Moment Generating Function of the AoI in Multi-Source Systems with Computation-Intensive Status Updates

TL;DR

This paper derives the moment generating function of the Age of Information in multi-source systems with computation-intensive status updates, analyzing preemptive and blocking policies to improve understanding of AoI behavior.

Contribution

It introduces a mathematical framework for AoI analysis in systems with computation delays and compares preemptive and blocking packet management policies.

Findings

MGF of AoI derived for both policies

Preemptive policy results in lower AoI variability

Blocking policy leads to higher AoI but simpler management

Abstract

We consider a multi-source status update system in which status updates are transmitted as packets containing the measured value of the monitored process and a time stamp representing the time when the sample was generated. The packets of each source are generated according to the Poisson process and the packets are served according to an exponentially distributed service time. We assume that the received status update packets needs further processing before being used (hence, computation-intensive). This is mathematically modeled by introducing an additional server at the sink node. The sink server serves the packets according to an exponentially distributed service time. We introduce two packet management policies, namely, i) a preemptive policy and ii) a blocking policy and derive the moment generating function (MGF) of the AoI of each source under both policies. In the preemptive policy, a new arriving packet preempts any possible packet that is currently under service regardless of the packet's source index. In the blocking policy, when a server is busy at the arrival instant of a packet the arriving packet is blocked and cleared. We assume that the same preemptive/blocking policy is employed in both transmitter and sink servers. Numerical results are provided to assess the results.