论文标题
桥接因果可逆性和时间可逆性：随机过程代数方法
Bridging Causal Reversibility and Time Reversibility: A Stochastic Process Algebraic Approach
论文作者
论文摘要
因果可逆性融合了并发系统的可逆性和因果关系。这表明只要撤消其所有后果，就可以取消采取行动，从而使该系统可以回到过去一致的状态。相反，在随机过程的领域中考虑了时间可逆性，主要是出于有效的分析目的。如果在时间方向相反的情况下，基于连续时间马尔可夫链的性能模型将其随机行为保持不变，则是可逆的。我们通过显示因果可逆性和时间可逆性在施工中确保因果可逆性和时间可逆性的条件来弥合这两种可逆性理论。这是在随机过程演算的设置中完成的，然后配备了一种随机双相似性的变体，该变体对远期和后向方向进行了核算。
Causal reversibility blends reversibility and causality for concurrent systems. It indicates that an action can be undone provided that all of its consequences have been undone already, thus making it possible to bring the system back to a past consistent state. Time reversibility is instead considered in the field of stochastic processes, mostly for efficient analysis purposes. A performance model based on a continuous-time Markov chain is time reversible if its stochastic behavior remains the same when the direction of time is reversed. We bridge these two theories of reversibility by showing the conditions under which causal reversibility and time reversibility are both ensured by construction. This is done in the setting of a stochastic process calculus, which is then equipped with a variant of stochastic bisimilarity accounting for both forward and backward directions.
