Online Algorithms for Optimizing Age of Information in the IoT Systems with Multi-Slot Status Delivery

Age of information (AoI) is recently proposed to measure the freshness of information, which provides a new performance metric for the real-time Internet of Things (IoT). In this letter, we investigate low complexity online algorithms to minimize the average AoI in an IoT system where the nodes are scheduled to sample the status with multiple packets and send it to the destination through noisy channels. Three online policies are proposed: Greedy policy, Max-Ratio policy and Lyapunov drift policy. Simulation results show that our online algorithms outperform the existing suboptimal algorithm and the Lyapunov drift policy yields the best performance.