Communication Links In Networks Research Articles

Enabling Space-Air integration: A Satellite-UAV networking authentication scheme

One of the goals of sixth-generation mobile networks (6G) is to achieve a larger network coverage area. Satellite networks enable global coverage and aerial nodes such as Unmanned Aerial Vehicle (UAV) can serve as a supplement to ground networks in remote environments. Therefore, 6G networks are gradually evolving towards Space-Air-Ground integrated networks. The combination of UAV networks and satellite networks is a research hotspot in the field of Space-Air integrated networks. However, the combination of UAV networks and satellite networks currently faces many challenges in terms of security. The characteristics of large propagation delay and unstable communication links in satellite networks make them vulnerable to various attacks, including eavesdropping, tampering, and impersonation. Meanwhile, existing research on UAV networks mainly focuses on UAV-Ground networking authentication mechanisms, which are not suitable for resource-constrained nodes in the Space-Air integration scenario. Therefore, based on elliptic curve public key cryptography and Chebyshev polynomial, we propose a secure networking authentication scheme for satellite nodes and UAV nodes in the Space-Air integration scenario. The security analysis indicates that our scheme possesses security attributes such as mutual authentication, key agreement, identity anonymity, unlinkability, perfect forward-backward security, and resistance against various protocol attacks, among other security properties. Performance analysis also indicates certain advantages of our scheme over existing schemes in terms of signaling, bandwidth, and computational overhead.

Zigbee Based Mobile Sensing for Wireless Sensor Networks

Wireless sensor networks, have drawn a lot of interest because of their adaptability and range of uses in different industries. WSNs face significant challenges when it comes to energy efficiency because sensor nodes are usually battery-powered and have limited resources. Several energy-efficient methods and protocols, such as duty cycling, data aggregation, and topology management, have been put forth to address this problem. Moreover, new potential for mobile wireless sensor networks are presented by the integration of WSNs with mobile and static devices, such as drones, tablets, and smartphones. In this study, we suggest utilizing Zigbee technology to establish a robust and flexible monitoring system for both stationary and mobile sensors. Numerous industries, including healthcare, smart agriculture, asset tracking, energy management, smart home automation, and industrial monitoring and control, have made extensive use of Zigbee. By leveraging Zigbee's capabilities, we hope to improve the protocol's performance while establishing dependable communication links between nodes, analyzing the communication range, and assessing the influence of environmental conditions. In this study, a system model for Zigbee deployment in mobile robots will be presented. It will address the basics of Zigbee, communication difficulties, networking with Zigbee, and simulations or real-world outcomes. We will learn about the strengths and weaknesses of Zigbee-based systems in terms of creating reliable communication links in mobile wireless sensor networks by looking at their architecture and functionality. The results of this study will help us comprehend Zigbee's potential to improve monitoring systems and make better decisions across a range of industries. The study's emphasis on mobile monitoring systems signifies a step forward in addressing the evolving needs of wireless sensor networks in dynamic environments.

Flocking control for Cucker–Smale model under denial‐of‐service attacks

AbstractIn this article, the issue of flocking control for Cucker–Smale model under denial‐of‐service (DoS) attacks is discussed. It is assumed that there is an active stage and an asleep stage for each period of the DoS. Malicious attacks partially or completely destroy the network communication links in the active stages, and replenish energy without any attacks in the dormant stages. By constructing the agents' position and velocity errors, the C–S model under DoS attacks is equivalently transformed into error systems. By applying the approach of products convergence for infinite sub‐stochastic matrices, a sufficient condition for producing the flocking behavior is obtained. An upper bound of relative errors for agents' final positions is established, which depends on initial states, the topology structure and the weight function. Finally, simulation experiments verify the effectiveness of the theoretical results.

Application of SDN Network Traffic Prediction Based on Speech Recognition in Educational Information Optimization Platform.

This paper constructs a SDN network traffic prediction model based on speech recognition and applies it to the educational information optimization platform. By analyzing the influencing factors of SDN network equipment, communication links, and network traffic, this paper constructs the initial index set of SDN network traffic situation. In the data plane of SDN, the queue management algorithm is used to control the flow. On this basis, an IRS mechanism is proposed based on the advantages of SDN centralized control and the difference of transmission performance requirements between large and small streams. For the transmission of large traffic, IRS adopts greedy routing and multipath routing based on the remaining bandwidth to make the traffic evenly distributed in the network, and IRS adds the scheduling strategy based on IP addressing to avoid packet disorder. Simulation results show that the effectiveness of this algorithm can reach 95.67% at the highest, and the MSE convergence is 0.0021 at the lowest. At the same time, this method completes the quantitative evaluation of SDN network traffic situation, effectively solves the problem that SDN traffic situation labels cannot be determined, and opens a new vision of global state observation for SDN network management. This research can provide some technical support for the educational information optimization platform.

Connection Quality Prediction and Nonlinear Control of Power Grid Communication Wireless Network

Learn about effective and uncontrolled gambling on wireless networks. Firstly, according to the control purpose, considering the reliability requirement of microgrid for network communication, the characteristics of wireless sensor network communication quality of service in microgrid, the influence of wireless connection reliability, and the mathematical standard of wireless communication are determined. Then, according to the estimation of the occurrence time of wireless communication link reliability, the reliability of wireless sensor network communication link in a smart grid is improved based on a fuzzy nonlinear control algorithm. Finally, the security and reliability of the control system described in this paper are measured by simulation. The experimental results show that the reliability of the wireless communication estimation time estimation algorithm and the power control algorithm based on fuzzy control can estimate the reliability, shortsightedness, and accuracy of good connections in real time. By adjusting the output power of the node, the connection quality and reliability can be controlled stably.

Endothelial signalling operates on a small‐world network to control vascular function

The endothelium is the innermost layer of all blood vessels and it controls a host of cardiovascular functions including vascular contractility, hemostasis, inflammation and the exchange of nutrients and waste products between circulating blood and tissue. The importance of the endothelium is clear since changes in the behaviour of this single layer of cells underlies almost all cardiovascular disease. To control each cardiovascular function, the endothelium processes and responds to endless streams of information that originate from multiple sources (i.e. blood cells, hormones, neighboring endothelial cells or underlying smooth muscle cells). To process so much information, the endothelium utilises distributed sensing on spatially‐distinct populations of cells that are primed to detect specific activators. These spatially‐distinct populations communicate across the endothelial network to coordinate vascular responses. The nature of the endothelial network, and how communication is achieved, is currently not understood. Here, by examining the Ca2+ responses in thousands of endothelial cells in intact arteries, we show how the endothelial network operates.Network organization controls overall system behaviour by determining the signal propagation speed, the robustness of the system to failures and attack, and the degree of synchronizability in the system. To determine the endothelial network structure, we used network (graph) theory. Graph theory has gained much attention due to its ability to quantify social, technological and biological systems, especially the connectivity and synchronisation of the nervous system. However, no studies have examined the network structure employed by the endothelium in the control of cardiovascular function. We analysed muscarinic‐ and histaminergic‐evoked Ca2+ activity from ~1000 endothelial cells from intact resistance arteries. Ca2+ signals were separately analysed in each of the 1000 individual endothelial cells using a custom‐written Python algorithm.Ca2+ activity in active cells was cross‐correlated and compared to a stochastic model to statistically quantify network connections. We show highly‐correlated Ca2+ activities occurred in multiple, separate, cell clusters for each agonist. The network communication links between the clusters exhibited unexpectedly short path‐lengths, i.e. the number of links between active cells was significantly shorter than expected when active cells were randomly positioned. The number of connections between active cells (degree distribution) followed a power‐law relationship, revealing a scale‐free network topology. The path‐length and degree distribution reveal an endothelial network with a ‘small‐world’ configuration. The small‐world configuration confers particularly dynamic endothelial properties including high signal‐propagation speed, stability and a high degree of synchronizability.These findings show that endothelial network design is effective for local and global efficiency in the interaction of cells, and for rapid and robust communication to efficiently control cardiovascular activity. The network organization explains how coordinated cell activity occurs across large regions of endothelium, despite sensing being distributed on spatially‐distinct populations of cells.

Small-world connectivity dictates collective endothelial cell signaling

Every blood vessel is lined by a single layer of highly specialized, yet adaptable and multifunctional endothelial cells. These cells, the endothelium, control vascular contractility, hemostasis, and inflammation and regulate the exchange of oxygen, nutrients, and waste products between circulating blood and tissue. To control each function, the endothelium processes endlessly arriving requests from multiple sources using separate clusters of cells specialized to detect specific stimuli. A well-developed but poorly understood communication system operates between cells to integrate multiple lines of information and coordinate endothelial responses. Here, the nature of the communication network has been addressed using single-cell Ca2+ imaging across thousands of endothelial cells in intact blood vessels. Cell activities were cross-correlated and compared to a stochastic model to determine network connections. Highly correlated Ca2+ activities occurred in scattered cell clusters, and network communication links between them exhibited unexpectedly short path lengths. The number of connections between cells (degree distribution) followed a power-law relationship revealing a scale-free network topology. The path length and degree distribution revealed an endothelial network with a “small-world” configuration. The small-world configuration confers particularly dynamic endothelial properties including high signal-propagation speed, stability, and a high degree of synchronizability. Local activation of small clusters of cells revealed that the short path lengths and rapid signal transmission were achieved by shortcuts via connecting extensions to nonlocal cells. These findings reveal that the endothelial network design is effective for local and global efficiency in the interaction of the cells and rapid and robust communication between endothelial cells in order to efficiently control cardiovascular activity.

Near Ground Pathloss Propagation Model Using Adaptive Neuro Fuzzy Inference System for Wireless Sensor Network Communication in Forest, Jungle and Open Dirt Road Environments.

In Wireless Sensor Networks which are deployed in remote and isolated tropical areas; such as forest; jungle; and open dirt road environments; wireless communications usually suffer heavily because of the environmental effects on vegetation; terrain; low antenna height; and distance. Therefore; to solve this problem; the Wireless Sensor Network communication links must be designed for their best performance using the suitable electromagnetic wave behavior model in a given environment. This study introduces and analyzes the behavior of the LoRa pathloss propagation model for signals that propagate at near ground or that have low transmitter and receiver antenna heights from the ground (less than 30 cm antenna height). Using RMSE and MAE statistical analysis tools; we validate the developed model results. The developed Fuzzy ANFIS model achieves the lowest RMSE score of 0.88 at 433 MHz and the lowest MAE score of 1.61 at 433 MHz for both open dirt road environments. The Optimized FITU-R Near Ground model achieved the lowest RMSE score of 4.08 at 868 MHz for the forest environment and lowest MAE score of 14.84 at 868 MHz for the open dirt road environment. The Okumura-Hata model achieved the lowest RMSE score of 6.32 at 868 MHz and the lowest MAE score of 26.12 at 868 MHz for both forest environments. Finally; the ITU-R Maximum Attenuation Free Space model achieved the lowest RMSE score of 9.58 at 868 MHz for the forest environment and the lowest MAE score of 38.48 at 868 MHz for the jungle environment. These values indicate that the proposed Fuzzy ANFIS pathloss model has the best performance in near ground propagation for all environments compared to other benchmark models.

Two-Dimensional Transmission of Four-Dimensional LDPC-Coded Modulation with Slepian Sequences for DSP-Free 40 km Metro Network Applications.

The growing data demands are pushing researchers to pay more attention to spectrally efficient modulation formats. The four-dimensional (4D) signal constellation modulation format has been investigated for metro networks’ applications to achieve better power efficiency. To cope with such modulation formats, the requirement of better digital signal processing (DSP) is also increasing rapidly. More complicated DSPs bring us extra costs; thus, the DSP-free coherent receivers are also investigated because of the high-power consumption of conventional DSP-based receivers, but the transceivers upgrading also results in extra costs. In this invited paper we implement a 4-dimentional modulation format based on Slepian sequences. We applied LDPC coding and experimentally investigated the BER performance in a two-dimensional (2D) 40 km fiber link transmission and demonstrate that being error free is possible without employing the complicated DSP. We compared our proposed modulation scheme with regular 16QAM and found it outperforms 16QAM with DSP over back-to-back transmission by 3.8 dB improvement in OSNR when BER = 10−5, while over 40 km metro network communication link our proposed 4D modulation signals are still successfully transmitted, and the LDPC-coding still works properly with such a new transmission strategy. On the other hand, DSP-free transmission of LDPC-coded 16-QAM exhibits an early error floor phenomenon.

Traffic flow modeling and feedback control for future Low-Altitude Air city Transport: An MFD-based approach

The imminent penetration of low-altitude passenger and delivery aircraft into the urban airspace will give rise to new urban air transport systems, which we call low-altitude air city transport (LAAT) systems. As the urban mobility revolution approaches, we must investigate (i) the collective behavior of LAAT aircraft in cities, and (ii) ways of controlling LAAT systems. Future LAAT systems exemplify a new class of modern large scale engineering systems — networked control systems. They are spatially distributed, consist of many interconnected elements with control loops through digital communication networks such that the system signals can be exchanged among all components through a common network. Therefore, a decentralized controller design in framework of the unilateral event-driven paradigm is considered. Inspired by controlled urban road networks, in this paper we first establish the concept of Macroscopic Fundamental Diagram (MFD) for LAAT systems and develop a collective and aggregate aircraft traffic flow model. Then, based on that, we design an adaptive boundary feedback flow control which is robust to various anomalies in technical devices and network communication links for LAAT systems.

Robust PIDD2 Controller Design for Perturbed Load Frequency Control of an Interconnected Time-Delayed Power Systems

The extensive practice of open communication links in the power system network introduces unavoidable communication time delays (CTDs). These CTDs demean the performance of the load frequency control (LFC) system, and in the worst condition, the LFC system becomes unstable. Thus, this brief proposes a robust proportional integral derivative double derivative (PIDD2) controller design for the perturbed LFC of the interconnected time-delayed power system. In this brief, the worst case plant selection approach is applied to find the worst case plant model using Kharitonov’s stability theorem of the interval system. The proposed PIDD2 controller is designed for the selected worst case plant model of the original interval plant. Furthermore, the tuning of PIDD2 controller is carried out using an internal model control (IMC) approach. The notable feature of the presented IMC scheme is that the IMC filter coefficient ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula> ) is determined in terms of maximum sensitivity ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$M_{s}$ </tex-math></inline-formula> ) and CTD, which shows the tradeoff between robustness and performance. The proposed control scheme is validated on a two-area time-delayed power system model. The effectiveness and robustness of the proposed IMC-PIDD2 control approach are assessed under parametric uncertainties in system parameters as well as CTD, nonlinearities, and step load demand disturbances. Besides, delay margin (DM) is also computed in the sense of Walton and Marshall stability theorems for the proposed control system. The efficacy of the proposed IMC-PIDD2 control scheme is verified by comparing it with the recently reported control schemes.

Number Theoretic Model of Concurrent Access in Hypercube Interconnection Network

Abstract: This paper proposes a mathematical logical model to use shared communication links in the hypercube interconnection network. To achieve our objective we have used the orthogonal property of binary coding used to label the processing nodes of the hypercube and applied binary coding based multiplexing technique and the XOR logic operation to separate the individual processing nodes data from the multiplexed signal. Keywords: Gray codes, Hypercube, 1’s complement logic, GIG codes, bipolar codes, orthogonal codes, Normalized inner product, Parallel computing System.

Circuit Type Multiple Beamforming Networks for Antenna Arrays in 5G and 6G Terrestrial and Non-Terrestrial Networks

To support the ever-increasing demand on connectivity and datarates, multiple beam antennas are identified as a critical technology for the fifth generation (5G), the sixth generation (6G) and more generally beyond 5G (B5G) wireless communication links in both terrestrial networks (TNs) and non-terrestrial networks (NTNs). To reduce the cost and power consumption, there is a marked industrial interest in adopting analogue multiple beam antenna array technology. A key sub-system in many of such antenna arrays is the circuit type multiple beamforming network (BFN). This has led to a significantly renewed interest in and new technological developments of Butler matrices, Blass matrices, and Nolen matrices as well as hybrid structures, mostly at millimeter-wave frequencies. To the best of the authors' knowledge, no comprehensive analysis and comparison of circuit type multiple BFNs have been properly reported with focus on 5 G and 6 G applications to date. In this paper, the principle of operation, design, and implementation of different circuit type multiple BFNs are discussed and compared. The suitability of these sub-systems for 5 G and B5G antenna arrays is reviewed. Major technology and research challenges are highlighted. It is expected that this review paper will facilitate further innovation and developments in this important field.

Characteristics of Rain-Induced Attenuation over Signal Links at Frequency Ranges of 25 and 38 GHz Observed in Beijing

Wireless communication has become a very important part of our lives, and it is well known that meteorological factors affect the quality of communication links, especially at higher frequencies because the physical dimensions of raindrops, hail stones, and snowflakes are on a similar wavelength to the propagating radio frequency. Millimeter-waves are an important technology for fifth-generation cellular networks which are currently being deployed all over the world. Since atmospheric effects are challenging in millimeter-wave transmissions, in this paper, we conducted line-of-sight field measurements at 25 GHz and 38 GHz. We monitored the received signal during rainfall events and compared the theoretical attenuation and the recorded rain-induced attenuation. We also derived the rain-induced attenuation (A) and rainfall rate (R) relation for stratiform and convective rain, respectively, using local rain drop size distribution (DSD) information at our measurement site collected during the period of two years. Furthermore, opportunistic sensing of atmospheric phenomena using microwave or millimeter-wave communication links in commercial cellular networks has recently attracted more attention in meteorological research worldwide. The accuracy of calculating rainfall rates from microwave links highly depends on the retrieval model and values of coefficients in the model, i.e., a and b of the A-R relation model. Here, the coefficients a and b are estimated based on local DSD measurement, and the performance of the improved A-R model is evaluated using propagated signal power based on measurement data. Compared to the (a, b) coefficients in the International Telecommunication Union Recommendation (ITU-R) P.838 document, the derived coefficients achieved an improved rainfall rate estimation.

Evaluation and Analysis for Maximum Lifespan of Wireless Sensor Networks by Energy-Efficient Design

Wireless Sensor Networks (WSNs) have used worldwide in the past few years and are now being used in health monitoring ,disaster management, defense, telecommunications, etc. Such networks are used in many industrial and consumer applications such as industrial process and environment monitoring, among others. A WSN network is a collection of specialized transducers known as sensor nodes with a communication link distributed randomly in any locations to monitor environmental parameters such as water level, and temperature. Each sensor node is equipped with a transducer, a signal processor, a power unit, and a transceiver. WSNs are now being widely used to monitor environmental parameters, including the amount of gas, water, temperature, humidity, oxygen level, dust, etc. The WSN for environment monitoring can be equivalently replaced by a multiple-input multiple-output (MIMO) relay network. Multi-hop relay networks have attracted significant research interest in recent years for their capability in increasing the coverage range. The network communication link from a source to a destination is implemented using the amplify-and-forward (AF) or decode-and-forward (DF) schemes. The AF relay receives information from the previous relay and simply amplifies the received signal and then forwards it to the next relay. On the other hand, the DF relay first decodes the received signal and then forwards it to the next relay in the second stage if it can perfectly decode the incoming signal. For analytical simplicity, in this thesis, we consider the AF relaying scheme and the results of this work can also be developed for the DF relay.

Robustness of Internet of Battlefield Things (IoBT): A Directed Network Perspective.

Through the combination of various intelligent devices and the Internet to form a large-scale network, the Internet of Things (IoT) realizes real-time information exchange and communication between devices. IoT technology is expected to play an essential role in improving the combat effectiveness and situation awareness ability of armies. The interconnection between combat equipment and other battlefield resources is referred to as the Internet of Battlefield Things (IoBT). Battlefield real-time data sharing and the cooperative decision-making among commanders are highly dependent on the connectivity between different combat units in the network. However, due to the wireless characteristics of communication, a large number of communication links are directly exposed in the complex battlefield environment, and various cyber or physical attacks threaten network connectivity. Therefore, the ability to maintain network connectivity under adversary attacks is a critical property for the IoBT. In this work, we propose a directed network model and connectivity measurement of the IoBT network. Then, we develop an optimal attack strategy optimization model to simulate the optimal attack behavior of the enemy. By comparing with the disintegration effect of some benchmark strategies, we verify the optimality of the model solution and find that the robustness of the IoBT network decreases rapidly with an increase of the unidirectional communication links in the network. The results show that the adversary will change the attack mode according to the parameter settings of attack resources and network communication link density. In order to enhance the network robustness, we need to adjust the defense strategy in time to deal with this change. Finally, we validated the model and theoretical analysis proposed in this paper through experiments on a real military network.

Efficient routing in UASN during the thermohaline environment condition to improve the propagation delay and throughput

In underwater acoustic sensor network (UASN), the challenging issues are bandwidth, higher propagation delay and heavy packet loss during data transmission. The issues can be solved through efficient routing algorithms. The existing UASN routing algorithms have larger latency in the network link and high rate of packet loss because of the salinity and temperature in the water at different depths. The salinity and temperature changes according to the depth and called as thermohaline circulation. In this paper, convex directional flooding optimisation (CDFO) algorithm improves the latency, throughput and lifetime of the nodes in the network under thermohaline condition and longshore drift from longshore current, which consist of transportation of sediments. The CDFO combines the convex optimisation and directional flooding-based routing algorithm, convex optimisation helps in identification of the hidden nodes in the network and strong communication links are established through polynomial time and semantic analysis and directional flooding algorithm reduces the packet loss and increases the network throughput. The routing protocol has implemented in ns2-AquaSim simulator and test bed for measurement of the performance metrics of the UASN.

Network Reconfiguration Algorithm (NRA) for scheduling communication-intensive graphs in heterogeneous computing environment

Distributed environments are widely used for computing complex applications modeled as task graphs. The computer network becomes more complex when the compute nodes are heterogeneous, however by choosing the appropriate network communication links for communication between a pair of compute tasks can enhance the computing efficiency(called network reconfiguration). One of the steps in heterogeneous network reconfiguration problem is mapping the application task graph edges on the network links. High Performance Computing (HPC) systems are usually heterogeneous, therefore mapping task graph edges on the communication links should consider the two factors: communication cost of task graph edges and the communication capability of network links. The system performance enhances if tasks are mapped on the compute nodes based on the computational costs of the tasks and the processing capability of compute nodes in addition to the edge scheduling on network links. In our earlier algorithm, Heterogeneous Edge and Task Scheduling (HETS) both edge and task mapping simultaneously improve the execution performance of task graphs. The proposed Network Reconfiguration Algorithm (NRA) minimizes the communication overhead and optimizes the schedule length with contention-aware model. NRA reduces an attribute Kirchhoff Index (KI) for optimal network reconfiguration providing minimum execution time. Both synthesized and task graphs of real applications are used for evaluation. The simulation results prove the efficiency of NRA in terms of average schedule length, schedule length ratio, speedup and system throughput. Comparisons with the baseline algorithms show that NRA provides 36% improved results specially for communication-intensive applications.

Maximising energy efficiency for direct communication links in wireless body area networks

Energy efficiency is a fundamental aspect for wireless body area networks (WBANs) due to the limited battery capacity and miniaturisation of sensor nodes. Prolonging the lifespan of a WBAN depends mostly on maximising the energy efficiency. WBAN systems operate under conflicting requirements of energy and spectrum efficiency. In this study, the two metrics of energy and spectrum efficiency for direct communication links for in-body and on-body sensor nodes are analysed. A general device-to-device communication model was adapted to WBAN. Optimal transmission power values to achieve maximum energy efficiency for in-body and on-body communication links are found. With reference to a maximum power level of 1.5 W compliant with the Federal Communications Commission for WBAN, it is also deduced that for on-body communication, decreasing maximum possible spectrum efficiency by 33% for medical devices operating in 400–450 and 950–956 MHz would improve energy efficiency by 75 times. Moreover, by decreasing spectrum efficiency by 38.3 and 48% leads to an increase in energy efficiency by 45.3 and 39.3 times in 2.4–2.5 and 3.1–10.6 GHz frequency bands, respectively. This trade-off is significant for medical applications having strict energy requirements.

A Link Quality Prediction Method for Wireless Sensor Networks Based on XGBoost

Link quality is an important factor for nodes selecting communication links in wireless sensor networks. Effective link quality prediction helps to select high quality links for communication, so as to improve stability of communication. We propose the improved fuzzy C-means clustering algorithm (SUBXBFCM) and use it to adaptively divide the link quality grades according to the packet reception rate. The Pearson correlation coefficient is employed to analyse the correlation between the hardware parameters and packet reception rate. The averages of the received signal strength indicator, link quality indicator and the signal to noise ratio are selected as the inputs of the link quality estimation model based on the XGBoost (XGB_LQE). The XGB_LQE is constructed to estimate the current link quality grade, which takes the classification advantages of XGBoost. Based on the estimated results of the XGB_LQE, the link quality prediction model (XGB_LQP) is constructed by using the XGBoost regression algorithm, which can predict the link quality grade at the next moment with historical link quality information. Experiment results in single-hop scenarios of square, laboratory, and grove show that the SUBXBFCM algorithm is effective at dividing the link quality grades compared with the normal division methods. Compared with link quality prediction methods based on the Support Vector Regression and 4C, XGB_LQP makes better predictions in single-hop wireless sensor networks.