Unmanned aerial vehicles in collaboration with fog computing network for improving quality of service

In this paper, we study a UAV-based fog or edge computing network in which UAVs and fog/edge nodes work together intelligently to provide numerous benefits in reduced latency, data offloading, storage, coverage, high throughput, fast computation, and rapid responses. In an existing UAV-based computing network, the users send continuous requests to offload their data from the ground users to UAV–fog nodes and vice versa, which causes high congestion in the whole network. However, the UAV-based networks for real-time applications require low-latency networks during the offloading of large volumes of data. Thus, the QoS is compromised in such networks when communicating in real-time emergencies. To handle this problem, we aim to minimize the latency during offloading large amounts of data, take less computing time, and provide better throughput. First, this paper proposed the four-tier architecture of the UAVs–fog collaborative network in which local UAVs and UAV–fog nodes do smart task offloading with low latency. In this network, the UAVs act as a fog server to compute data with the collaboration of local UAVs and offload their data efficiently to the ground devices. Next, we considered the Q-learning Markov decision process (QLMDP) based on the optimal path to handle the massive data requests from ground devices and optimize the overall delay in the UAV-based fog computing network. The simulation results show that this proposed collaborative network achieves high throughput, reduces average latency up to 0.2, and takes less computing time compared with UAV-based networks and UAV-based MEC networks; thus, it can achieve high QoS.     

VDNet: an infrastructure‐less UAV‐assisted sparse VANET system with vehicle location prediction

Vehicular Ad Hoc Network (VANET) has been a hot topic in the past few years. Compared with vehicular networks where vehicles are densely distributed, sparse VANET have more realistic significance. The first challenge of a sparse VANET system is that the network suffers from frequent disconnections. The second challenge is to adapt the transmission route to the dynamic mobility pattern of the vehicles. Also, some infrastructural requirements are hard to meet when deploying a VANET widely. Facing these challenges, we devise an infrastructure‐less unmanned aerial vehicle (UAV) assisted VANET system called V ehicle‐D rone hybrid vehicular ad hoc Net work (VDNet), which utilizes UAVs, particularly quadrotor drones, to boost vehicle‐to‐vehicle data message transmission under instructions conducted by our distributed vehicle location prediction algorithm. VDNet takes the geographic information into consideration. Vehicles in VDNet observe the location information of other vehicles to construct a transmission route and predict the location of a destination vehicle. Some vehicles in VDNet equips an on‐board UAV, which can deliver data message directly to destination, relay messages in a multi‐hop route, and collect location information while flying above the traffic. The performance evaluation shows that VDNet achieves high efficiency and low end‐to‐end delay with controlled communication overhead. Copyright © 2016 John Wiley & Sons, Ltd.     

Performance analysis of cooperative multi‐carrier relay‐based UAV networks over generalized fading channels

The outage probability in a network of cooperative unmanned airborne vehicles (UAVs) over generalized fading channels is studied analytically using finite mixture with expectation maximization technique. A relay‐based topology with one ground control unit (GCU) is considered, where the cooperative UAVs can communicate with the GCU directly or through relay. The application the UAV is assigned for specifies the minimum required transmission rate the UAV should achieve. The outage probability of the system is defined as the probability that either the transmission rate over any of the links drops below a predefined minimum threshold for that link or the Relay‐GCU link is not able to transmit the aggregate data from all relayed UAVs and the minimum rate required by the relay UAV itself. Throughout the paper, expressions for the outage probability and the average achievable bit rate of a cooperative multi‐carrier system are derived over generalized fading channels. Finite mixture with expectation maximization algorithm is utilized to derive a simple approximate expression for the probability density function (pdf) of the achievable bit rate assuming adaptive M‐ary quadrature amplitude modulation (M‐QAM). This pdf is used to derive closed‐form expressions for the outage probability and the average bit rate. Copyright © 2011 John Wiley & Sons, Ltd.     

一种面向无人机通信的协作干扰安全传输技术

本文利用无人机的高机动特性带来信道的动态变化这一机理,通过合理地控制无人机位置,靠近合法节点并远离窃听节点,增加合法节点的信道增益,削弱窃听节点的信道增益,从而提高信源端和目的端的安全通信容量。已有的无人机空地信道模型大多仅考虑视距传输链路,本文在此基础上增加了非视距链路（Not Line of Sight, NLOS）,并且在窃听者位置存在估计误差条件下,建立了两架无人机协同通信场景,在上述场景下通过合理规划两架无人机飞行轨迹,增强合法信道增益,削弱窃听信道增益,并联合无人机的功率分配,实现最大化平均保密速率。该优化问题为非凸问题,因此采用了连续凸近似（Successive Convex Approximation, SCA）以及块坐标下降算法 （Block Coordinate Descent Algorithm, BCD）来解决问题。仿真结果表明在视距链路和非视距链路同时存在的前提下,通过规划两架无人机的飞行轨迹,信号功率,能有效提升无人机通信系统的保密速率。      

Efficient data management and control over WSNs using SDN‐enabled aerial networks

The recent developments in collaborative search, acquisition, and tracking have hoisted the geographical barrier. The network between unmanned aerial vehicles (UAVs) and wireless sensor networks (WSNs) is one such collaboration, which comprises battery‐powered static sensor nodes that act as sources and sinks and UAVs that act as relays. This collaborative network presents with opportunities and advantages, but at the same time, configuration of such networks is an arduous task. The WSN nodes are characterized by constant depleting power. Their network itself requires constant management and reconfiguration. These requisites can be slaked through the formation of an efficient data dissemination algorithm, which acclimates according to the network state. Considering this, a data dissemination approach is presented in this paper, which constructs a virtual topology predicated on the charge of WSN nodes utilizing software‐defined networks (SDNs) through UAVs. The topology is constantly monitored and reconfigured when required. The aerial nodes are equipped with multiple‐input multiple‐output (MIMO) antennas in order to facilitate simultaneous communication with the ground nodes, the base station, and the SDN controller. An efficient sleep timer and backoff counter strategies are also utilized by the proposed approach. The SDN controller facilitates the topology formation and maintenance of a sleep timer and a backoff counter. The proposed model is compared with clustered hierarchical layouts and hexagonal cell layouts through the network simulations. The results suggest significant improvements in the proposed model for various metrics, such as lifetime, delay, latency, delivery ratio, and throughput in comparison with the existing solutions.     

ECaD: Energy‐efficient routing in flying ad hoc networks

Much progress can be expected in the domain of unmanned aerial vehicle (UAV) communication by the next decade. The cooperation between multiple UAVs in the air exchanging data among themselves can naturally form a flying ad hoc network (FANET). Such networks can be the key support to accomplish several kinds of missions while providing the required assistance to terrestrial networks. However, they are confronted with many challenges and difficulties, which are due to the high mobility of UAVs, the frequent packet losses, and the weak links between UAVs, all affecting the reliability of the data delivery. Furthermore, the unbalanced energy consumption may result in earlier UAV failure and consequently accelerate the decrease of the network lifetime, thus disrupting the overall network. This paper supports the use of the movement information and the residual energy level of each UAV to guarantee a high level of communication stability while predicting a sudden link breakage prior to its occurrence. A robust route discovery process is used to explore routing paths where the balanced energy consumption, the link breakage prediction, and the connectivity degree of the discovered paths are all considered. The performance of the scheme is evaluated through a series of simulations. The outcomes demonstrate the benefits of the proposed scheme in terms of increasing the lifetime of the network, minimizing the number of path failures, and decreasing the packet losses.     

Fair end‐to‐end window‐based congestion control in time‐varying data communication networks

Communication networks are time varying and, hence, fair sharing of network resources among the users in such a dynamic environment is a challenging task. In this context, a time‐varying network model is designed, and the shortest user's route is found. In the designed network model, an end‐to‐end window‐based congestion control scheme is developed with the help of internal nodes or router, and the end user can get implicit feedback (throughput). This scheme is considered as fair if the allocation of resources among users minimizes overall congestion or backlog in the networks. Window update approach is based on a multi‐class fluid model and is updated dynamically by considering delays (communication, propagation, and queuing) and the backlog of packets in the user's routes. Convergence and stability of the window size are obtained using a Lyapunov function. A comparative study with other window‐based methods is also provided.     

Stackelberg game-based task offloading in mobile edge computing-enabled hierarchical multi-coalition unmanned aerial vehicle networks

The unmanned aerial vehicle (UAV) coalition networks have been widely used in emergency mission scenarios. The introduction of the mobile edge computing (MEC) paradigm into multi-coalition UAV networks further improves the mission processing performance of UAV coalitions. In this paper, we investigate the problem of minimizing total task processing delay of UAV members in MEC-enabled coalition-based UAV networks. First, we propose a hierarchical offloading model in which multiple UAV heads decide its position selection strategy and multiple UAV members decide its offloading strategy when offloading tasks to UAV heads. Considering data arrival from multiple UAV member nodes at each UAV head, the first come first served (FCFS) queuing model is introduced when the UAV head processes tasks from members. Second, the hierarchical offloading delay minimization problem is formulated as a multi-leader multi-follower Stackelberg game. The existence of a Stackelberg equilibrium (SE) is proved by showing that multi-leader subgame and multi-follower subgame are exact potential games (EPGs) with Nash equilibrium (NE). We design a best response-based hierarchical iterative offloading algorithm to solve SE. Finally, the simulation results show that the performance of the proposed scheme is better than that of other benchmark methods and the proposed scheme can effectively reduce the total delay for all UAV members.     

Adaptive offloading with MPTCP for unmanned aerial vehicle surveillance system

Unmanned aerial vehicles (UAVs) are utilized in the surveillance and reconnaissance system of hazardous locations by utilizing the feature that they can freely move away from space constraints. Furthermore, the application scope of the UAVs expanded not only for simple image data collection but also for analysis of complex image data without human intervention. However, mobile UAV systems, such as drone, have limited computing resources and battery power which makes it a challenge to use these systems for long periods of time. In this paper, we propose an AOM, Adaptive Offloading with MPTCP (Multipath TCP), architecture for increasing drone operating time. We design not only the task offloading management module via the MPTCP to utilize heterogeneous network but also the response time prediction module for mission critical task offloading decision. Through the prototype drone implementation, we show the AOM reduces the task response time and increases drone operation time.     

基于深度强化学习的无人机间通信链路智能决策

由于无人机组网灵活、快速、低成本的特性,空中基站被视为在未来无线通信中有前景的技术。无人机集群可以通过相互协调和合作,完成的复杂任务,具有重大的研究和实用价值,而无人机间的高效通信是当下面临的重大挑战。为了在满足无人机间通信速率的前提下,尽可能节省发射功率,本文提出基于深度强化学习的集群方案和功率控制的智能决策算法。首先,本文设计了三种无人机集群方案,以对地面用户提供无缝的无线覆盖;然后,本文提出了基于深度Q网络（Deep Q-network）算法的集群方案和功率控制决策算法,用深度神经网络输出不同条件下联合决策的无人机集群方案和发射功率,并研究了重要性采样技术,提高训练效率。仿真结果表明,本文提出的深度强化学习算法能够正确决策无人机集群方案和发射功率,与不带强化学习的深度学习（Deep Learning Without Reinforcement Learning, DL-WO-RL）算法相比,用更低的发射功率满足无人机之间的通信速率要求,并且重要性采样技术能够缩短DQN算法的收敛时间。      

激光供能无人机集群充电策略研究

在复杂的环境中,单个无人机(UAV)执行任务的效率比较低,因此UAV越来越趋向于集群化、协作化。对于激光供能UAV集群来说,高效的充电调度对提高UAV集群的生存能力至关重要。本文提出了一种基于实时能量检测的在线充电策略(REDOCS)。根据UAV各个时刻的剩余能量计算出UAV的实时能量消耗率,然后计算每个UAV的剩余飞行时间以此来选择需要充电的UAV。相较于离线充电策略,REDOCS可以在提高整个网络的运行效率的同时降低UAV集群迫降率。最后通过算例验证,证明了REDOCS在UAV集群充电调度上表现更优。     

机动飞行环境无人机航拍图像拼接技术研究

以实战环境下无人机航拍图像的全景拼接为研究目的,提出了一种适用于无人机在机动飞行条件下的航空图像拼接算法,该算法采用空间变换、特征识别、匹配相关和信息融合等图像处理技术,可实现序列图像空间旋转、变形、尺度变换等特殊情况下的无缝拼接,通过真实使用环境试验测试,该算法具有在多种机动飞行环境下航拍图像拼接准确的特点,取得了良好的效果。     

无人机自主编队飞行控制的技术问题

从未来无人机的性能需求出发,详细描述了无人机编队飞行的功能特点和核心技术。根据无人机的任务要求,将编队飞行分为作战编队、侦察编队和混合协同编队,同时研究了编队飞行控制的关键技术,并对无人机编队重构技术进行了探讨和分析。     

无人机激光无线能量传输APT系统跟踪设计

无人机激光无线能量传输捕获、瞄准、跟踪(APT)系统是系统接收端获得稳定能源的保障。为了解决能量传输过程中充电链路高效可靠的问题, 结合无人机激光能量传输系统特点及实际需求, 在设计中建立自适应感兴趣区域, 提高图像处理速度, 降低噪声, 准确提取目标坐标; 综合考虑多重误差后通过Kalman预测算法实现稳定跟踪, 并根据系统特点提出了系统功率传输效率的计算方案。结果表明, 当无人机飞行速率在18km/h内, 该APT系统能够在300m~500m距离准确跟踪无人机, 跟踪精度在320μrad内。该方案能够保证激光能量传输过程的跟踪精度与可靠性。     

Low-cost camera based sense and avoid in unmanned aerial vehicles: Sensing and control methods

Over the past two decades, unmanned aerial vehicles (UAVs) have attracted more and more attention because of their increasing applications in the military and civil sectors. Collision avoidance is a core problem in developing UAVs. In this paper, a low-cost camera based sense and avoid control scheme is proposed. First, for the unmanned aerial vehicle (UAV) sense and avoid problem, we propose and demonstrate a low cost solution with only one monocular, wide field of view camera. We adapted a deep learning based algorithm and made it lightweight enough to run on-board the UAV. We created a synthetic dataset to increase the size of the training data set. Second, we developed a filter to estimate the 3D position and velocity of the moving obstacle. Third, based on the estimated information, we adapted the velocity obstacle approach to work in 3D. Finally, we implemented the algorithms in the software framework of our UAV testbed and conducted flight tests, demonstrating the effectiveness of the solution.     

基于DRL的无人机辅助边缘计算服务质量优化

针对无人机（Unmanned Aerial Vehicle, UAV）搭载移动边缘服务器为地面用户进行服务时的服务质量（Quality of Service, QoS）问题,提出了一种基于深度强化学习的优化方案,旨在优化UAV飞行轨迹和卸载方案以最大化UAV为用户服务时的QoS。首先,定义了任务延迟来表征任务新鲜度,在任务延迟的基础上提出了一种新的QoS评价指标;其次,将最大化QoS问题建模为一个无转移概率的马尔可夫决策过程,并定义了该过程的状态空间、动作空间和奖励函数;最后,UAV通过所提出的算法进行训练,优化任务卸载方案并寻找最优飞行轨迹为地面用户进行服务以提高QoS。仿真结果表明所提算法较于其他算法能有效提高UAV为地面用户服务过程中的QoS且提高任务新鲜度。      

On the secrecy performance of integrated satellite‐aerial‐terrestrial networks

This paper investigates secure transmission of an integrated satellite‐aerial‐terrestrial network (ISATN), where multiple eavesdroppers (Eves) attempt to overhear the satellite signals cooperatively. The ISATN adopts an unmanned aerial vehicle (UAV) equipped with multiple antennas as a relay with threshold‐based decode‐and‐forward (DF) protocol. By assuming that perfect instantaneous channel state information (CSI) of the satellite‐UAV link and the statistical CSI of the UAV‐user link are available, we first propose a beamforming (BF) scheme for maximizing the achievable secrecy rate (ASR) of the considered network. Then, we derive the analytical expressions of the secrecy outage probability (SOP) and ergodic secrecy rate (ESR) of the considered system with the BF strategy under an assumption that the satellite‐UAV link undergoes the shadowed‐Rician fading, while the UAV‐user link experiences the correlated Rayleigh fading. Finally, numerical results are given to demonstrate the superiority of the proposed BF scheme against zero forcing (ZF) and maximal ratio transmission (MRT) schemes and the validity of the secrecy performance analysis.     

Triboelectricity Based Self-Powered Digital Displacement Sensor for Aircraft Flight Actuation

The utilization of unmanned aerial vehicles (UAVs) is on the rise across various industries. In such a scenario, the issue of flight safety for these UAVs becomes increasingly paramount. Currently, UAVs exhibit shortcomings in flight attitude perception compared to more mature manned aircraft, especially concerning the position sensing of flight actuation, which poses significant safety risks. Mature position monitoring solutions for flight actuation used in manned aircraft cannot be directly integrated into systems of UAV due to compatibility issues. This necessitates the development of new position sensing technologies to address this challenge. Triboelectric nanogenerators, with their advantages of miniaturization, self-powering capabilities, and the ability to generate voltage-level electrical signals, are chosen to form a part of the position detection system for sensors in UAVs. In this study, a self-powered displacement sensor is developed that utilizes frictional charge separation signals. This sensor is specifically designed to monitor the position status of the flight actuators in UAV. With a compact volume of <11.1 cm³ and a weight of <9.5 g, this sensor is lightweight efficient and adaptable for practical applications.     

Efficient slice‐aware H.264/AVC video transmission over time‐driven priority networks

This paper proposes a multimedia streaming architecture that combines network and video technologies to handle video traffic over multi‐hop access networks. In this context, resource overprovision typical of current quality of service approaches will become a limiting factor because of the increasing spread of bandwidth‐intensive multimedia applications. The proposed scheme adopts a time‐driven priority scheduling at network nodes and exploits slice classification at the video encoder to differentiate packets. The service guarantees offered by time‐driven priority, together with the packet classification, significantly reduce congestion and increase the video quality at the receiver with respect to the traditional differentiated services (DiffServ) approach, also achieving high resource utilization. This is an important result, as current DiffServ‐based architectures are far from obtaining such resource utilization in conjunction with reasonable delays and jitters. Copyright © 2013 John Wiley & Sons, Ltd.     

Goodput and throughput comparison of single‐hop and multi‐hop routing for IEEE 802.11 DCF‐based wireless networks under hidden terminal existence

We investigate how multi‐hop routing affects the goodput and throughput performances of IEEE 802.11 distributed coordination function‐based wireless networks compared with direct transmission (single hopping), when medium access control dynamics such as carrier sensing, collisions, retransmissions, and exponential backoff are taken into account under hidden terminal presence. We propose a semi‐Markov chain‐based goodput and throughput model for IEEE 802.11‐based wireless networks, which works accurately with both multi‐hopping and single hopping for different network topologies and over a large range of traffic loads. Results show that, under light traffic, there is little benefit of parallel transmissions and both single‐hop and multi‐hop routing achieve the same end‐to‐end goodput. Under moderate traffic, concurrent transmissions are favorable as multi‐hopping improves the goodput up to 730% with respect to single hopping for dense networks. At heavy traffic, multi‐hopping becomes unstable because of increased packet collisions and network congestion, and single‐hopping achieves higher network layer goodput compared with multi‐hop routing. As for the link layer throughput is concerned, multi‐hopping increases throughput 75 times for large networks, whereas single hopping may become advantageous for small networks. The results point out that the end‐to‐end goodput can be improved by adaptively switching between single hopping and multi‐hopping according to the traffic load and topology. Copyright © 2015 John Wiley & Sons, Ltd.