratories conduct their own tests independently, and there is no information exchange between the laboratories, forming a large number of drug testing information islands, which hindrance the problem of drug testing data sharing and research and early warning of parallel cases. This paper proposes to use alliance chain to solve the data sharing of drug testing laboratories, and analyzes the problem of consensus algorithm of drug testing alliance Block chain. Aiming at the consensus algorithm problem, this paper proposes to optimize the consensus algorithm of drug testing blockchain based on Cultural Genetic Algorithm. Firstly, Genetic Algorithm (GA) is modified to form efficient HGA algorithm based on Hash function. Then, an efficient Cultural Genetic algorithm CHGA is formed by introducing Cultural Algorithm to transform HGA. Then combining Pareto multi-objective optimization technology to improve the efficient multi-objective optimization Cultural Genetic Algorithm PCHGA algorithm, and using PCHGA algorithm to solve the Byzantine fault-tolerant consensus algorithm, the formation of multi-objective optimization cultural genetic algorithm practical Byzantine algorithm PCHGA-PBFT. The problem of consensus node candidate set and primary node election of PBFT is solved with the algorithm above, and the available algorithm of PBFT consensus optimization is obtained.The simulation results show that the proposed algorithm achieves the desired results in the selection of consensus nodes and primary nodes.

Key words: alliance block chain, drug testing, PBFT algorithm, cultural genetic algorithm, Hash function, multi-objective optimization

CLC Number: 

  • TP393

Fig.1

Flow of PBFT algorithm"

Fig.2

Hash genetic algorithm HGA"

Fig.3

Cultural genetic algorithm CHGA"

Fig.4

Genetic coding of chromosomes"

Fig.5

Multi-objective decision"

Fig.6

Multi-objective cultural genetic algorithmPCHGA-PBFT"

Fig.7

PCHGA-PBFT consensus node set"

Fig.8

PCHGA-PBFTprimary node election"

Fig.9

PCHGA-PBFT consensus node optimization"

Fig.10

PCHGA-PBFT consensus trading delay time"

Fig.11

PCHGA-PBFT transaction throughput"

1 王日宏,张立锋,徐泉清,等. 可应用于联盟链的拜占庭容错共识算法[J].计算机应用研究, 2020, 37(11):3382-3386.
Wang Ri-hong, Zhang Li-feng, Xu Quan-qing,et al. Byzantine fault tolerance algorithm for consortium blockchain[J]. Application Research of Computers,2020, 37(11): 3382-3386.
2 王壹铭,初剑峰,王永军,等. 基于有向无环图的高效区块链共识算法[J].吉林大学学报:理学版,2020,58(5):1167-1172.
Wang Yi-ming, Chu Jian-feng, Wang Yong-jun,et al. Efficient blockchain consensus algorithm based on directed acyclic graph[J]. Journal of Jilin University(Science Edition), 2020,58(5): 1167-1172.
3 李铁克,王伟玲,张文学. 基于文化遗传算法求解柔性作业车间调度问题[J]. 计算机集成制造系统,2010,16(4):861-866.
Li Tie-ke, Wang Wei-ling, Zhang Wen-xue. Solving flexible Job Shop scheduling problem based on cultural genetic algorithm[J]. Computer Integrated Manufacturing Systems,2010, 16(4):861-866.
4 兰海燕,杨莘元,刘海波,等. 基于文化算法的多用户OFDM系统资源分配[J].吉林大学学报:工学版, 2011,41(1):226-230.
Lan Hai-yan, Yang Xin-yuan, Liu Hai-bo, et al. Resource allocation for multiuser OFDM system based on cultural algorithm[J]. Journal of Jilin University(Engineering and Technology Edition), 2011,41(1): 226-230.
5 景沈艳,孙吉贵,张永刚. 用遗传算法求解调度问题[J]. 吉林大学学报:理学版,2002,40(3):263-267.
Jing Shen-yan, Sun Ji-gui, Zhang Yong-gang. Solving scheduling problems with genetic algorithm[J]. Journal of Jilin University(Science Edition), 2002, 40(3): 263-267.
6 曹阳,刘亚军,俞琰,等. 基于遗传-蚁群算法的云计算任务调度优化[J]. 吉林大学学报:理学版,2016,54(5):1077-1081.
Cao Yang, Liu Ya-jun, Yu Yan, et al. Task scheduling and optimization of cloud computeing based on genetic algorithm and ant colony algorithm[J]. Journal of Jilin University(Science Edition), 2016, 54(5): 1077-1081.
7 闫盼,谭瑛,张建华. 一种用于进化算法历史计算数据的高效利用方法[J].计算机工程与科学,2016,38(1):62-66.
Yan Pan, Tan Ying, Zhang Jian-hua. A method of using historical calculation data efficiently in evolutionary algorithms[J]. Computer Engineering & Science, 2016, 38(1):62-66.
8 李宾,刘淑媛,刘衍珩. 基于散列表的快速分组分类算法[J]. 吉林大学学报:理学版,2005,43(6):787-793.
Li Bin, Liu Shu-yuan, Liu Yan-heng. FastPacketC lassification algorithm based on hash table[J]. Journal of Jilin University(Science Edition), 2005, 43(6): 787-793.
9 Kacem I, Hammadi S, Borne P. Pareto-optimality approach for flexible Job-Shop scheduling problems: hybridization of evolutionary algorithms and fuzzy logic[J]. Mathematics and Computers in Simulation, 2002, 60(3-5):245-276.
10 刘萌伟, 黎夏. 基于Pareto多目标遗传算法的公共服务设施优化选址研究——以深圳市医院选址为例[J].热带地理,2010,30(6):650-655.
Liu Meng-wei, Li Xia. A pareto genetic algorithm for multi-objective site search problem:a case study on hospital location in Shenzhen city[J]. Tropical Geography, 2010, 30(6):650-655.
11 孙冲,李文辉. 基于搜索空间自适应分割的多目标粒子群优化算法[J]. 吉林大学学报:理学版,2019,57(2):345-351.
Sun Chong, Li Wen-hui. Multi-objective particle swarm optimization algorithm based on self-adaption partition of search space[J]. Journal of Jilin University(Science Edition), 2019, 57(2):345-351.
12 刘华蓥,王静,许少华,等. 基于空间划分树的多目标粒子群优化算法[J]. 吉林大学学报:理学版,2011,49(4):696-702.
Liu Hua-ying, Wang Jing, Xu Shao-hua, et al. Multi-objective particle swarm optimization algorithm based on spatial partition tree[J]. Journal of Jilin University(Science Edition), 2011,49(4):696-702.
13 张强,朱刘涛,王颖. 基于文化混洗蛙跳算法求解连续空间优化问题[J] .吉林大学学报:理学版,2020,58(6):1443-1451.
Zhang Qiang, Zhu Liu-tao, Wang Ying. Cultural shuffled frog leaping algorithm for contionuous space optimization problem[J]. Journal of Jilin University(Science Edition), 2020,58(6): 1443-1451.
[1] Li-jie ZHANG,Xi-ta A,Xiao TIAN,Wen LI. Multi⁃objective optimization design of accelerated degradation test based on Gamma process [J]. Journal of Jilin University(Engineering and Technology Edition), 2022, 52(2): 361-367.
[2] Bao-feng SUN,Xin-xin REN,Zai-si ZHENG,Guo-yi Li. Multi⁃objective flow shop optimal scheduling considering worker's load [J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(3): 900-909.
[3] Bing-hai ZHOU,Zhao-xu HE. Static semi⁃kitting strategy⁃based multi⁃objective just⁃in⁃time material distribution scheduling [J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(3): 910-916.
[4] Ji-cheng HUANG,Cheng SHEN,Ai-min JI,Xian-wang LI,Bin ZHANG,Kun-peng TIAN,Hao-lu LIU. Optimization of cutting⁃conveying key working parameters of hemp harvester [J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(2): 772-780.
[5] Bing-hai ZHOU,Qiong WU. Balancing and bi⁃objective optimization of robotic assemble lines [J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(2): 720-727.
[6] Fang-wu MA,Li HAN,Liang WU,Jin-hang LI,Long-fan YANG. Damping optimization of heavy⁃loaded anti⁃vibration platform based on genetic algorithm and particle swarm algorithm [J]. Journal of Jilin University(Engineering and Technology Edition), 2020, 50(5): 1608-1616.
[7] Xue-shen CHEN,Tao CHEN,Tao WU,Xu MA,Ling-chao ZENG,Lin-tao CHEN. Design and experiment on harvester for winter planting potato of straw coverage [J]. Journal of Jilin University(Engineering and Technology Edition), 2020, 50(2): 749-757.
[8] Yin-ping LI,Tian-xu JIN,Li LIU. Design and dynamic characteristic simulation of pantograph⁃catenary continuous energy system for pure electric LHD [J]. Journal of Jilin University(Engineering and Technology Edition), 2020, 50(2): 454-463.
[9] Fang-wu MA,Hong-yu LIANG,Ying ZHAO,Meng YANG,Yong-feng PU. Multi⁃objective crashworthiness optimization design of concave triangles cell structure with negative Poisson′s ratio [J]. Journal of Jilin University(Engineering and Technology Edition), 2020, 50(1): 29-35.
[10] Zhong-yi CAI,Fan-xiang MENG,Qing-min CHEN,Xuan ZHAO. Preform optimization for near-net-shape forming process of complex knuckle forging [J]. Journal of Jilin University(Engineering and Technology Edition), 2020, 50(1): 84-90.
[11] Fu-chun JIA,Xian-jie MENG,Yu-long LEI. Optimal design of two degrees of freedom dynamic vibration absorber based on multi-objective genetic algorithm [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(6): 1969-1976.
[12] Bin-bin YU,Liang HU,Ling CHI. Digital signature scheme against internal and external attack for wireless sensor networks [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(5): 1676-1681.
[13] QIU Xiao-ming, WANG Yin-xue, YAO Han-wei, FANG Xue-qing, XING Fei. Multi-objective optimization of resistance spot welding parameters for DP1180/DP590 using grey relational analysis based Taguchi [J]. 吉林大学学报(工学版), 2018, 48(4): 1147-1152.
[14] WANG Deng-feng, ZHANG Shuai, WANG Yong, CHEN Hui. Optimization design of assembled wheel based on performance of fatigue and 13° impact [J]. 吉林大学学报(工学版), 2018, 48(1): 44-56.
[15] YU Fan-hua, LIU Ren-yun, ZHANG Yi-min, ZHANG Xiao-li, SUN Qiu-cheng. Swarm intelligence algorithm of dynamic reliability-based robust optimization design of mechanic components [J]. 吉林大学学报(工学版), 2017, 47(6): 1903-1908.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!