Residual energy-based clustering in UAV-aided wireless sensor networks for surveillance and monitoring applications

Abstract

Aim: Unmanned aerial vehicle (UAV)-aided wireless sensor networks (WSNs) are effectively used for surveillance, monitoring, and rescue applications in military and commercial domains. In UAV-aided WSNs (UWSNs), efficient data gathered from sensor nodes are desired to enhance network performance. However, communication between UAV and sensor nodes is challenging due to the high mobility of the UAV and a large number of sensor nodes. Clustering in UWSNs limits the number of sensor nodes communicating with the UAV, i.e., only the cluster head in a cluster can transmit the sensed data to the UAV, which reduces collision probability. Methods: In this paper, we propose a residual energy-based clustering algorithm for sensor-to-UAV communication in UWSNs. The cluster size and the number of sensor nodes in a cluster are determined on the basis of the residual energy of the sensor nodes. The performance of the proposed algorithm is evaluated by using the MATLAB simulator and then compared with that of the conventional clustering algorithm. Results: According to our extensive simulation results, the proposed clustering scheme significantly outperforms the conventional one in terms of network lifetime and data delivery ratio. Conclusion: Hence, through our studies and simulations, it can be assured that the network lifetime of UWSNs can be prolonged and the throughput of the network can also be elevated by controlling the early death of sensor nodes due to the uneven energy consumptions. We will come up with further analysis and validation of our work in the future.