Jointly Optimal Fair Data Collection and Trajectory Design Algorithms in UAV-Aided Cellular Networks

Author(s):  
Dan Song ◽  
Xiangping Bryce Zhai ◽  
Xin Liu ◽  
Chee Wei Tan
2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Lin Xiao ◽  
Yipeng Liang ◽  
Chenfan Weng ◽  
Dingcheng Yang ◽  
Qingmin Zhao

In this paper, we consider a ground terminal (GT) to an unmanned aerial vehicle (UAV) wireless communication system where data from GTs are collected by an unmanned aerial vehicle. We propose to use the ground terminal-UAV (G-U) region for the energy consumption model. In particular, to fulfill the data collection task with a minimum energy both of the GTs and UAV, an algorithm that combines optimal trajectory design and resource allocation scheme is proposed which is supposed to solve the optimization problem approximately. We initialize the UAV’s trajectory firstly. Then, the optimal UAV trajectory and GT’s resource allocation are obtained by using the successive convex optimization and Lagrange duality. Moreover, we come up with an efficient algorithm aimed to find an approximate solution by jointly optimizing trajectory and resource allocation. Numerical results show that the proposed solution is efficient. Compared with the benchmark scheme which did not adopt optimizing trajectory, the solution we propose engenders significant performance in energy efficiency.


Sensors ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 37
Author(s):  
Tariq Qayyum ◽  
Zouheir Trabelsi ◽  
Asad Malik ◽  
Kadhim Hayawi

Unmanned aerial vehicles (UAVs) play an important role in facilitating data collection in remote areas due to their remote mobility. The collected data require processing close to the end-user to support delay-sensitive applications. In this paper, we proposed a data collection scheme and scheduling framework for smart farms. We categorized the proposed model into two phases: data collection and data scheduling. In the data collection phase, the IoT sensors are deployed randomly to form a cluster based on their RSSI. The UAV calculates an optimum trajectory in order to gather data from all clusters. The UAV offloads the data to the nearest base station. In the second phase, the BS finds the optimally available fog node based on efficiency, response rate, and availability to send workload for processing. The proposed framework is implemented in OMNeT++ and compared with existing work in terms of energy and network delay.


2002 ◽  
Vol 8 (4) ◽  
pp. 241-246 ◽  
Author(s):  
J.C.H. Spence ◽  
N. Jiang ◽  
U. Weierstall

Alloy design has been a lifelong interest of Gareth Thomas, and modern design algorithms include atomistic parameters which are obtainable from new electron microscope techniques such as ALCHEMI. In this paper, we discuss the relevance of ALCHEMI site occupancy measurements to intermetallic alloys, and summarize prior work. The results are found to lie in regions of a site-occupancy diagram (SOC) relating ordering energies to occupancy, as predicted by the Bragg–Williams theory of short-range order. These predictions also explain previous inconsistencies in the ALCHEMI measurements. A diffraction camera and X-ray detector system of novel design is proposed for dedicated ALCHEMI analysis for substitutional and interstitial dopant site-occupancy measurement, and details of the design given. Using this novel hardware design, the data-collection times for two-dimensional ALCHEMI patterns should be reduced by an order of magnitude or more, and the full data collection process automated. The resulting occupancy information can provide essential input parameters for atomistic alloy design algorithms, and can provide entirely new information on interstitial occupancies in minerals, ceramics, semiconductors, and alloys.


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