Delay-Tolerant Energy-Aware Unmanned Aerial Vehicles-Based Sensor Data Aggregation Protocol for Efficient Collection of Sensor Data
Seshendranath Balla Venkata, Taqy Aleobahaey, Hema Srikanth, M P Sahana., Sunaina Sangeet. T
Abstract
In recent years, Wireless Sensor Networks (WSNs) deployed in large-scale, lightly connected, and separated environments often lack the ability to determine end-to-end connectivity. To address these limitations, this research proposes a Delay-Tolerant Energy-Aware Unmanned Aerial Vehicles (DT-EA-UAV) data aggregation protocol for the efficient collection of sensor data using UAVs as mobile data mules. The network model consists of multiple geographically distributed WSN clusters, where Cluster Heads (CHs) are selected using a hybrid metric combining residual energy, distance to UAV flying routes, and occupancy of the data buffer. Different sensor data are provided within priority levels, and sensor data handling is separated into time-critical measurements and delay-tolerant traffic. An improved energyaware Grey Wolf Optimization (GWO) algorithm determines UAV flight paths, incorporating delay deadlines, residual UAV energy, and dynamic speed control near high-data clusters. The protocol employs opportunistic inter-cluster relaying for faster high-priority data transfer. Experimental results demonstrated that DT-EA-UAV using the GWO algorithm significantly improved the delivery ratio by 97.2 % and reduced the average energy consumption by 0.186 J per node within a round compared to the existing UAV-WSN using the Ant Colony Optimization (ACO) algorithm.