HTTP Adaptive Streaming (HAS) is becoming the de-facto video delivery technology over best-effort networks nowadays, thanks to the myriad advantages it brings. However, many studies have shown that HAS suffers from many Quality of Experience (QoE)-related issues in the presence of competing players. This is mainly caused by the selfishness of the players resulting from the decentralized intelligence given to the player. Another limitation is the bottleneck link that could happen at any time during the streaming session and anywhere in the network. These issues may result in wobbling bandwidth perception by the players and could lead to missing the deadline for chunk downloads, which result in the most annoying issue consisting of rebuffering events. In this paper, we leverage the SoftwareDefined Networking paradigm to take advantage of the global view of the network and its powerful intelligence that allows reacting to the network changing conditions. Ultimately, we aim at preventing the re-buffering events, resulting from deadline misses, and ensuring high QoE for the accepted clients in the system. To this end, we use Deterministic Network Calculus (DNC) to guarantee a maximum delay for the download of the video chunks while maximizing the perceived video quality. Simulation results show that the proposed solution ensures high efficiency for the accepted clients without any rebuffering events which result in high user QoE. Consequently, it might be highly useful for scenarios where video chunks should be strictly downloaded on-time or ensuring low delay with high user QoE such as serving video premium subscribers or remote control/driving of an autonomous vehicle in future 5G mobile networks.
The consideration of mobile networks as a communication infrastructure for unmanned aerial vehicles (UAVs) creates a new plethora of emerging services and opportunities. In particular, the availability of different mobile network operators (MNOs) can be exploited by the UAVs to steer connection to the MNO ensuring the best quality of experience (QoE). While the concept of traffic steering is more known at the network side, extending it to the device level would allow meeting the emerging requirements of today's applications. In this vein, an efficient steering solutions that take into account …
Next-generation networks need to meet ubiquitous and high data-rate demand. Therefore, this paper considers the throughput and trajectory optimization of terahertz (THz)-enabled unmanned aerial vehicles (UAVs) in the sixth-generation (6G) communication networks. In the considered scenario, multiple UAVs must provide on-demand terabits per second (TB/s) services to an urban area along with existing terrestrial networks. However, THz-empowered UAVs pose some new constraints, e.g., dynamic THz-channel conditions for ground users (GUs) association and UAV trajectory optimization to fulfill GU's th…
This paper aims to propose a three-dimensional (3D) point process that can be employed to generally deploy unmanned aerial vehicles (UAVs) in a large-scale cellular network and tractably analyze the fundamental network-wide performances of the network. This 3D point process is devised based on a 2D marked Poisson point process in which each point and its random mark uniquely correspond to the projection and the altitude of each point in the 3D point process, respectively. We elaborate on some important statistical properties of the proposed 3D point process and use them to tractably analyze th…
This paper investigates traffic flow modeling issue in multi-services oriented unmanned aerial vehicle (UAV)-enabled wireless networks, which is critical for supporting future various applications of such networks. We propose a general traffic flow model for multi-services oriented UAV-enable wireless networks. Under this model, we first classify the network services into three subsets: telemetry, Internet of Things (IoT), and streaming data. Based on the Pareto distribution, we then partition all UAVs into three subgroups with different network usage. We further determine the number of packet…
Anomaly detection for the Internet of Things (IoT) is a major intelligent service required by many fields, including intrusion detection, device-activity analysis, and security supervision. However, the heterogeneous distribution of data and resource-constrained end nodes present challenges for existing anomaly detection models. Due to the advantages of flexible deployment and multi-dimensional resources, high altitude platform stations (HAPSs) and unmanned aerial vehicles (UAVs), which are important components of vertical heterogeneous networks (VHetNets), have significant potential for sensi…
In this paper, we propose a novel joint intelligent trajectory design and resource allocation algorithm based on user's mobility and their requested services for unmanned aerial vehicles (UAVs) assisted networks, where UAVs act as nodes of a network function virtualization (NFV) enabled network. Our objective is to maximize energy efficiency and minimize the average delay on all services by allocating the limited radio and NFV resources. In addition, due to the traffic conditions and mobility of users, we let some Virtual Network Functions (VNFs) to migrate from their current locations to othe…
Due to the advanced capabilities of the Internet of Vehicles (IoV) components such as vehicles, Roadside Units (RSUs) and smart devices as well as the increasing amount of data generated, Federated Learning (FL) becomes a promising tool given that it enables privacy-preserving machine learning that can be implemented in the IoV. However, the performance of the FL suffers from the failure of communication links and missing nodes, especially when continuous exchanges of model parameters are required. Therefore, we propose the use of Unmanned Aerial Vehicles (UAVs) as wireless relays to facilitat…
The proliferation of the Internet of Things (IoT) technologies have strengthen the self-monitoring and autonomous characteristics of the sensor networks deployed in numerous application areas. The recent developments of the edge computing paradigms have also enabled on-site processing and managing capabilities of sensor networks. In this paper, we introduce a system model that enables end-to-end secure connectivity between low-power IoT devices and UAVs, that helps to manage data processing tasks of a heterogeneous wireless sensor networks. The performance of proposed solution is analyzed by u…
AP Association for RHS-Enabled Cell-Free Uplink MIMO in Industrial Indoor UAV Networks
Shanghai Jiao Tong University（上海交通大学）；Xi’an Jiaotong University（西安交通大学）；Jiangnan University（江南大学）；Beijing University of Posts and Telecommunications（北京邮电大学）
Wireless Federated Learning over UAV-enabled Integrated Sensing and Communication
University of Alabama in Huntsville（阿拉巴马大学亨茨维尔分校）；University of Glasgow（格拉斯哥大学）；Manchester Metropolitan University（曼彻斯特城市大学）；Lac Hong University（Lac Hong大学）
UAV Control and Communication Enabled Low-Altitude Economy: Challenges, Resilient Architecture and Co-design Strategies
School of Information Science and Technology, Harbin Institute of Technology, Shenzhen（哈尔滨工业大学深圳校区信息科学与技术学院）；Information System Technology and Design, Singapore University of Technology and Design（新加坡科技设计大学信息系统技术设计系）；ChinaTelecom Singapore Innovation Research Institute（中国电信新加坡创新研究院）；Information System Technology and Design Pillar, Singapore University of Technology and Design, Singapore（新加坡科技设计大学信息系统技术设计支柱）
Northumbria University（诺森比亚大学）；Central South University（中南大学）；China University of Mining and Technology（中国矿业大学）；University of Glasgow（格拉斯哥大学）；University of Essex（埃塞克斯大学）
In this paper, multi-unmanned aerial vehicle (UAV) enabled mobile edge computing (MEC), i.e., UAVE is studied, where several UAVs are deployed as flying MEC platform to provide computing resource to ground user equipments (UEs). Compared to the traditional fixed location MEC, UAV enabled MEC (i.e., UAVE) is particular useful in case of temporary events, emergency situations and on-demand services, due to its high flexibility, low cost and easy deployment features. However, operation of UAVE faces several challenges, two of which are how to achieve both 1) the association between multiple UEs a…
Diffusion-based Auction Mechanism for Efficient Resource Management in 6G-enabled Vehicular Metaverses
School of Automation, Guangdong University of Technology（广东工业大学自动化学院）；School of Computer Science and Engineering, Nanyang Technological University（南洋理工大学计算机科学与工程学院）；Department of Electrical and Computer Engineering, Auburn University（奥本大学电气与计算机工程系）
Coupled with the rise of Deep Learning, the wealth of data and enhanced computation capabilities of Internet of Vehicles (IoV) components enable effective Artificial Intelligence (AI) based models to be built. Beyond ground data sources, Unmanned Aerial Vehicles (UAVs) based service providers for data collection and AI model training, i.e., Drones-as-a-Service, is increasingly popular in recent years. However, the stringent regulations governing data privacy potentially impedes data sharing across independently owned UAVs. To this end, we propose the adoption of a Federated Learning (FL) based…
Unmanned Aerial Vehicles (UAVs) enabled communications is a novel and attractive area of research in cellular communications. It provides several degrees of freedom in time, space and it can be used for multiple purposes. This is why wide deployment of UAVs has the potential to be integrated in the upcoming 5G standard. In this paper, we present a novel cell outage compensation (COC) framework to mitigate the effect of the failure of any outdoor Base Station (BS) in 5G networks. Within our framework, the outage compensation is done with the assistance of sky BSs (UAVs) and Ground BSs (GBSs). A…
In this paper, we provide a performance analysis for practical unmanned aerial vehicle (UAV)-enabled networks. By considering both line-of-sight (LoS) and non-line-of-sight (NLoS) transmissions between aerial base stations (BSs) and ground users, the coverage probability and the area spectral efficiency (ASE) are derived. Considering that there is no consensus on the path loss model for studying UAVs in the literature, in this paper, three path loss models, i.e., high-altitude model, low-altitude model and ultra-low-altitude model, are investigated and compared. Moreover, the lower bound of th…
Coexistence of 3GPP access networks, namely 4G and 5G, and non-3GPP access networks, namely Wi-Fi, has enabled data offloading from one access network to another to reduce burden on the congested network. Within the evolution of 5G system, the coexistence has been evolved to a multi-access framework where simultaneous transmission on both 3GPP and non-3GPP access networks has been enabled. This framework is named as access traffic steering, splitting and switching (ATSSS) in 3GPP and is considered as one of the key enablers to provide stringent requirements on data rate and service continuity.…
Unmanned Aerial Vehicle (UAV) networks have emerged as a promising technique to rapidly provide wireless coverage to a geographical area, where a flying UAV can be fast deployed to serve as cell site. Existing work on UAV-enabled wireless networks overlook the fast UAV deployment for wireless coverage, and such deployment problems have only been studied recently in sensor networks. Unlike sensors, UAVs should be deployed to the air and they are generally different in flying speed, operating altitude and wireless coverage radius. By considering such UAV heterogeneity to cover the whole target a…
Unmanned aerial vehicle (UAV)-assisted multi-access edge computing (MEC) has become one promising solution for energy-constrained devices to meet the computation demand and the stringent delay requirement. In this work, we investigate a multiple UAVs-assisted two-stage MEC system in which the computation-intensive and delay-sensitive tasks of mobile devices (MDs) are cooperatively executed on both MEC-enabled UAVs and terrestrial base station (TBS) attached with the MEC server. Specifically, UAVs provide the computing and relaying services to the mobile devices. In this regard, we formulate a …
Receive side scaling (RSS) is a network interface card (NIC) technology. It provides the benefits of parallel receive processing in multiprocessing environments. However, existing RSS-enabled NICs lack a critical data steering mechanism that would automatically steer incoming network data to the same core on which its application process resides. This absence causes inefficient cache usage if an application is not running on the core on which RSS has scheduled the received traffic to be processed. In Linux systems, it cannot even ensure that packets in a TCP flow are processed by a single core…
The recent advances in information and communication technology (ICT) have further extended Internet of Things (IoT) from the sole "things" aspect to the omnipotent role of "intelligent connection of things". Meanwhile, the concept of internet of everything (IoE) is presented as such an omnipotent extension of IoT. However, the IoE realization meets critical challenges including the restricted network coverage and the limited resource of existing network technologies. Recently, Unmanned Aerial Vehicles (UAVs) have attracted significant attentions attributed to their high mobility, low cost, an…
Waterford Institute of Technology（沃特福德理工学院）；Walton Institute（沃尔顿研究所）；Northumbria University Newcastle（纽卡斯尔诺森比亚大学）；National University of Sciences and Technology（国立科技大学）
6G envisions artificial intelligence (AI) powered solutions for enhancing the quality-of-service (QoS) in the network and to ensure optimal utilization of resources. In this work, we propose an architecture based on the combination of unmanned aerial vehicles (UAVs), AI and blockchain for agricultural supply-chain management with the purpose of ensuring traceability, transparency, tracking inventories and contracts. We propose a solution to facilitate on-device AI by generating a roadmap of models with various resource-accuracy trade-offs. A fully convolutional neural network (FCN) model is us…
One of the major restrictions on the practical applications of unmanned aerial vehicles (UAV) is their incomplete self-sufficiency, which makes continuous operations infeasible without human oversights. The more oversight UAVs require, the less likely they are going to be commercially advantageous when compared to their alternatives. As an autonomous system, how much human interaction is needed to function is one of the best indicators evaluating the limitations and inefficiencies of the UAVs. Popular UAV related research areas, such as path planning and computer vision, have enabled substanti…
Blockchain-Enabled Routing for Zero-Trust Low-Altitude Intelligent Networks
College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics（南京航空航天大学电子与信息学院）；College of Civil Aviation, Nanjing University of Aeronautics and Astronautics（南京航空航天大学民航学院）；College of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics（南京航空航天大学人工智能学院）；College of Computing and Data Science, Nanyang Technological University（南洋理工大学计算机与数据科学学院）
Unmanned aerial vehicles (UAVs) are envisioned to be extensively employed for assisting wireless communications in Internet of Things (IoT) applications. On the other hand, terahertz (THz) enabled intelligent reflecting surface (IRS) is expected to be one of the core enabling technologies for forthcoming beyond-5G wireless communications that promise a broad range of data-demand applications. In this paper, we propose a UAV-mounted IRS (UIRS) communication system over THz bands for confidential data dissemination from an access point (AP) towards multiple ground user equipments (UEs) in IoT ne…
Airborne base stations (carried by drones) have a great potential to enhance coverage and capacity of cellular networks. Multiple scenarios and use cases will highly benefit from such technology such as (i) offloading terrestrial base stations (BSs) in dense and urban areas, and (ii) providing coverage for rural areas. However, one of the main challenges facing the deployment of airborne BSs is the limited available energy at the drone, which limits the flight time. In fact, most of the currently used unmanned aerial vehicles (UAVs) can only operate for one hour maximum. This limits the perfor…
Unmanned aerial vehicles (UAVs) are emerging as enablers for supporting many applications and services, such as precision agriculture, search and rescue, temporary network deployment or coverage extension, and security. UAVs are being considered for integration into emerging 5G networks as aerial users or network support nodes. We propose to leverage UAVs in 5G to assist in the prevention, detection, and recovery of attacks on 5G networks. Specifically, we consider jamming, spoofing, eavesdropping and the corresponding mitigation mechanisms that are enabled by the versatility of UAVs. We intro…
