The Impact of Tagged and Competing Traffic Properties on Peak AoI in 5G Systems

Abstract

The Age of Information (AoI) is a metric for state update applications, which plays a crucial role in the Internet of Things (IoT). In many environments, such as factories and energy grid deployment, end sensing nodes tend to be naturally clustered, resulting in high variability and autocorrelation in the packet arrival process. In this paper, we assess the impact of variability and autocorrelation of packet arrivals in one cluster on the performance of other clusters in 5G cellular systems by explicitly accounting for the batch nature of the packet arrival and service processes arising as a a result of discrete nature of the scheduling process and the autocorrelational properties of the arrival processes. We show that not only the mean arrival rates but coefficient of variation (CoV) and autocorrelation in the arrival processes from tagged and competing clusters affect both the mean and distribution of the peak AoI (PAoI). Although the impact of these second-order properties depends heavily on their relative loads, it is tagged cluster properties that produces the most impact on its own performance metrics. Notably, the worst performance is observed when the competing traffic takes on the properties of the Poisson process - unit variability and no memory. The main practical takeaway is that increase in either tagged or background sources variability can raise the PAoI by 40-60%, but it also makes it more stable around the mean value reducing the jitter at the destination.