  We study the average Age of Information (AoI) and peak AoI (PAoI) of a
dual-queue status update system that monitors a common stochastic process.
Although the double queue parallel transmission is instrumental in reducing
AoI, the out of order of data arrivals also imposes a significant challenge to
the performance analysis. We consider two settings: the M-M system where the
service time of two servers is exponentially distributed; the M-D system in
which the service time of one server is exponentially distributed and that of
the other is deterministic. For the two dual-queue systems, closed-form
expressions of average AoI and PAoI are derived by resorting to the graphic
method and state flow graph analysis method. Our analysis reveals that compared
with the single-queue system with an exponentially distributed service time,
the average PAoI and the average AoI of the M-M system can be reduced by 33.3%
and 37.5%, respectively. For the M-D system, the reduction in average PAoI and
the average AoI are 27.7% and 39.7%, respectively. Numerical results show that
the two dual-queue systems also outperform the M/M/2 single queue dual-server
system with optimized arrival rate in terms of average AoI and PAoI.
