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Even with the benefits, UAV-assisted IoT networks face difficulties stemming from limited energy and the consequential results of UAV trajectory on both of those the effectiveness of data acquisition and power intake. Also, the uplink transmission time and energy consumption of IoT devices are influenced by the choice of hover factors. Consequently, the focus of the work lies in investigating the issue of UAVs route intending to lower AoI, thus enabling IoT to gather data in a very timely and productive fashion.
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This paper investigated the path organizing issue for multi-UAV collaboration in finishing data collection jobs and proposed a DP-MATD3 path scheduling algorithm to minimize the weighted average AoI. The algorithm optimizes the Critic network by introducing the PSO algorithm, beating The difficulty on the MATD3 algorithm getting at risk of community optima.
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This paper aims to design and style a collaborative path-planning process for multiple UAVs, to attenuate the collected AoI. This process encompasses two distinctive phases: the flight phase, wherever UAVs transfer, as well as the hovering collection stage, wherever UAVs hover to collect info from IoT devices. Hence, the AoI collected by UAVs A n ( t )
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