• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

计算机工程与科学

• 计算机网络与信息安全 • 上一篇    下一篇

N状态二进制一致性算法设计及其优化

刘华1,杨春曦1,韩光松2,谢可心1   

  1. (1.昆明理工大学化学工程学院,云南 昆明 650500;2.国防大学联合作战学院,河北 石家庄 050084)
  • 收稿日期:2018-03-26 修回日期:2018-11-08 出版日期:2019-06-25 发布日期:2019-06-25
  • 基金资助:

    国家自然科学基金(61364002)

Design and optimization of an N-state
binary consensus algorithm

LIU Hua1,YANG Chunxi1,HAN Guangsong2,XIE Kexin1   

  1. (1.Faculty of Chemical Engineering,Kunming University of Science and Technology,Kunming 650500;
    2.Joint Operations College,PLA National Defense University,Shijiazhuang 050084,China)

     
  • Received:2018-03-26 Revised:2018-11-08 Online:2019-06-25 Published:2019-06-25

摘要:

针对二进制一致性算法扩展性差、经验依赖性强的缺点,提出了一种N状态分布式二进制一致性算法。首先,基于Gossip算法的平均一致性思想和轮盘赌思想,更新无线传感器网络状态均值和当前状态均值的偏差程度,计算所有可能更新状态的初始概率分布;然后,利用遗传算法优化初始概率分布,得到准确率较高的最优概率分布。仿真结果表明,在相同状态个数条件下,本文所设计的算法具有更好的准确率和收敛时间。

关键词: 一致性, 遗传算法, 二进制, 优化

Abstract:

Given the disadvantages of poor expansibility and strong experience dependence of existing binary consensus algorithms, we propose an Nstate distributed binary consensus algorithm. Firstly, based on the idea of average consensus of the Gossip algorithm and the roulette idea, the degree of deviation between the state average of the wireless sensor network and the current state average is updated, and the initial probabilistic distribution of all possible update states is calculated. Secondly, the genetic algorithm is applied to optimize the initial probability distribution and obtain the optimal probability distribution with better accuracy. The results show that the proposed algorithm has higher accuracy and shorter convergence time under the same number of states.
 

Key words: consensus, genetic algorithm, binary, optimization