  In this article, we provide an accessible introduction to the emerging idea
of Age of Information (AoI) that quantifies freshness of information and
explore its possible role in the efficient design of freshness-aware Internet
of Things (IoT). We start by summarizing the concept of AoI and its variants
with emphasis on the differences between AoI and other well-known performance
metrics in the literature, such as throughput and delay. Building on this, we
explore freshness-aware IoT design for a network in which IoT devices sense
potentially different physical processes and are supposed to frequently update
the status of these processes at a destination node (such as a cellular base
station). Inspired by the recent interest, we also assume that these IoT
devices are powered by wireless energy transfer by the destination node. For
this setting, we investigate the optimal sampling policy that jointly optimizes
wireless energy transfer and scheduling of update packet transmissions from IoT
devices with the goal of minimizing long-term weighted sum-AoI. Using this, we
characterize the achievable AoI region. We also compare this AoI-optimal policy
with the one that maximizes average throughput (throughput-optimal policy), and
demonstrate the impact of system state on their structures. Several promising
directions for future research are also presented.
