Minimizing AoI in a 5G-based IoT Network under Varying Channel Conditions


Age of information (AoI) is a key metric to measure the freshness of information for IoT applications. Most of existing analytical models for AoI are overly idealistic and do not capture state-of-the-art transmission technologies such as 5G as well as channel dynamics in both frequency and time domains. In this paper, we present Kronos, a real-time 5G-compliant scheduler that minimizes AoI for IoT data collection. Kronos is designed to cope with highly dynamic channel conditions. Its main function is to perform RB allocation and to select MCS for each source node based on channel conditions, with the objective of minimizing long-term AoI. To meet the stringent real-time requirement for 5G, we develop a GPU-based implementation of Kronos on commercial off-the-shelf Nvidia GPUs. Through extensive experimentation, we show that Kronos can find near-optimal solutions under sub-millisecond time scale. To the best of our knowledge, this is the first real-time AoI scheduler that is 5G compliant.

IEEE Internet of Things Journal