In this paper, we examine a multi-sensor system where each sensor may monitor more than one time-varying information process and send status updates to a remote monitor over a common channel. We consider that each sensor's status update may contain information about more than one information process in the system subject to the system's constraints. To investigate the impact of this correlation on the overall system's performance, we conduct an analysis of both the average Age of Information (AoI) and source state estimation error at the monitor. Building upon this analysis, we subsequently explore the impact of the packet arrivals, correlation probabilities, and rate of processes' state change on the system's performance. Next, we consider the case where sensors have limited sensing abilities and distribute a portion of their sensing abilities across the different processes. We optimize this distribution to minimize the total AoI of the system. Interestingly, we show that monitoring multiple processes from a single source may not always be beneficial. Our results also reveal that the optimal sensing distribution for diverse arrival rates may exhibit a rapid regime switch, rather than smooth transitions, after crossing critical system values. This highlights the importance of identifying these critical thresholds to ensure effective system performance.

翻译：本文研究一个多传感器系统，其中每个传感器可监测多个时变信息进程，并通过公共信道向远程监控器发送状态更新。考虑到系统约束，每个传感器的状态更新可能包含系统中多个信息进程的信息。为探究这种相关性对整体系统性能的影响，我们对监控器处的平均信息年龄（AoI）与源状态估计误差进行了分析。基于此分析，我们进一步探讨了数据包到达、相关概率及进程状态变化率对系统性能的影响。随后，我们考虑传感器感知能力受限的情况，研究其如何将部分感知能力分配给不同进程。我们通过优化该分配方案以最小化系统总AoI。有趣的是，我们发现从单一信源监测多个进程并非总是有益的。研究结果还表明，针对不同到达率的最优感知分配方案在跨越关键系统阈值时可能出现急剧的机制切换，而非平滑过渡。这凸显了识别这些关键阈值对保障系统有效性能的重要性。