Wireless Scheduling to Optimize Age of Information Based on Earliest Update Time

Abstract

Recently, has been recognized that there is a practical limitation with the original notion of Age of Information (AoI) metric in terms of quantifying the freshness of information content. A new metric, called Age of Incorrect Information (AoII), has been proposed. In this article, we introduce the notion of AoII+ metric by modifying AoII with practical considerations. Then, we investigate a scheduling problem to minimize AoII+ in an IoT data collection network. We derive a theoretical lower bound for the minimum AoII+. Then, we present Heh—a low-complexity online scheduler to minimize AoII+. The design of Heh is based on the estimation of a novel offline scheduling priority metric without any future knowledge. We prove that at each time, transmitting one source with the largest offline scheduling priority metric minimizes AoII+. Through extensive simulations, we show that the lower bound is very tight and that the AoII+ obtained by Heh is close to optimal.