scholarly journals Robust Edge Computing in UAV Systems via Scalable Computing and Cooperative Computing

Author(s):  
Zhi Liu ◽  
Cheng Zhan ◽  
Ying Cui ◽  
Celimuge Wu ◽  
Han Hu

<div>Unmanned aerial vehicle (UAV) systems are of increasing interest to academia and industry due to their mobility, flexibility and maneuverability, and are an effective alternative to various uses such as surveillance and mobile edge computing (MEC). However, due to their limited computational and communications resources, it is difficult to serve all computation tasks simultaneously. This article tackles this problem by first proposing a scalable aerial computing solution, which is applicable for computation tasks of multiple quality levels, corresponding to different computation workloads and computation results of distinct performances. It opens up the possibility to maximally improve the overall computing performance with limited computational and communications resources. To meet the demands for timely video analysis that exceed the computing power of a UAV, we propose an aerial video streaming enabled cooperative computing solution namely, UAVideo, which streams videos from a UAV to ground servers. As a complement to scalable aerial computing, UAVideo minimizes the video streaming time under the constraints on UAV trajectory, video features, and communications resources. Simulation results reveal the substantial advantages of the proposed solutions. Besides, we highlight relevant directions for future research.</div>

2021 ◽  
Author(s):  
Zhi Liu ◽  
Cheng Zhan ◽  
Ying Cui ◽  
Celimuge Wu ◽  
Han Hu

<div>Unmanned aerial vehicle (UAV) systems are of increasing interest to academia and industry due to their mobility, flexibility and maneuverability, and are an effective alternative to various uses such as surveillance and mobile edge computing (MEC). However, due to their limited computational and communications resources, it is difficult to serve all computation tasks simultaneously. This article tackles this problem by first proposing a scalable aerial computing solution, which is applicable for computation tasks of multiple quality levels, corresponding to different computation workloads and computation results of distinct performances. It opens up the possibility to maximally improve the overall computing performance with limited computational and communications resources. To meet the demands for timely video analysis that exceed the computing power of a UAV, we propose an aerial video streaming enabled cooperative computing solution namely, UAVideo, which streams videos from a UAV to ground servers. As a complement to scalable aerial computing, UAVideo minimizes the video streaming time under the constraints on UAV trajectory, video features, and communications resources. Simulation results reveal the substantial advantages of the proposed solutions. Besides, we highlight relevant directions for future research.</div>


2020 ◽  
Vol 27 (1) ◽  
pp. 140-146 ◽  
Author(s):  
Fuhui Zhou ◽  
Rose Qingyang Hu ◽  
Zan Li ◽  
Yuhao Wang

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3363
Author(s):  
Linpei Li ◽  
Xiangming Wen ◽  
Zhaoming Lu ◽  
Wenpeng Jing

The data volume is exploding due to various newly-developing applications that call for stringent communication requirements towards 5th generation wireless systems. Fortunately, mobile edge computing makes it possible to relieve the heavy computation pressure of ground users and decrease the latency and energy consumption. What is more, the unmanned aerial vehicle has the advantages of agility and easy deployment, which gives the unmanned aerial vehicle enabled mobile edge computing system opportunities to fly towards areas with communication demand, such as hotspot areas. However, the limited endurance time of unmanned aerial vehicle affects the performance of mobile edge computing services, which results in the incomplete mobile edge computing services under the time limit. Consequently, this paper concerns the energy-efficient scheme design of the unmanned aerial vehicle while providing high-quality offloading services for ground users, particularly in the regions where the ground communication infrastructures are overloaded or damaged after natural disasters. Firstly, the model of energy-efficient design of the unmanned aerial vehicle is set up taking the constraints of the energy limitation of the unmanned aerial vehicle, the data causality, and the speed of the unmanned aerial vehicle into account. Subsequently, aiming at maximizing the energy efficiency of the unmanned aerial vehicle in the unmanned aerial vehicle enabled mobile edge computing system, the bits allocation in each time slot and the trajectory of the unmanned aerial vehicle are jointly optimized. Secondly, a successive convex approximation based alternating algorithm is brought forward to deal with the non-convex energy efficiency maximization problem. Finally, it is proved that the proposed energy efficient scheme design of the unmanned aerial vehicle is superior to other benchmark schemes by the simulation results. Besides, how the performance of proposed scheme design change under different parameters is discussed.


2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Lei He ◽  
Jianfeng Ma ◽  
Ruo Mo ◽  
Dawei Wei

Unmanned Aerial Vehicle (UAV) has enormous potential in many domains. According to the characteristics of UAV, it is important for UAV network to assure low latency and integrity and authentication of commands sent by command center or command stations to UAV. In this paper, we proposed a UAV network architecture based on mobile edge computing (MEC) which helps guarantee low latency in the UAV network. Afterwards, we proposed a designated verifier proxy blind signature (DVPBS) scheme for UAV network and proved that it is existentially unforgeable under an adaptive chosen message attack in the random oracle model. We compared the efficiency of our DVPBS scheme with other signature schemes by implementing them in jPBC and theoretically analyzing their signature length. The experiment results indicate that our DVPBS scheme is efficient. The signature length of our DVPBS is longer, but it is still short enough compared with the transmission capacity of UAV.


2018 ◽  
Vol 8 (7) ◽  
pp. 1160 ◽  
Author(s):  
Juyong Lee ◽  
Jihoon Lee

Due to the recent developments in mobile network technology and the supply of mobile devices, services that require high computing power and fast access speed, such as machine learning and multimedia streaming, are attracting attention. Mobile Edge Computing (MEC) has emerged. MEC allows servers to be located close to users to efficiently handle these services and provides users with ultra-low latency content delivery and powerful computing services. However, there has been a lack of research into the architecture required to efficiently use the computing power and resources of MEC. So, this paper proposes hierarchical MEC architecture in which MEC servers (MECS) are arranged in a hierarchical scheme to provide users with rapid content delivery, high computing performance, and efficient use of server resources.


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