  A large body of applications that involve monitoring, decision making, and
forecasting require timely status updates for their efficient operation. Age of
Information (AoI) is a newly proposed metric that effectively captures this
requirement. Recent research on the subject has derived AoI optimal policies
for the generation of status updates and AoI optimal packet queueing
disciplines. Unlike previous research we focus on low-end devices that
typically support monitoring applications in the context of the Internet of
Things. We acknowledge that these devices host a diverse set of applications
some of which are AoI sensitive while others are not. Furthermore, due to their
limited computational resources they typically utilize a simple First-In
First-Out (FIFO) queueing discipline. We consider the problem of optimally
controlling the status update generation process for a system with a
source-destination pair that communicates via a wireless link, whereby the
source node is comprised of a FIFO queue and two applications, one that is AoI
sensitive and one that is not. We formulate this problem as a dynamic
programming problem and utilize the framework of Markov Decision Processes to
derive optimal policies for the generation of status update packets. Due to the
lack of comparable methods in the literature, we compare the derived optimal
policies against baseline policies, such as the zero-wait policy, and
investigate the performance of all policies for a variety of network
configurations. Results indicate that existing status update policies fail to
capture the trade-off between frequent generation of status updates and
queueing delay and thus perform poorly.
