This paper considers a laser-powered unmanned aerial vehicle (UAV)-enabled wireless power transfer (WPT) system. In the system, a UAV is dispatched as an energy transmitter to replenish energy for ...battery-limited sensors in a wireless rechargeable sensor network (WRSN) by transferring radio frequency (RF) signals, and a mobile unmanned vehicle (MUV)-loaded laser transmitter travels on a fixed path to charge the on-board energy-limited UAV when it arrives just below the UAV. Based on the system, we investigate the trajectory optimization of laser-charged UAVs for charging WRSNs (TOLC problem), which aims to optimize the flight trajectories of a UAV and the travel plans of an MUV cooperatively to minimize the total working time of the UAV so that the energy of every sensor is greater than or equal to the threshold. Then, we prove that the problem is NP-hard. To solve the TOLC problem, we first propose the weighted centered minimum coverage (WCMC) algorithm to cluster the sensors and compute the weighted center of each cluster. Based on the WCMC algorithm, we propose the TOLC algorithm (TOLCA) to design the detailed flight trajectory of a UAV and the travel plans of an MUV, which consists of the flight trajectory of a UAV, the hovering points of a UAV with the corresponding hovering times used for the charging sensors, the hovering points of a UAV with the corresponding hovering times used for replenishing energy itself, and the hovering times of a UAV waiting for an MUV. Numerical results are provided to verify that the suggested strategy provides an effective method for supplying wireless rechargeable sensor networks with sustainable energy.
In a Wireless Sensor Network (WSN), when a large amount of sensors are randomly deployed into a detection area, an efficient sleep/active scheduling for sensors to maximize the network lifetime of ...target (or detection area) coverage, which is called the coverage problem, is an important issue. The problem was proved NP-complete. Recently, many methods were proposed for solving the coverage problem, each of which can be divided into two phases: the first is to find as many as possible coverage sets from the sensors and the other is to schedule the coverage sets got from the first phase. Therefore, all coverage problems involve the scheduling process of the coverage sets to maximize the network lifetime. In this paper, we investigate the Maximum Coverage Sets Scheduling (MCSS) problem: given a coverage set collection in which each coverage set covers all targets (or the whole detection area) in WSN, the problem is to find a feasible scheduling for the coverage set collection to maximize the network lifetime. Firstly, we prove the MCSS problem is NP-hard. Secondly, we formulate the problem as an integer linear programming problem. Thirdly, we first propose a greedy algorithm, called Greedy-MCSS, to solve the MCSS problem. Then based on the Greedy-MCSS algorithm, we propose an approximation algorithm, MCSS Algorithm (MCSSA) for solving the MCSS problem, which gives the theoretical performance guarantee. Finally, extensive simulation results are shown to further verify the performance of our algorithms.
The built environment's impact on human activities has been a hot issue in urban research. Compared to motorized spaces, the built environment of pedestrian and cycling street spaces dramatically ...influences people's travel experience and travel mode choice. The streets' built environment data play a vital role in urban design and management. However, the multi-source, heterogeneous, and massive data acquisition methods and tools for the built environment have become obstacles for urban design and management. To better realize the data acquisition and for deeper understanding of the urban built environment, this study develops a new portable, low-cost Arduino-based multi-sensor array integrated into a single portable unit for built environment measurements of street cycling spaces. The system consists of five sensors and an Arduino Mega board, aimed at measuring the characteristics of the street cycling space. It takes air quality, human sensation, road quality, and greenery as the detection objects. An integrated particulate matter laser sensor, a light intensity sensor, a temperature and humidity sensor, noise sensors, and an 8K panoramic camera are used for multi-source data acquisition in the street. The device has a mobile power supply display and a secure digital card to improve its portability. The study took Beijing as a sample case. A total of 127.97 G of video data and 4794 Kb of txt records were acquired in 36 working hours using the street built environment data acquisition device. The efficiency rose to 8474.21% compared to last year. As an alternative to conventional hardware used for this similar purpose, the device avoids the need to carry multiple types and models of sensing devices, making it possible to target multi-sensor data-based street built environment research. Second, the device's power and storage capabilities make it portable, independent, and scalable, accelerating self-motivated development. Third, it dramatically reduces the cost. The device provides a methodological and technological basis for conceptualizing new research scenarios and potential applications.
The Johnson–Holmquist-II(JH-2) model is introduced as the constitutive model for rock materials in tunnel smooth blasting. However, complicated and/or high-cost experiments need to be carried out to ...obtain the parameters of the JH-2 constitutive model. This study chooses Barre granite as an example to propose a quick and convenient determination method for the parameters of the JH-2 model using a series of computational and extrapolated methods. The validity of the parameters is verified via comparing the results of 3D numerical simulations with laboratory blast-loading experiments. Subsequently, the verified parameter determination method, together with the JH-2 damage constitutive model, is applied in the numerical simulation of smooth blasting in Zigaojian tunnel, Hangzhou–Huangshan high-speed railway. The overbreak/underbreak induced by rock blasting and joints/discontinuities is well estimated through comparing the damage contours resulting from the numerical study with the tunnel profiles measured from the tunnel site. The peak particle velocities (PPVs) of the near field are extracted to estimate the damage scope and damage degree for the surrounding rock mass of the tunnel on the basis of PPV damage criteria. This method can be used in the excavation of rock tunnels subjected to large strains, high strain rates, and high pressures, thereby reducing safety risk and economic losses.
The spatial pattern of trees is an important feature of forests, and different spatial patterns of trees exhibit different ecological stability. Research has confirmed that natural forests with ...random patterns have higher biodiversity and stronger resistance to unstable factors such as pests and diseases. Even if they are disturbed or destroyed by unstable factors such as pests and diseases, they can still recover and rescue themselves; while artificial forests with uniform and clustered patterns have lower biodiversity and are susceptible to unstable factors such as pests and diseases. And once pests and diseases occur, it’s more difficult for them to recover. In order to promote the healthy and stable development of the forestry industry and protect the diversity of the biological environment, it is necessary to protect the random pattern of natural forests from being destroyed in the process of forest management, while effectively transforming the spatial pattern of artificial forests into a random pattern. Therefore, in order to ensure the convenient and accurate determination of the type of forest spatial pattern, research on methods for determining forest spatial pattern has become particularly important. Based on the theory of uniformity, this study proposes definitions and related theories of included exclusive sphere, included exclusive body, included random pattern, and included uniformity. Under the guidance of the definition of inclusion uniformity and related theories, and by using mathematical method, it is proved that the uniformity of inclusion (
CL
) is asymptotically subject to the Eq.
18
, Therefore, the relationship between the included uniformity (
CL
) and the number of trees in the sample plot was established, and the corresponding relationship formula was obtained, and then the determination of the spatial pattern type of trees was completed by using the corresponding relationship formula. Through rigorous reasoning and case verification, the determination method of forest spatial pattern is effective.
Unmanned Aerial Vehicle (UAV) plays an increasingly role in data collection from Wireless Sensor Networks (WSNs) with the advantages of its high mobility and flexibility. However, the energy ...limitation of UAV restricts its application for data collection tasks. To solve the problem, we install solar panel on UAV to acquire energy from sunlight. This paper studies Data Collection Maximization based on Solar-powered UAV (DCMS) problem in urban environment with lots of obstacles, where one UAV equipped with solar panel is used to collect data from WSN. The problem aims at optimizing the flight trajectory of UAV such that the amount of data collected from WSN is maximized. We prove that the problem is NP-hard. To solve the DCMS problem, we first propose three algorithms: Bypass Obstacles during Flight Algorithm (BOFA), Auxiliary Graph Flight Path (AGFP), Construct Flight Plan in data collection Area (CFPA). Their objectives are to bypass the obstacles, to obtain the flight path connecting all data collection areas in WSN, to optimize the flight trajectories of UAV in the data collection areas, respectively. Afterwards, we propose an approximation algorithm called DCMSA to solve the DCMS problem based on BOFA, AGFP, CFPA algorithms. Finally, the proposed algorithm is verified by extensive simulations.
The deployment of unmanned aerial vehicles (UAVs) has significantly improved the efficiency of data collection for wireless sensor networks (WSNs). The freshness of collected information from sensors ...can be measured by the age of information (AoI), which is an important factor to consider in data collection. For data collection during long-term mission, the energy limitation of UAVs may cause mission interruption, which makes supplementation of the UAVs’ energy more necessary. To this end, we introduce the mobile unmanned vehicle (MUV) to guarantee the UAVs’ energy supplementation. In this paper, we investigate the problem of multi-UAVs and single-MUV cooperative trajectory planning (MUSM-CTP) for data collection in WSNs with consideration for the AoI the collected data and the limited battery capacity of UAVs. The objective of this problem is to find cooperative flight trajectories for multiple UAVs and to determine the MUV’s travel plan to replace batteries for the UAVs, such that the average AoI of all collected data is minimized. We prove the NP-hardness of the problem and design the algorithm via three phases to solve this: determining candidate hover points based on the affinity propagation (AP) clustering method, constructing the flight trajectories of multiple UAVs based on the genetic algorithm (GA), and designing a travel plan for the MUV. The simulation results verify the effectiveness of the proposed algorithm in improving the freshness of the information collected from all of the sensors.
Unmanned Aerial Vehicle (UAV) can be used as wireless aerial mobile base station for collecting data from sensors in UAV-based Wireless Sensor Networks (WSNs), which is crucial for providing seamless ...services and improving the performance in the next generation wireless networks. However, since the UAV are powered by batteries with limited energy capacity, the UAV cannot complete data collection tasks of all sensors without energy replenishment when a large number of sensors are deployed over large monitoring areas. To overcome this problem, we study the Real-time Data Collection with Laser-charging UAV (RDCL) problem, where the UAV is utilized to collect data from a specified WSN and is recharged using Laser Beam Directors (LBDs). This problem aims to collect all sensory data from the WSN and transport it to the base station by optimizing the flight trajectory of UAV such that real-time data performance is ensured It has been proven that the RDCL problem is NP-hard. To address this, we initially focus on studying two sub-problems, the Trajectory Optimization of UAV for Data Collection (TODC) problem and the Charging Trajectory Optimization of UAV (CTO) problem, whose objectives are to find the optimal flight plans of UAV in the data collection areas and charging areas, respectively. Then we propose an approximation algorithm to solve each of them with the constant factor. Subsequently, we present an approximation algorithm that utilizes the solutions obtained from TODC and CTO problems to address the RDCL problem. Finally, the proposed algorithm is verified by extensive simulations.
Finding the minimum connected dominating set (MCDS) is a key problem in wireless sensor networks, which is crucial for efficient routing and broadcasting. However, the MCDS problem is NP-hard. In ...this paper, a new approximation algorithm with approximation ratio
H
(
Δ
)+3 in time
O
(
n
2
) is proposed to approach the MCDS problem. The key idea is to divide the sensors in CDS into
core
sensors and
supporting
sensors. The core sensors dominate the supporting sensors in CDS, while the supporting sensors dominate other sensors that are not in CDS. To minimize the number of both the cores and the supporters, a three-phased algorithm is proposed. (1) Finding the base-core sensors by constructing independent set (denoted as
S
1
), in which the sensors who have the largest
|
N
2
(
v
)
|
|
N
(
v
)
|
(number of two-hop neighbors over the number of one-hop neighbors) will be selected greedily into
S
1
; (2) Connecting all base-core sensors in
S
1
to form a connected subgraph, the sensors in the subgraph are called cores; (3) Adding the one-hop neighbors of the core sensors to the supporter set
S
2
. This guarantees a small number of sensors can be added into CDS, which is a novel scheme for MCDS construction. Extensive simulation results are shown to validate the performance of our algorithm.
Internet of Things (IoT) is rapidly spreading and reaching a multitude of different domains, since the fifth generation (5G) wireless technologies are the key enablers of many IoT applications. It is ...hence apparent that the broadcast nature of IoT devices makes data security unprecedentedly critical. Compared with traditional cryptography algorithms, which cannot cater for the features of IoT devices characterized by the severe limits in terms of energy, computation and storage capabilities, physical layer security (PLS) has been regarded as a promising solution to facilitate secure communications by exploiting the intrinsic randomness of the wireless medium. However, most of previous works assumed that all devices are static, and the impact of mobility on PLS deserves further investigation. In this paper, applying two types of random mobile models, i.e., the models of Random WayPoint (RWP) and Random Direction (RD), we study the impact of mobility on PLS in a scenario with three types of wireless devices (i.e., a destination, multiple interferers and an eavesdropper). Specifically, we establish an analytical framework for secrecy transmission capacity (STC), a fundamental metric in the study of PLS, under RWP and RD models. To the best of our knowledge, this is the first paper to derive STC and present the condition to achieve a positive STC with the consideration of mobility. We conclude that the RWP mobile destination can achieve a higher STC than that achievable in RD mobile and static scenarios, while RWP mobile eavesdropper is a challenging scenario to obtain a positive STC. Therefore, we propose an effective secrecy improvement strategy for the latter. Simulation validates the theoretical analyses.
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