Optimizing Sensor Data Transmission in Collaborative Multi-Sensor Environments

In the era of smart agriculture and smart industry, sensor networks have become indispensable for gathering crucial data to improve efficiency, reduce resource consumption, and enhance decision-making processes. In this context, sensor data transmission schedules are essential for real-time control in smart applications. This research explores the optimization of sensor data transfer schedules in environments where external sources can also contribute with informative updates in a non-controllable fashion. We propose an online method based on dynamic programming for AoI minimization that obtains optimal budgeted update instants in the presence of external assistance. Our findings reveal optimal transmission intervals, addressing data redundancy challenges and contributing to efficient sensor network utilization.