“…Afterwards, a series of works [5]- [12] aimed at characterizing the average AoI and its variations (e.g., Peak Age-of-Information (PAoI) [8]- [10] and Value of Information of Update (VoIU) [11]) for adaptations of the queueing model studied in [4]. Another direction of research [13]- [33] focused on employing AoI as a performance metric for different communication systems that deal with time critical information while having limited resources, e.g., multi-server information-update systems [14], broadcast networks [15]- [17], multi-hop networks [18], cognitive networks [19], unmanned aerial vehicle (UAV)assisted communication systems [20]- [22], IoT networks [2], [23], [24], ultra-reliable low-latency vehicular networks [25], multicast networks [26], decentralized random access schemes [32], and multi-state time-varying networks [33]. Particularly, the objective of this research direction was to characterize optimal policies that minimize average AoI, referred to as ageoptimal polices, by applying different tools from optimization theory.…”