A coin selection strategy based on the greedy and genetic algorithm

被引:2
|
作者
Wei, Xuelin [1 ]
Wu, Chang [1 ]
Yu, Haoran [1 ]
Liu, Siyan [1 ]
Yuan, Yihong [2 ]
机构
[1] Univ Elect Sci & Technol China, Sch Informat & Commun Engn, 2006 Xiyuan Ave, Chengdu, Peoples R China
[2] Univ Sydney, Sch Comp Sci & Engn, Sydney, NSW, Australia
关键词
Coin selection; UTXO; Bitcoin transaction; Block size; Greedy algorithm; Genetic algorithm;
D O I
10.1007/s40747-022-00799-2
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Coin selection method refers to the process undergone when selecting a set of unspent transaction outputs (UTXOs) from a cryptocurrency wallet or account to use as inputs in each transaction. The most applied coin selection method that UTXO-based cryptocurrencies currently employ is an algorithm that decides on a certain set of UTXOs that matches the target amount and limits the transaction fee. However this approach trades off favourable maintenance overhead of the entire network for low transaction fees, as many low-value UTXOs known as "dust" is produced. Over time, this will impact the scalability and management of the cryptocurrency network as the global set of UTXOs become larger. Therefore, there is an urgency to find a higher-performing coin selection method suitable for UTXO-based cryptocurrencies. This paper proposes a method based on the greedy and genetic algorithm for effectively choosing sets of UTXOs in Bitcoin. The main objective of this coin selection strategy is to get as close as possible to the target while also maintaining and possibly reducing the number of UTXO inputs.
引用
收藏
页码:421 / 434
页数:14
相关论文
共 50 条
  • [1] A coin selection strategy based on the greedy and genetic algorithm
    Xuelin Wei
    Chang Wu
    Haoran Yu
    Siyan Liu
    Yihong Yuan
    Complex & Intelligent Systems, 2023, 9 : 421 - 434
  • [2] Data Source Selection Based on an Improved Greedy Genetic Algorithm
    Yang, Jian
    Xing, Chunxiao
    SYMMETRY-BASEL, 2019, 11 (02):
  • [3] Genetic algorithm based on Greedy strategy in the 0-1 Knapsack Problem
    Zhao, JiangFei
    Huang, Tinglei
    Pang, Fei
    Liu, YuanJie
    THIRD INTERNATIONAL CONFERENCE ON GENETIC AND EVOLUTIONARY COMPUTING, 2009, : 105 - 107
  • [4] A Random Search and Greedy Selection based Genetic Quantum Algorithm for Combinatorial Optimization
    Pavithr, R. S.
    Gursaran
    2013 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2013, : 2422 - 2427
  • [5] The optimization selection of tests based on greedy algorithm
    Liu, Jian-Min
    Liu, Yuan-Hong
    Feng, Fu-Zhou
    Jiang, Peng-Cheng
    Binggong Xuebao/Acta Armamentarii, 2014, 35 (12): : 2109 - 2115
  • [6] A Particle Swarm Optimization Algorithm Based on Genetic Selection Strategy
    Tang, Qin
    Zeng, Jianyou
    Li, Hui
    Li, Changhe
    Liu, Yong
    ADVANCES IN NEURAL NETWORKS - ISNN 2009, PT 3, PROCEEDINGS, 2009, 5553 : 126 - +
  • [7] A Genetic Algorithm based Peer Selection Strategy for BitTorrent Networks
    Wu, Tiejun
    Li, Maozhen
    Ponraj, Mahesh
    Qi, Man
    2009 WORLD CONGRESS ON NATURE & BIOLOGICALLY INSPIRED COMPUTING (NABIC 2009), 2009, : 335 - +
  • [8] Improved genetic algorithm based on greedy and simulated annealing ideas for vascular robot ordering strategy
    Wang, Zixi
    Huang, Yubo
    Zhang, Yukai
    Sheng, Yifei
    Lai, Xin
    Lu, Peng
    PLOS ONE, 2025, 20 (02):
  • [9] A relative attribute reduction algorithm based on greedy strategy
    Zhang, Guojun
    Qinghua Daxue Xuebao/Journal of Tsinghua University, 2012, 52 (SUPPL.1): : 150 - 153
  • [10] Optimization of Seedlings Transplanting Strategy Based on Greedy Algorithm
    Tong, Junhua
    Jiang, Huanyu
    Xu, Xiaolong
    Fang, Chao
    KNOWLEDGE ENGINEERING AND MANAGEMENT, 2011, 123 : 33 - 39