Maximum AoI Minimization for Target Monitoring in Battery-Free Wireless Sensor Networks

Abstract

Age of Information (AoI) has been proposed to measure the freshness of the sensory data for IoT applications. In Battery-free WSNs (BF-WSNs), The AoI minimization data collection problem has been extensively studied. Apart from data collection, target monitoring is also an important application for BF-WSNs. To capture the freshness of the sensory data, the AoI of the sensory data related to targets (The AoI of targets) needs to be considered. To guarantee the performance of the target monitoring system, the maximum AoI of all targets should be minimized. However, existing works mainly investigated the AoI of the sensory data related to nodes (The AoI of nodes). Also, existing energy models are not practical enough for battery-free nodes. To deal with those problems, in this paper, we first propose a more practical energy model. Then the problem of Maximum AoI minimization for Target monitoring in Battery-free WSNs (MTB) is formally defined based on the proposed energy model. A two-stage algorithm is proposed to solve MTB optimally, in which all nodes in the network are scheduled collaboratively to monitor all the targets in the monitoring field. Extensive simulations and real-world experiments verify the high performance of our algorithm and energy model.