Randomization Procedures in the Computation of Cumulative-Time Distributions over Discrete State Markov Processes
Randomization Procedures in the Computation of Cumulative-Time Distributions over Discrete State Markov Processes
复制标题
离散状态马尔可夫过程的累积时间分布计算中的随机化过程
作者：
B. Melamed;M. Yadin
本文提出了一种计算累积时间数值界限的方法，即，在离散状态马尔可夫过程中，在进入另一个指定的状态分布集之前，在一个指定的状态集中所花费的时间。该方法使用随机化程序来计算适当定义的瞬态马尔可夫过程的结果，计算的瞬态分布是等效的必要的累积时间分布。的方法，延迟时间的延迟网络的延迟应用程序的概述，其有效性进行评估，通过比较结果与逗留时间的问题与已知的分布。
This paper proposes a methodology for computing numerical bounds on cumulative-time i.e., the time spent in a specified set of states before entering another specified set of states distributions over discrete state Markov processes. The methodology uses randomization procedures to compute results for appropriately defined transient Markov processes; the transient distribution computed is equivalent to the requisite cumulative-time distribution. A queueing application of the methodology to delay times in queueing networks is outlined and its efficacy is appraised by comparing the results with a sojourn time for a problem with a known distribution.