Age Analysis of Correlated Information in Multi-Source Updating Systems With MAP Arrivals

Information freshness in cyber-physical systems is essential for real-time applications that involve perception and control. Many of these applications rely on data generated by multiple correlated sources. To capture the inherent dependency in status update packets, we quantify the age of correlated information (AoCI) in a multi-source queueing system where each source generates packets following a Markovian arrival process (MAP) and these packets are subsequently served with exponentially distributed service times. Using the matrix geometric approach, we derive the sojourn time distribution in this MAP/M/1 queueing system. Furthermore, we obtain closed-form expressions for the average and peak AoCI in terms of the system parameters, considering both single and multiple source scenarios. Numerical results show the impact of correlated arrivals with different distribution properties on the achievable AoCI.