通信学报 ›› 2023, Vol. 44 ›› Issue (3): 164-177.doi: 10.11959/j.issn.1000-436x.2023059

• 学术论文 • 上一篇    下一篇

基于偏向稳定的分布式审计因果一致性模型

田俊峰1,2, 杨乾宇1,2, Jitian Xiao3   

  1. 1 河北大学网络空间安全与计算机学院,河北 保定 071002
    2 河北省高可信信息系统重点实验室,河北 保定 071002
    3 伊迪斯科文大学科学学院,君达乐 WA6027
  • 修回日期:2023-02-23 出版日期:2023-03-25 发布日期:2023-03-01
  • 作者简介:田俊峰(1965− ),男,河北保定人,博士,河北大学教授、博士生导师,主要研究方向为信息安全与分布式计算
    杨乾宇(1998− ),女,山西长治人,河北大学硕士生,主要研究方向为信息安全、数据一致性
    Jitian Xiao(1958− ),男,河北邯郸人,博士,伊迪斯科文大学教授,主要研究方向为数据库应用、数据处理、数据挖掘、大数据分析和企业数据安全
  • 基金资助:
    河北省自然科学基金资助项目(京津冀基础合作专项)(F2021201058);河北省自然科学基金资助项目(F2021201049)

Distributed audit causal consistency model based on biased stability

Junfeng TIAN1,2, Qianyu YANG1,2, Xiao Jitian3   

  1. 1 School of Cyber Security and Computer, Hebei University, Baoding 071002, China
    2 Key Laboratory on High Trusted Information System in Hebei Province, Baoding 071002, China
    3 School of Science, Edith Cowan University, Joondalup WA6027, Australia
  • Revised:2023-02-23 Online:2023-03-25 Published:2023-03-01
  • Supported by:
    The Natural Science Foundation of Hebei Province (Beijing-Tianjin-Hebei Basic Cooperation Special Project)(F2021201058);The Natural Science Foundation of Hebei Province(F2021201049)

摘要:

在分布式存储中,因果一致性由于易编程与性能权衡最佳而备受青睐。为解决现有因果一致性成果中矢量依赖跟踪损失吞吐量的问题,提出了基于偏向稳定的分布式审计因果一致性模型。在查询操作中使用组合矢量时间戳替代全矢量时间戳,减少系统管理与通信开销。同时,将分布式关联数组引入因果审计,分区协同审计细化数据依赖性,以减少虚假依赖条目数量。理论分析与仿真结果表明,所提模型可提升吞吐量48.26%,降低更新响应时延16.25%。

关键词: 数据一致性, 因果一致性, 分布式存储, 偏向稳定, 因果审计

Abstract:

In the distributed storage, causal consistency is favored due to the best trade-off between ease of programming and performance.To address the problem of vector-dependent tracking loss of throughput in existing causal consistency results, a distributed audit causal consistency model based on biased stability was proposed.Combined vector timestamps were used instead of full vector timestamps in query operations to reduce system management and communication overhead.Meanwhile, the causal auditing was introduced with the help of distributed associative arrays, and data dependency was refined by partitioned cooperative auditing to reduce the number of false dependency entries.Theoretical analysis and simulation results show that proposed model improves throughput by 48.26% and reduces update response latency by 16.25%.

Key words: data consistency, causal consistency, distributed storage, bias stability, causal audit

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