Age of Information for Multiple-Source Multiple-Server Networks

Having timely and fresh knowledge about the current status of information sources is critical in a variety of applications, where the status update arrives at the destination later than its generation time due to processing and communication delays. The freshness of the status update at the destination is captured by the notion of the age of information. In this study, we analyze a multiple sensing network with multiple sources, multiple servers, and a monitor (destination). Each source corresponds to an independent piece of information, and its age is individually measured. Given a particular source, the servers independently sense the source of information and send the status update to the monitor. We assume that updates arrive at the servers according to Poisson random processes. Each server sends its updates to the monitor through a direct link, which is modeled as a queue. The service time to transmit an update is considered to be an exponential random variable. We examine both homogeneous and heterogeneous service and arrival rates for the single-source case, and homogeneous arrival and service rates for the multiple-source case. We derive a closed-form expression for the average age of information under a last-come-first-serve (LCFS) queue for a single source and an arbitrary number of homogeneous servers. Using a recursive method, we derive the explicit average age of information for any number of sources and homogeneous servers. We also investigate heterogeneous servers and a single source, and present efficient algorithms for finding the average age of information. Optimal update scheduling strategies are also investigated in several scenarios, providing insights into enhancing the system performance in terms of update freshness.