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Linpei Li
School of Information and Communication Engineering, Beijing University of Posts and Telecommunications , Beijing 100876, China.

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Journal article
Published: 17 October 2019 in Sensors
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The unmanned aerial vehicle (UAV) enabled mobile edge computing (MEC) system is attracting a lot of attentions for the potential of low latency and low transmission energy consumption, due to the advantages of high mobility and easy deployment. It has been widely applied to provide communication and computing services, especially in Internet of Things (IoT). However, there are still some challenges in the UAV-enabled MEC system. Firstly, the endurance of the UAV is limited and further impacts the performance of the system. Secondly, mobile devices are battery-powered and the batteries of some devices are hard to change. Therefore, in this paper, a UAV-enabled MEC system in which the UAV is empowered to have computing capability and provides tasks offloading service is studied. The total energy consumption of the UAV-enabled system, which includes the energy consumption of the UAV and the energy consumption of the ground users, is minimized under the constraints of the UAV’s energy budget, the number of each task’s bits, the causality of the data and the velocity of the UAV. The bits allocation of uploading data, computing data, downloading data and the trajectory of the UAV are jointly optimized with the goal of minimizing the total energy consumption. Moreover, a two-stage alternating algorithm is proposed to solve the non-convex formulated problem. Finally, the simulation results show the superiority of the proposed scheme compared with other benchmark schemes. Finally, the performance of the proposed scheme is demonstrated under different settings.

ACS Style

Linpei Li; Xiangming Wen; Zhaoming Lu; Qi Pan; Wenpeng Jing And Zhiqun Hu. Energy-Efficient UAV-Enabled MEC System: Bits Allocation Optimization and Trajectory Design. Sensors 2019, 19, 4521 .

AMA Style

Linpei Li, Xiangming Wen, Zhaoming Lu, Qi Pan, Wenpeng Jing And Zhiqun Hu. Energy-Efficient UAV-Enabled MEC System: Bits Allocation Optimization and Trajectory Design. Sensors. 2019; 19 (20):4521.

Chicago/Turabian Style

Linpei Li; Xiangming Wen; Zhaoming Lu; Qi Pan; Wenpeng Jing And Zhiqun Hu. 2019. "Energy-Efficient UAV-Enabled MEC System: Bits Allocation Optimization and Trajectory Design." Sensors 19, no. 20: 4521.

Journal article
Published: 15 November 2018 in Sensors
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With the new advancements in flight control and integrated circuit (IC) technology, unmanned aerial vehicles (UAVs) have been widely used in various applications. One of the typical application scenarios is data collection for large-scale and remote sensor devices in the Internet of things (IoT). However, due to the characteristics of massive connections, access collisions in the MAC layer lead to high power consumption for both sensor devices and UAVs, and low efficiency for the data collection. In this paper, a dynamic speed control algorithm for UAVs (DSC-UAV) is proposed to maximize the data collection efficiency, while alleviating the access congestion for the UAV-based base stations. With a cellular network considered for support of the communication between sensor devices and drones, the connection establishment process was analyzed and modeled in detail. In addition, the data collection efficiency is also defined and derived. Based on the analytical models, optimal speed under different sensor device densities is obtained and verified. UAVs can dynamically adjust the speed according to the sensor device density under their coverages to keep high data collection efficiency. Finally, simulation results are also conducted to verify the accuracy of the proposed analytical models and show that the DSC-UAV outperforms others with the highest data collection efficiency, while maintaining a high successful access probability, low average access delay, low block probability, and low collision probability.

ACS Style

Qi Pan; Xiangming Wen; Zhaoming Lu; Linpei Li; Wenpeng Jing. Dynamic Speed Control of Unmanned Aerial Vehicles for Data Collection under Internet of Things. Sensors 2018, 18, 3951 .

AMA Style

Qi Pan, Xiangming Wen, Zhaoming Lu, Linpei Li, Wenpeng Jing. Dynamic Speed Control of Unmanned Aerial Vehicles for Data Collection under Internet of Things. Sensors. 2018; 18 (11):3951.

Chicago/Turabian Style

Qi Pan; Xiangming Wen; Zhaoming Lu; Linpei Li; Wenpeng Jing. 2018. "Dynamic Speed Control of Unmanned Aerial Vehicles for Data Collection under Internet of Things." Sensors 18, no. 11: 3951.