LAUSR

IoT sensor networks enable long-term environmental monitoring. Most environmental applications require sensor node data gathering to satisfy application objectives. Therefore, sensing range optimization is a significant element in prolonging the lifetime of IoT sensor networks and saving energy. This study proposes an adaptive density control based on random sensing range (ADCR). It can reduce data redundancy by selecting several active and hybrid nodes in a sensing field. Thus, reducing redundancy power consumption will maximize the network lifetime. The simulation results demonstrate the effectiveness of density control based on the random sensing range.