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This paper presents a regional density-aware data collection (RDDC) using unmanned aerial vehicles (UAVs) in large-scale wireless sensor networks (WSNs). The RDDC is designed to support fast data collection by adaptively adjusting the value of the minimum contention window (CWmin) of the sensor nodes depending on the regional node density of sensing fields. The operation of RDDC consists of the region-partitioning, node-scanning, and data-collecting phases. In the region-partitioning phase, the RDDC partitions the sensing field into multiple regions and assigns a region ID to each sensor node according to the region to which it belongs. In the node-scanning phase, the RDDC calculates the node density of each region. Finally, in the data-collecting phase, the RDDC assigns different CWmin values to each sensor node considering the regional node density of each region. The experimental simulation results show that the RDDC obtains higher aggregate throughput and shorter delay than the existing data collection method.

Regional Density-aware Data Collection Using Unmanned Aerial Vehicle in Large-scale Wireless Sensor Networks