scholarly journals Intelligent Spectrum Management and Trajectory Design for UAV-Assisted Cognitive Ambient Backscatter Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Jiazhou Liu ◽  
Sa Xiao ◽  
Huayan Guo ◽  
Xiangwei Zhou ◽  
Shixin He

In this paper, we consider a novel Internet of Things (IoT) system in smart city called unmanned aerial vehicle- (UAV-) assisted cognitive backscatter network, where a UAV is employed as both a relay and a radio frequency source to help the data transmission between ground IoT backscatter devices (BDs) and a remote data center (DC). However, since the IoT applications are usually not assigned dedicated spectrum resource in smart cities, these data transmissions from BDs to the DC should share the licensed spectrum of cellular users (CUs). Therefore, we aim to maximize the minimum uplink throughput among all BDs while avoiding severe interference to CUs via joint spectrum management and UAV trajectory design. To solve the problem, we propose an iterative method utilizing block coordinated decent to partition the variables into two blocks. For the spectrum management problem, we first prove its convexity with the transmit power and time scheduling and then propose a two-step method to solve the two variables sequentially. For the UAV trajectory design problem, we resort to the fractional programming method to handle it. Simulation results demonstrate that the proposed algorithm can significantly increase the average max-min rate of the BDs while guaranteeing the acceptable interference to CUs with a fast convergence speed.

2022 ◽  
pp. 1459-1480
Author(s):  
Anand Nayyar ◽  
Rachna Jain ◽  
Bandana Mahapatra ◽  
Anubhav Singh

Smart cities are composed of interlinked components with constant data transfer and services targeted at increasing the life style of the people. The chapter focuses on diverged smart city components as well as the security models designed to be implemented. The four major paradigms discussed in this chapter are smart grids, building automation system (BAS), unmanned aerial vehicle (UAV), and smart vehicles. Apart from addressing the security concerns of every component, the major highlights of this chapter are architecture, smart environment, industry, lifestyle, services, and digital lifestyle quality. Finally, the chapter focuses on privacy preserving mechanisms, its essence over smart cities, strong architecture related to privacy, preserving mechanism, and various approaches available that can retaliate these issues in a smart city environment.


Facilities ◽  
2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Patrick T.I. Lam ◽  
Daniel Lai ◽  
Chi-Kin Leung ◽  
Wenjing Yang

Purpose As smart cities flourish amidst rapid urbanization and information and communication technology development, the demand for building more and more data centers is rising. This paper aims to examine the principal issues and considerations of data center facilities from the cost and benefit dimensions, with an aim to illustrate the approaches for maximizing the net benefits and remain “green.” Design/methodology/approach A comprehensive literature review informs the costs and benefits of data center facilities, and through a case study of a developer in Hong Kong, the significance of real estate costs is demonstrated. Findings Major corporations, establishments and governments need data centers as a mission critical facility to enable countless electronic transactions to take place any minute of the day. Their functional importance ranges from health, transport, payment, etc., all the way to entertainment activities. Some enterprises own them, whilst others use data center services on a co-location basis, in which case data centers are regarded as an investment asset. Real estate costs affect their success to a great extent, as in the case of a metropolitan where land cost forms a substantial part of the overall development cost for data centers. Research limitations/implications As the financial information of data center projects are highly sensitive due to the competitive status of the industry, a full set of numerical data is not available. Instead, the principles for a typical framework are established. Originality/value Data centers are very energy intensive, and their construction is usually fast tracked costing much to build, not to mention the high-value equipment contents housed therein. Their site locations need careful selection due to stability and security concerns. As an essential business continuity tool, the return on investment is a complex consideration, but certainly the potential loss caused by any disruption would be a huge amount. The life cycle cost and benefit considerations are revealed for this type of mission-critical facilities. Externalities are expounded, with emphasis on sustainable issues. The impact of land shortage for data center development is also demonstrated through the case of Hong Kong.


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.


2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
An Li ◽  
Huohuo Han ◽  
Chuanxin Yu

This paper investigates the problem of maximizing the secrecy energy efficiency (SEE) for unmanned aerial vehicle- (UAV-) to-ground wireless communication system, in which a fixed-wing UAV tries to transmit covert information to a terrestrial legitimate destination receiver with multiple terrestrial eavesdroppers. In particular, we intend to maximize the worst-case SEE of UAV by jointly optimizing UAV’s flight trajectory and transmit power over a finite flight period. However, the formulated problem is challenging to solve because of its large-scale nonconvexity. For efficiently solving this problem, we first decouple the above optimization problem into two subproblems and then propose an alternating iterative algorithm by adopting block coordinate descent method and Dinkelbach’s algorithm as well as successive convex approximation technique to seek a suboptimal solution. For the sake of performance comparison, two benchmark schemes, the secrecy rate maximization (SRM) scheme and constrained energy minimization (CEM) scheme are considered to obtain more useful insights. Finally, simulation results are executed to verify that our proposed SEE maximization (SEEM) algorithm is superior to two benchmark schemes for the UAV-ground communication system.


2021 ◽  
Vol 38 (5) ◽  
pp. 1403-1411
Author(s):  
Nashwan Adnan Othman ◽  
Ilhan Aydin

An Unmanned Aerial Vehicle (UAV), commonly called a drone, is an aircraft without a human pilot aboard. Making UAVs that can accurately discover individuals on the ground is very important for various applications, such as people searches, and surveillance. UAV integration in smart cities is challenging, however, because of problems and concerns such as privacy, safety, and ethical/legal use. Human action recognition-based UAVs can utilize modern technologies. Thus, it is essential for future development of the aforementioned applications. UAV-based human activity recognition is the procedure of classifying photo sequences with action labels. This paper offers a comprehensive study of UAV-based human action recognition techniques. Furthermore, we conduct empirical research studies to assess several factors that might influence the efficiency of human detection and action recognition techniques in UAVs. Benchmark datasets commonly utilized for UAV-based human action recognition are briefly explained. Our findings reveal that the existing human action recognition innovations can identify human actions on UAVs with some limitations in range, altitudes, long-distance, and a large angle of depression.


Energies ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2880
Author(s):  
Abbas Akbari ◽  
Ahmad Khonsari ◽  
Seyed Mohammad Ghoreyshi

In recent years, a large and growing body of literature has addressed the energy-efficient resource management problem in data centers. Due to the fact that cooling costs still remain the major portion of the total data center energy cost, thermal-aware resource management techniques have been employed to make additional energy savings. In this paper, we formulate the problem of minimizing the total energy consumption of a heterogeneous data center (MITEC) as a non-linear integer optimization problem. We consider both computing and cooling energy consumption and provide a thermal-aware Virtual Machine (VM) allocation heuristic based on the genetic algorithm. Experimental results show that, using the proposed formulation, up to 30 % energy saving is achieved compared to thermal-aware greedy algorithms and power-aware VM allocation heuristics.


2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Lantu Guo ◽  
Meiyu Wang ◽  
Yun Lin

With the development of IoT in smart cities, the electromagnetic environment (EME) in cities is becoming more and more complex. A full understanding of the characteristics of past spectrum resource utilization is the key to improving the efficiency of spectrum management. In order to explore the characteristics of spectrum utilization more comprehensively, this paper designs an EME portrait model. By checking the statistical information of the spectrum data, including changes in the noise floor and channel utilization in each individual wireless service, the correlation between the spectrum and time or space of different channels and the information is merged into a high-dimensional model through consistency transformation to form the EME portrait. The portrait model is not only convenient for storage and retrieval but also beneficial for transfer and expansion, which will become an important foundation for intelligent electromagnetic spectrum management.


2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Liming Chen ◽  
Xiaoyun Kuang ◽  
Fusheng Zhu ◽  
Lijia Lai ◽  
David Fan

In this paper, we provide a comprehensive survey for the artificial intelligence and spectrum management, which are used for cache-enabled Internet of Things (IoT) in smart cities. In smart cities, there emerge a lot of new applications such as data collection and communication, environment monitoring, and real-time processing, which cannot be supported by the conventional wireless transmission techniques. Hence, some new wireless transmission techniques should be developed to support the emerging applications in smart cities. In this survey, we focus on the artificial intelligence, spectrum management, and caching techniques, where the interference arises due to the limited spectrum resources. In particular, we first review the current research status of these new techniques and, then, give some challenges on the system design. We further provide several feasible solutions on these challenges, in order to implement the IoT networks in smart cities. Finally, we conclude the work in the part of conclusions and give some discussions on the future works.


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