在拜占庭进程中检测因果关系:同步系统案例

IF 0.8 4区 计算机科学 Q3 COMPUTER SCIENCE, THEORY & METHODS Information and Computation Pub Date : 2024-08-12 DOI:10.1016/j.ic.2024.105212
Anshuman Misra, Ajay D. Kshemkalyani
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引用次数: 0

摘要

检测分布式系统中事件之间的因果关系或 "发生在前 "的关系是分布式应用程序的基本组成部分。最近的研究证明,在存在拜占庭进程的异步分布式系统中,无论通信机制是通过单播、多播还是广播,都无法解决这一问题。鉴于这一不可能性结果,我们将注意力转向同步系统,并研究在此类系统中解决因果关系检测问题的可能性。在本文中,我们证明了在同步分布式系统中存在拜占庭进程的情况下,可以解决事件间的因果关系检测问题。我们通过提供两种算法来证明这一结果。第一种算法使用复制状态机(RSM)方法和矢量时钟。第二种算法基于轮次,使用矩阵时钟。基于 RSM 的算法也能在部分同步系统中确定性地运行。
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Detecting causality in the presence of Byzantine processes: The case of synchronous systems

Detecting causality or the “happens before” relation between events in a distributed system is a fundamental building block for distributed applications. It was recently proved that this problem cannot be solved in an asynchronous distributed system in the presence of Byzantine processes, irrespective of whether the communication mechanism is via unicasts, multicasts, or broadcasts. In light of this impossibility result, we turn attention to synchronous systems and examine the possibility of solving the causality detection problem in such systems. In this paper, we prove that causality detection between events can be solved in the presence of Byzantine processes in a synchronous distributed system. We prove the result by providing two algorithms. The first algorithm uses the Replicated State Machine (RSM) approach and vector clocks. The second algorithm is round-based and uses matrix clocks. The RSM-based algorithm can also run deterministically in partially synchronous systems.

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来源期刊
Information and Computation
Information and Computation 工程技术-计算机:理论方法
CiteScore
2.30
自引率
0.00%
发文量
119
审稿时长
140 days
期刊介绍: Information and Computation welcomes original papers in all areas of theoretical computer science and computational applications of information theory. Survey articles of exceptional quality will also be considered. Particularly welcome are papers contributing new results in active theoretical areas such as -Biological computation and computational biology- Computational complexity- Computer theorem-proving- Concurrency and distributed process theory- Cryptographic theory- Data base theory- Decision problems in logic- Design and analysis of algorithms- Discrete optimization and mathematical programming- Inductive inference and learning theory- Logic & constraint programming- Program verification & model checking- Probabilistic & Quantum computation- Semantics of programming languages- Symbolic computation, lambda calculus, and rewriting systems- Types and typechecking
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