Age of Information (AoI) has recently received much attention due to its relevance in IoT sensing and monitoring applications. In this paper, we consider the problem of minimizing the AoI in a system in which a set of sources are observed by multiple sensors in a many-to-many relationship, and the probability that a sensor observes a source depends on the state of the source. This model represents many practical scenarios, such as the ones in which multiple cameras or microphones are deployed to monitor objects moving in certain areas. We formulate the scheduling problem as a Markov Decision Process, and show how the age-optimal scheduling policy can be obtained. We further consider partially observable variants of the problem, and devise approximate policies for large state spaces. Our evaluations show that the approximate policies work well in the considered scenarios, and that the fact that sensors can observe multiple sources is beneficial, especially when there is high uncertainty of the source states.

翻译：信息时代(AoI)最近因其在IoT感应和监测应用中的关联性而受到很大关注。在本文中,我们考虑了在一个系统中将AoI最小化的问题,在这个系统中,多个传感器在多种关系中观测了一组源,传感器观测源的可能性取决于源的状况。这个模型代表了许多实际的情景,例如安装了多部照相机或麦克风来监测在某些地区移动的物体。我们把时间安排问题设计成一个Markov决策程序,并表明如何实现年龄最佳的时间安排政策。我们进一步考虑问题的部分可观察变量,并为大型州空间设计了近似政策。我们的评估表明,近似政策在所考虑的情景中效果良好,而且传感器能够观测多个源的实实在在有益,特别是当源状态存在高度不确定性时。