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… Click to show full 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.
               
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