We present an algorithm for the numerical evaluation of the state-space distribution of an Age-of-Information network. Given enough computational resources, the evaluation can be performed to an arbitrary high precision. An Age-of-Information network is described by a vector of natural numbers, that track how outdated status information from various agents is. Our algorithm yields the means to determine any moment of the corresponding stochastic process. This can be extremely valuable for cases in which the network consists of controllers that communicate with one another, as it potentially allows for less conservative control behavior. It also enables the comparison of different policies regarding their performance (minimizing the average Age-of-Information) to a much more accurate degree than was possible before. This is illustrated using the conventional MaxWeight policy and the optimal policy. We also validate and compare the algorithm with Monte-Carlo-Simulations.

翻译：我们对信息时代网络的状态空间分布进行数字评估。 如果计算资源充足, 评估可以任意地进行。 信息时代网络由自然数字矢量描述, 跟踪来自各种代理商的过时状态信息。 我们的算法生成了确定相应随机过程任何时刻的手段。 对于网络由相互沟通的控制器组成的情况, 这可能极有价值, 因为它可能允许较保守的控制行为 。 它还能够将不同政策性能( 最小化信息平均年龄)的比较比以前更精确得多。 这用传统的 MaxWeight 政策和最佳政策来说明。 我们还验证和比较了与Monte-Carlo模拟的算法。