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An Intelligent UAV based Data Aggregation Algorithm for 5G-enabled Internet of Things

机译:一种基于智能的UV数据聚合算法,适用于支持的5G互联网

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摘要

Unmanned Aerial Vehicle (UAV) has become a significant part of 5G or beyond 5G (B5G) paradigm, and is used in various scenarios, including cargo delivery, agricultural application, event surveillance, etc. Although plenty of studies have been proposed on UAV-based data aggregation, how to ensure security and energy-efficiency of the data aggregation process in 5G-enabled Internet of Things (IoT) is an open problem. In this paper, we propose an Intelligent UAV-based Data Aggregation Algorithm, named IDAA for 5G-Enabled IoT. Specifically, IDAA applies v-Support Vector Regression (v-svr) to predict the data collection rate. Then, a security level based task decomposition mechanism is designed that allows UAVs to accept the tasks of corresponding security levels. Finally, energy efficient routes for UAV are planned utilizing a deep reinforcement learning method to achieve the trade-off between the sinking ratio and the energy cost. The theoretical analysis and simulation results indicate that (i) IDAA improves the security of data aggregation; and (ii) IDAA enables UAVs to collect more data and consume less energy compared with baseline strategies.
机译:无人驾驶飞行器(UAV)已成为5G或超过5G(B5G)范式的重要组成部分,并用于各种场景,包括货物交付,农业应用,事件监测等。虽然UAV-已经提出了大量研究 - 基于数据聚合,如何确保第5G个功能Internet的数据聚合过程的安全性和节能(IOT)是一个打开问题。在本文中,我们提出了一种基于智能UV的数据聚合算法,名为IDAA的IDAA,启用了5G的IOT。具体地,IDAA应用V-Support向量回归(V-SVR)来预测数据收集率。然后,设计了一种基于安全级别的任务分解机制,允许UAV接受相应安全级别的任务。最后,利用深度加强学习方法计划UAV的节能路线,以实现下沉比和能源成本之间的权衡。理论分析和仿真结果表明(i)IDAA提高了数据聚集的安全性; (ii)IDAA使无人机能够收集更多数据并与基线策略相比消耗更少的能量。

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