Trust data collections via vehicles joint with unmanned aerial vehicles in the smart Internet of Things - Li, Ting; Liu, Wei; Wang, Tian; Ming, Zhao; Li, Xiong; Ma, Ming (Transactions on emerging telecommunications technologies, 2022)
Due to their mobile character, ground vehicles and unmanned aerial vehicles (UAVs) are currently being considered as sensing devices that can collect data in the Internet of Things (IoT). Building and enhancing trust and security environments in data collection processes are fundamental and essential requirements. Here, we proposed a novel scheme named “Trust Data Collections via Vehicles joint with UAVs in the Smart Internet of Things” (T‐SIoTs scheme), which targets to establish a trust‐based environment for data collections by utilizing both trust vehicles and UAVs. First, to optimize security aspect, data center (DC) selected trust‐based vehicles as mobile data collectors via analyzing and digging historical datasets. To promise coverage regions of data collections, several static stations are established, which can be utilized as static data collectors. Second, UAVs are arranged by the DC to collect data stored by both trust‐based vehicles and static data collectors. In the T‐SIoTs scheme, trajectories of UAVs are designed according to shortest‐distance‐first routing scheme. Comprehensive theoretical analyses and experiments have been provided to evaluate and support the T‐SIoTs scheme. Compared with the previous studies, the T‐SIoTs scheme can improve the security ratio by 46.133% to 54.60% approximately. And with the routing scheme, the energy consumptions of UAVs can be reduced by 46.93% approximately. To improve data security, the trust‐based collection scheme proposed in this article selected trust vehicles as mobile data collectors via analyzing historical trajectory datasets. To promise coverage regions of data collections, static stations were established as static data collectors by shortest distance method. Finally, UAVs were arranged to collect the data in both the mobile data collectors and the static data collectors by clustering method.