Unmanned Aerial Vehicle (UAV)-assisted communication has drawn increasing attention recently. In this paper, we investigate 3D UAV trajectory design and band allocation problem considering both the ...UAV's energy consumption and the fairness among the ground users (GUs). Specifically, we first formulate the energy consumption model of a quad-rotor UAV as a function of the UAV's 3D movement. Then, based on the fairness and the total throughput, the fair throughput is defined and maximized within limited energy. We propose a deep reinforcement learning (DRL)-based algorithm, named as EEFC-TDBA (energy-efficient fair communication through trajectory design and band allocation) that chooses the state-of-the-art DRL algorithm, deep deterministic policy gradient (DDPG), as its basis. EEFC-TDBA allows the UAV to: 1) adjust the flight speed and direction so as to enhance the energy efficiency and reach the destination before the energy is exhausted; and 2) allocate frequency band to achieve fair communication service. Simulation results are provided to demonstrate that EEFC-TDBA outperforms the baseline methods in terms of the fairness, the total throughput, as well as the minimum throughput.
VANETs enable information exchange among vehicles, other end devices and public networks, which plays a key role in road safety/infotainment, intelligent transportation systems, and self-driving ...systems. As vehicular connectivity soars, and new on-road mobile applications and technologies emerge, VANETs are generating an ever-increasing amount of data, requiring fast and reliable transmissions through VANETs. On the other hand, a variety of VANETs related data can be analyzed and utilized to improve the performance of VANETs. In this article, we first review VANETs technologies to efficiently and reliably transmit big data. Then, the methods employing big data for studying VANETs characteristics and improving VANETs performance are discussed. Furthermore, we present a case study where machine learning schemes are applied to analyze VANETs measurement data for efficiently detecting negative communication conditions.
Space-air-ground integrated network (SAGIN) is envisioned as a promising solution to provide cost-effective, large-scale, and flexible wireless coverage and communication services. Since realworld ...deployment for testing of SAGIN is difficult and prohibitive, an efficient SAGIN simulation platform is requisite. In this article, we present our developed SAGIN simulation platform which supports various mobility traces and protocols of space, aerial, and terrestrial networks. Centralized and decentrallized controllers are implemented to optimize the network functions such as access control and resource orchestration. In addition, various interfaces extend the functionality of the platform to facilitate user-defined mobility traces and control algorithms. We also present a case study where highly mobile vehicular users dynamically choose different radio access networks according to their quality of service (QoS) requirements.
Internet of Things (IoT) allows billions of physical objects to be connected to collect and exchange data for offering various applications, such as environmental monitoring, infrastructure ...management, and home automation. On the other hand, IoT has unsupported features (e.g., low latency, location awareness, and geographic distribution) that are critical for some IoT applications, including smart traffic lights, home energy management and augmented reality. To support these features, fog computing is integrated into IoT to extend computing, storage and networking resources to the network edge. Unfortunately, it is confronted with various security and privacy risks, which raise serious concerns towards users. In this survey, we review the architecture and features of fog computing and study critical roles of fog nodes, including real-time services, transient storage, data dissemination and decentralized computation. We also examine fog-assisted IoT applications based on different roles of fog nodes. Then, we present security and privacy threats towards IoT applications and discuss the security and privacy requirements in fog computing. Further, we demonstrate potential challenges to secure fog computing and review the state-of-the-art solutions used to address security and privacy issues in fog computing for IoT applications. Finally, by defining several open research issues, it is expected to draw more attention and efforts into this new architecture.
Recently, many academic institutions and standardization organizations have conducted research on vehicular communications based on LTE or 5G. As the most important standardization organization of ...cellular systems, the 3rd Generation Partnership Project (3GPP) has been developing the standard supporting vehicle-to-everything (V2X) services based on LTE, and has already prepared the roadmap toward 5G-based V2X services. With the emergence of new technologies and applications, such as connected autonomous vehicles, 5G-enabled vehicular networks face a variety of security and privacy challenges, which have not been fully investigated. In this article, we first present the infrastructure of 5G-enabled vehicular networks. Then the essential security and privacy aspects of V2X in LTE specified by 3GPP are introduced. After that, as a case study, we investigate the security and privacy issues of a 5G-enabled autonomous platoon, and propose several candidate solutions, including secure group setup with privacy preservation, distributed group key management, and cooperative message authentication. Finally, we discuss the security and privacy challenges in 5G-enabled vehicular networks.
Along with the popularity of mobile social networks (MSNs) is the increasing danger of privacy breaches due to user location exposures. In this work, we take an initial step towards quantifying ...location privacy leakage from MSNs by matching the users' shared locations with their real mobility traces. We conduct a three-week real-world experiment with 30 participants and discover that both direct location sharing (e.g., Weibo or Renren) and indirect location sharing (e.g., Wechat or Skout) can reveal a small percentage of users' real points of interests (POIs). We further propose a novel attack to allow an external adversary to infer the demographics (e.g., age, gender, education) after observing users' exposed location profiles. We implement such an attack in a large real-world dataset involving 22,843 mobile users. The experimental results show that the attacker can effectively predict demographic attributes about users with some shared locations. To resist such attacks, we propose SmartMask, a context-based system-level privacy protection solution, designed to automatically learn users' privacy preferences under different contexts and provide a transparent privacy control for MSN users. The effectiveness and efficiency of SmartMask have been well validated by extensive experiments.
Enabling HD-map-assisted cooperative driving among CAVs to improve navigation safety faces technical challenges due to increased communication traffic volume for data dissemination and an increased ...number of computing/storing tasks on CAVs. In this article, a new architecture that combines MEC and SDN is proposed to address these challenges. With MEC, the interworking of multiple wireless access technologies can be realized to exploit the diversity gain over a wide range of radio spectrum, and at the same time, computing/storing tasks of a CAV are collaboratively processed by servers and other CAVs. By enabling NFV in MEC, different functions can be programmed on the server to support diversified AV applications, thus enhancing the server's flexibility. Moreover, by using SDN concepts in MEC, a unified control plane interface and global information can be provided, and by subsequently using this information, intelligent traffic steering and efficient resource management can be achieved. A case study is presented to demonstrate the effectiveness of the proposed architecture.
Consumer privacy and consumption confidentiality and integrity are the main security concerns for smart grid connection with the residential electricity consumers. This paper proposes a lightweight ...privacy-preserving electricity consumption aggregation scheme that exploits lightweight lattice-based homomorphic cryptosystem. In the proposed scheme, smart household appliances aggregate their readings without involving the smart meter. Although smart meters or the intermediate base station cannot decrypt this aggregated consumption, they can validate the message's authenticity. The proposed scheme also investigates the impact of different types of smart appliances on the home area network's overhead. The total communication and computation load for the proposed scheme is trivial and tolerable by different parties in the connection, i.e., smart appliances, smart meters, and the base station. In addition, the deployed cryptosystem, which depends on simple arithmetic operations, can further reduce the computation duty for smart appliances. Simulation results and security analysis show that our proposed scheme guarantees consumers privacy, and messages authenticity and integrity, with lightweight communication and computation complexity.
Vehicle-to-grid (V2G) connection allows a two-way electricity transmission between electric vehicles (EVs) and the power grid for achieving many known benefits. However, V2G connections suffer from ...certain security threats, such as to the EV's privacy and in authenticating the EV to the grid. In this paper, we propose a lightweight secure and privacy-preserving V2G connection scheme in which the power grid assures the confidentiality and integrity of exchanged information during (dis)charging electricity sessions and overcomes the EVs' authentication problem. The proposed scheme guarantees the financial profits of the grid and prevents EVs from acting maliciously. Meanwhile, EVs preserve their private information by generating their own pseudonym identities. In addition, the scheme maintains accountability for the electricity exchange trade. Furthermore, the proposed scheme provides these security requirements by lightweight overhead, as it diminishes the number of exchanged messages during (dis)charging sessions. Simulation results demonstrate that the proposed scheme significantly reduces the total communication and computation load for V2G connection, particularly for EVs.
Mobile video streaming is fundamental to advanced applications in the fifth generation (5G) networks. Millimeter wave (mmWave) communication represents a leading 5G technology, which provides rich ...bandwidth and, therefore, great potentials for high-quality mobile video streaming. However, mobile video streaming in mmWave 5G networks faces fundamental challenges due to mmWave antenna directivity and high user mobility. As such, users typically have short connection durations and frequent handoffs, making video streaming suffer from long handoff delays and connection latency. In this paper, we tackle the issues by developing a caching-based mmWave framework, which precaches video contents at the base station for handoff users and thus significantly reduces the connection and retrieval delays. As a result, high-mobility users with frequent handoffs can enjoy continuous high-quality video streaming. Specifically, we model the proposed system as a cache management problem and attain optimal video streaming quality by using Markov decision process to dynamically allocate proper cache memory space of each base station to mobile users. A cell-by-cell decomposition method is proposed to solve the dynamic programming problem with significantly reduced computational complexity. Using extensive simulations, we demonstrate that the proposed solution can effectively maintain high-quality mobile video streaming for high-mobility 5G users moving among mmWave small cells with directional antenna.
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