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The authenticity and integrity of sensed data in the data collection stage is a very critical aspect for the smart city industrial environment. They impact the accuracy of data analysis and the objectivity of making decisions. However, how to identify attack behaviors from environmental interference and establish a secure route to transmit data for resource-constrained terminals are challenging problems. To address these problems, in this article, we propose a trust-based security system (TSS). In TSS, we first design a trust model using binomial distribution for calculating the node's trust value and a third-party recommendation scheme for improving the objectivity of trust value. Then, we propose a trust management scheme for preventing the on–off attack. After that, we design a secure routing protocol, which is used to balance the security, transmission performance, and energy efficiency. Finally, the analytical results of the TSS are evaluated with extensive simulation experiment.

In underground coal mine, the routing protocol in Wireless Sensor Network (WSN) based on fog computing can effectively achieve combination the monitoring task with the computing task, and provide the correct data forwarding path to meet the requirements of the aggregation and transmission of sensed information. However, the energy efficiency is still taken into account, especially, the unbalance of energy consumption. 5G is a technical system of high frequency and low frequency mixing, with characteristics of large capacity, low energy consumption and low cost. With the formal freeze on 5G NSA standards, 5G networks are one step closer to our lives. In this paper, a centralized non-uniform clustering routing protocol C-EEUC based on the residual energy and communication cost. The C-EEUC protocol considers all nodes as candidate cluster heads in the clustering stage and defines a weight matrix P. The value of the matrix elements takes into account the residual energy of nodes and the cost of communication between nodes and cluster heads, selected as the basis for the cluster head. When selecting a cluster head, each time a node with the largest weight is selected from a set of candidate cluster heads, other candidate cluster heads within the competition range abandon competition, and then updates the candidate cluster head set. Experimental results show that the protocol optimized in this paper can effectively extend the network life cycle.

Motion tracking is attractive in what concerns a smart city environment, where citizens have to interact with Internet of Things (IoT) infrastructures spread all around one particular city. Motion tracking is important for smart services and location-based services in smart cities, since it provides natural ways for users to interact with the IoT infrastructures, such as the ability to recognize of a wide range of hand motion in real-time. Compared with dedicated hardware devices, ubiquitous devices with reliable speakers and microphones can be developed to achieve cheap acoustic-based motion tracking, which is appropriate for low-power and low-cost IoT applications. However, for complex urban environments, it is very difficult for acoustic-based methods to achieve accurate motion tracking due to multipath fading and limited sampling rate at mobile devices. In this paper, a new parameter called multipath dispersion vector (MDV) is proposed to estimate and mitigate the impact of multipath fading on received signals using extreme learning machine. Based on MDV, a robust acoustic motion tracking (RAMTEL) method is proposed to calculate the moving distance based on the phase change of acoustic signals, and track the corresponding motion in 2-D plane by using multiple speakers. The method is then proposed and implemented on standard Android smartphones. Experiment results show, without any specialized hardware, RAMTEL can achieve an impressive millimeter-level accuracy for localization and motion tracking applications in multipath fading environments. Specifically, the measurement errors are less than 2 and 4 mm in 1-D and 2-D scenarios, respectively.

Based on fog computer, an industrial wireless sensor network (F-IWSN) is a novel wireless sensor network in the industry. It not only can more efficiently reduce information transmission latency, but also can more beneficially achieve the real-time control and the rapid resource scheduling. However, similar to other distributed networks, it also faces enormous security challenges, especially those internal attacks. The differences from those traditional security schemes are that, one is the trade-off between security, transmission performance and energy consumption to meet the requirements of information convergence and control, the other constructs a multi-dimensional selective forwarding scheme to achieve the real time transmission. In this paper, we propose a Gaussian distribution-based comprehensive trust management system (GDTMS) for F-IWSN. Furthermore, in its trust decision, the grey decision making is introduced to achieve the trade-off between security, transmission performance and energy consumption. The proposed trade-off can effectively select the secure and robust relay node, namely, a trust management-based secure routing scheme. In addition, the proposed schemes are also applicable to defending against bad mouthing attacks. Simulation results show that, the comprehensive performance of GDTMS is better than other similar algorithms. It can effectively prevent the appearance of network holes, and balance the network load, promote the survivability of the network.

Wireless networks attract increasing interests from a variety of industry communities. However, the wide applications of wireless industrial networks are still challenged by unreliable services due to severe multipath fading effects. Such effects are not only caused by massive metal surfaces but also moving operators and logistical vehicles, which will lead to temporal fading effects. A three-layer impulse response framework is proposed to characterize such effects, in which both the specular and scattered components vary with the spacial movement of nearby objects. In this context, a received signal strength indicator will be a noisy estimation only on the specular power and fail to describe the link quality accurately without the aid of scattered power. Consequently, an augmented Kalman-filter-based link quality estimator has been designed to track both the specular and scattered power in the distribution parameter space with constant noise covariance matrices. Experiments from industrial sites show significantly increased accuracy.

As an innovative networking paradigm in the Internet of Things, information-centric networking (ICN) has improved security than the traditional IP networks. However, it still faces a large number of security threats, especially those threats from internal attacks. The trust management technology is an effective approach for defending against internal attacks. In this paper, our contributions lie in our investigating the requirements of cybersecurity in ICN and analyzing the typical attack behaviors and defense schemes. Then, we propose a fast and efficient trust management scheme (FETMS) for defending against the on-off attack, which is an intelligent internal attack. The simulation results show that FETMS can efficiently detect and remove the malicious node in a short period of time; meanwhile, it can achieve lower latency and add its mobility.

Rician distribution has been widely utilized to describe wireless fading channel. In the non-stationary temporal fading channel like industrial scenarios, both the specular and scattered components of the multi-path fading channel will be time varying. As a result, the online estimation of Rician parameters is necessary to provide stable wireless service. The traditional estimation approaches of Rician parameters are designed for channel measurement usage and therefore have to work in the data-aided mode for online estimation with modulated I/Q samples. To solve this problem, some non-data-aided algorithms have been proposed in recent years, but only valid in specific scenarios. In this paper, we formulate the estimation of Rician parameters from modulated I/Q samples as a two-dimensional Gaussian mixture model to provide a general non-data-aided Rician parameter estimation method. By involving a priori information of modulation scheme and the motivation of optimized gradient searching, the independent parameters in the maximum likelihood estimation can be significantly decreased to three, which leads to fast convergence of the modified expectation-maximization algorithm with high accuracy. The combination of these modifications has been finally formulated as a Rician mixture model. The numerical results and field measurements illustrate the feasibility of this methodology.

Web of things (WoT) are inclined to suffer from internal attacks, which are from compromised nodes. Due to resource-constraint of WoT, the traditional security methods cannot be deployed. One of the most appropriate protection mechanisms to resist internal attacks is the trust management system. For the sake of evaluate the performance of WoT reasonably and appropriately, we improve the Beta-based reputation system, and propose a Poisson Distribution-based trust model (PDTM) in this paper. In view of evaluating a sensor node (or terminal) behaviors, its reputation and trust are represented by the Poisson distribution. PDTM is used to look for reliable nodes to transmit data and weaken malicious attacks within WoTs. The simulation results indicate that the PDTM can resist internal attack effectively, in order to strengthen the network security.

For mMTC and uRLLC coexistence system, traditional random access techniques cannot meet the different requirements of the mixed traffic. To tackle this issue, in this paper, a novel priority based distributed queuing random access (PDQRA) mechanism is proposed for mMTC and uRLLC coexistence system. To meet the access delay requirement of uRLLC devices (UTDs), the preambles are divided into two groups. The first group is completely selected by partial UTDs, while the second group is shared by the mMTC devices (MTDs) and the rest of the UTDs. To evaluate the performance of the proposed mechanism, the access delay of devices is mathematically analyzed. Moreover, an optimization problem is formulated via jointly optimizing the preamble division ratio and selection probability of the preamble groups to minimize the access delay of MTDs while guaranteeing the delay requirement of the UTDs. Then, a low-complexity algorithm developed based on particle swarm optimization (PSO) is proposed to obtain the suboptimal solutions. Finally, numerical simulations are presented to verify the effectiveness of the proposed mechanism.

For hierarchical wireless sensor network (WSN), the clustered routing protocol can effectively deal with large-scale application requirements, thereby, how to efficiently elect the secure cluster heads becomes very critical. Unfortunately, many current studies only focus on improving security while neglecting energy efficiency and transmission performance. In this paper, a lightweight trust management scheme (LTMS) is proposed based on binomial distribution for defending against the internal attacks. Simultaneously, distance domain, energy domain, security domain and environment domain are considered and introduced to propose a multidimensional secure clustered routing (MSCR) scheme by using dynamic dimension weight in hierarchical WSNs. The simulation results show that LTMS can effectively prevent a malicious node from being elected as a cluster head, and MSCR can achieve a balance between security, transmission performance and energy efficiency under the requirements of environmental applications.

As an efficient approach, the trust policy is implemented to defend against insider attacks in complex networks. However, the imperfection of trust relationships directly hinders the effort to quantitatively calculate trust value, especially in choosing a cooperative partner. Fortunately, the game theory is gradually concerned with addressing the above issue to further enhance security. In this paper, the game theory and the trust policy are reviewed briefly. Then, the research roadmap on game-based trust in complex networks is discussed and analysed deeply. Furthermore, some research directions in the near future are given. It is worth mentioning that our contributions not only describe the evolution of the game-based trust clearly but also suggest the trust mechanism based on the bounded rational game more suitable to uncertain information.

As a key component of the information sensing and aggregating for big data, cloud computing, and Internet of Things (IoT), the information security in wireless sensor network (WSN) is critical. Due to constrained resources of sensor node, WSN is becoming a vulnerable target to many security attacks. Compared to external attacks, it is more difficult to defend against internal attacks. The former can be defended by using encryption and authentication schemes. However, this is invalid for the latter, which can obtain all keys of the network. The studies have proved that the trust management technology is one of effective approaches for detecting and defending against internal attacks. Hence, it is necessary to investigate and review the attack and defense with trust management. In this paper, the state-of-the-art trust management schemes are deeply investigated for WSN. Moreover, their advantages and disadvantages are symmetrically compared and analyzed in defending against internal attacks. The future directions of trust management are further provided. Finally, the conclusions and prospects are given.

In order to address the challenges in MIMO channel measurement and modeling for 5G communication scenarios, a CDM-based parallel channel sounder is developed and evaluated in this article. Compared to traditional TDM-based channel sounders, our parallel channel sounder supports eight-by-eight (8 x 8) MIMO communications, 200 MHz RF bandwidth, 5 ns multipath time resolution, 36 dB dynamic range, and 2 kHz maximum Doppler shift at a speed of 350 km/h. To achieve these performance targets, a series of sophisticated technical solutions are proposed and analyzed to realize 32 ps synchronization accuracy, 51.36 Gb/s parallel data streaming, and high-precision calibration across multiple channels. Key functions and performance metrics are evaluated and verified in a microwave chamber. Real measurement results in a complex campus environment show that our CDM-based parallel channel sounder can capture more detailed channel characteristics, and therefore offer accurate PDPs and RMS delay spreads at both LoS and NLoS positions under MIMO communication scenarios.

Vehicular ad hoc networks, wireless sensor networks, Internet of Things, and mobile device-to-device communications can be modeled as different homogeneous fog networks, wherein similar terminals/things/devices/nodes are sharing their computation, communication, and storage resources in the neighborhood for achieving better system performance through effective collaborations. It is very desirable, but quite challenging, to simultaneously reduce service delay and energy consumption in such networks for delay-sensitive and energy-constraint applications, e.g., virtual reality and online 3-D gaming on mobile devices. In this paper, a cross-layer analytical framework is developed to formulate and study the balance between service delay and energy consumption. An effective control parameter ${V}$ is derived to characterize their tradeoff relationship during dynamic task scheduling processes in fog networks. Combining this analysis with Lyapunov optimization techniques, a novel delay energy balanced tasking scheduling (DEBTS) algorithm is proposed to minimize the overall energy consumption while reducing average service delay and delay jitter. It is proved that DEBTS can achieve the theoretical [ ${O(1/V), O(V)}$ ] tradeoff between these two performance metrics. Further, extensive simulation results show that DEBTS can offer much better delay-energy performance in task scheduling challenges. Specifically, for a typical ${V}$ value of ${4 \times 10^{4}}$ , DEBTS can save 26% and 29% more energy, and at the same time, reduce average service delay by 29% and 32%, than traditional random scheduling and least busy scheduling algorithms, respectively.

The Industrial Internet of Things is cited as the latest means for making manufacturing more flexible, cost effective, and responsive to changes in customer demands. In this paper, we present a mobile cloud based scheduling strategy for the industrial Internet of Things. Several computing paradigms, such as mobile cloud computing, fog computing, and edge computing can be integrated to the industrial Internet of Things, which allow to offload tasks to the cloud for execution. We model the task scheduling problem as an energy consumption optimization problem, while taking into account task dependency, data transmission, and some constraint conditions, such as response time deadline and cost, and further solve it by genetic algorithms. A series of simulation experiments are conducted to evaluate the performance of the algorithm and the results have shown that our proposal is more efficient than the baseline approach.

Wireless local area network (WLAN) is an indivisible part of the next generation wireless system. In this paper, an open Wi-Fi platform is designed and developed with special consideration of real-time signal processing. Such system can help accelerate research and development of future wireless network, especially in the case of cellular/ Wi-Fi co-existing networks. This platform is based on the Intel general-purpose processor and the universal software radio peripheral (USRP) radio front end. The design including the physical layer implementations is purely software and is optimized for real-time signal processing on the general purpose processor. In the lab experiment, this platform supports baseband rate up to 700 Mbps with 2 transmitters in 80 MHz bandwidth. A cellular-Wi-Fi signaling interface between the Wi-Fi access point (AP) and the 5G core network is also developed and validated as an example for wireless resource allocation.

High-dense titanium alloys with a 3D network core–shell structure of different N contents were synthesized successfully by means of spark plasma sintering of the nitrided titanium particles. The microstructure investigation shows that the core–shell structure with an obvious boundary within a grain is constructed in light of different solid solution levels of nitrogen in grain boundary and grain inner. The mechanical behaviors have been experimentally assessed through compressive testing. The compacts exhibit a much enhanced strength while retaining a reasonable ductility, which can be attributed to their novel core–shell structure. With an increasing N content as well as shell thickness, the strength increases and the ductility decreases, in accordance with the morphology observations.

As a three-dimensional distributed network, the UAV network is very critical for communication security. The current security approaches for UAV are mainly traditional secure schemes, such as encryption, authentication, and etc. Unfortunately, these secure schemes could not defend against the internal attacks. Simultaneously, as an effective technology to defend against the internal attacks, this is, a trust management technology, has security vulnerabilities in the third party recommendation. Nevertheless, there is also the risk of cyber holes in UAV network. In this paper, we propose an indirect observation node selection scheme (IONSS) to solve these issues. For all current indirect observation nodes, their energy levels are sorted to select the appropriate nodes. The Grey-decision calculation is performed and sorted with the attribute of these nodes, and the previous nodes are preferentially selected as the indirect observation nodes. The simulation results show that the balance between security and energy efficiency.

The widespread application of networks is providing a better platform for the development of society and technology. With the expansion of the scope of network applications, many issues need to be solved. Among them, the maximization of utility and the improvement of security have attracted much attention. Many existing attacks mean the network faces security challenges. The concept of trust should be considered to address these security issues. Meanwhile, the utility of the network, including efficiency, profit, welfare, etc., are concerns that should be maximized. Over the past decade, the concepts of game and trust have been introduced to various types of networks. However, there is a lack of research effort on several key points in distributed networks, which are critical to the information transmission of distributed networks, such as expelling malicious nodes quickly and accurately and finding equilibrium between energy assumption and high transmission rate. The purpose of this paper is to give a holistic overview of existing research on trust and game theory in networks. We analyzed that network utility can be maximized in terms of effectiveness, profits, and security. Moreover, a possible research agenda is proposed to promote the application and development of game theory and trust for improving security and maximizing utility.

The massive multi-input multi-output (MIMO) antennas and the millimeter wave communication technologies have been widely known as two key technologies for the fifth generation (5G) wireless communication systems [1, 2, 3, 4, 5, 6]. Compared with conventional MIMO antenna technology, massive MIMO can improve more than 10 times spectrum efficiency in wireless communication systems [7]. Moreover, the beamforming gain based on the massive MIMO antenna technology helps to overcome the path loss fading in millimeter wave channels.

In coal mine, the routing protocol in Wireless Sensor Network (WSN) based on fog computing can effectively achieve combination the monitoring task with the computing task, and provide the correct data forwarding path to meet the requirements of the aggregation and transmission of sensed information. However, the energy efficiency is still taken into account, especially, the unbalance of energy consumption. 5G is a technical system of high frequency and low frequency mixing, with characteristics of large capacity, low energy consumption and low cost. With the formal freeze on 5G NSA standards, 5G networks are one step closer to our lives. In this paper, a centralized non-uniform clustering routing protocol based on the residual energy and communication cost. The protocol considers all nodes as candidate cluster heads in the clustering stage and defines a weight matrix P. The value of the matrix elements takes into account the residual energy of nodes and the cost of communication between nodes and cluster heads, selected as the basis for the cluster head. When selecting a cluster head, each time a node with the largest weight is selected from a set of candidate cluster heads, other candidate cluster heads within the competition range abandon competition, and then updates the candidate cluster head set. Experimental results show that the protocol optimized in this paper can effectively extend the network life cycle.

As the rapid development of the information and communication technology (ICT), the energy consumption problem of ICT industry, which causes about 2% of worldwide CO2 emissions yearly and burdens the electrical bill of network operators [1], has drawn universal attention.

The time-frequency spatial distribution of multi-network radiant energy \( {\mathbf{e}}(t,f,{\mathbf{s}}) \) depends on the topology of the network, the location of the base station, the transmit power of the antenna, and the physical environment of the wireless communication.

The deployment of a large number of small cells poses new challenges to energy efficiency, which has often been ignored in fifth generation (5G) cellular networks. While massive multiple-input multiple outputs (MIMO) will reduce the transmission power at the expense of higher computational cost, the question remains as to which computation or transmission power is more important in the energy efficiency of 5G small cell networks. Thus, the main objective in this chapter is to investigate the computation power based on the Landauer principle. Simulation results reveal that more than 50% of the energy is consumed by the computation power at 5G small cell base stations (BSs). Moreover, the computation power of 5G small cell BS can approach 800 W when the massive MIMO (e.g., 128 antennas) is deployed to transmit high volume traffic. This clearly indicates that computation power optimization can play a major role in the energy efficiency of small cell networks.

Ultra-dense deployment of small cell base stations (BSs), relay nodes, and distributed antennas is considered as a de facto solution for realizing the significant performance improvements needed to accommodate the overwhelming future mobile traffic demand (Ge et al. in IEEE Wirel Commun 23(1):72–79 (2016), [1]). Traditional network expansion techniques like cell splitting are often utilized by telecom operators to achieve the expected throughput, which is less efficient and proven not to keep up with the pace of traffic proliferation in the near future. Heterogeneous networks (HetNets) then become a promising and attractive network architecture to alleviate the problem. “HetNets” is a broad term that refers to the coexistence of different networks (e.g., traditional macrocells and small cell networks like femtocells and picocells), each of them constituting a network tier.

In recent years, with the rapid development of the wireless communication industry, wireless communication networks are becoming more effective in the direction of network diversification, high bandwidth, high frequency band, ubiquity, synergy, overlap and application integration and more flexible to meet the needs of people’s different communication services, a variety of mature wireless access technologies are being rapidly deployed in various scenarios.

Although NB-IoT’s standardization gives us a future direction, we have to face some issues of existing networks converged, especially, the wireless sensor net-work (WSN) and cellular networks (CN) converged. On the other hand, the increase in number of sensor nodes and in the mobile devices is forcing the backhaul network architecture to undergo radical transformation. To meet the requirements of low latency and high quality of service (QoS), we put forward a novel converged network architecture. Meanwhile, we give three application scenarios. The analysis results show this architecture could facility the network design.

With the seamless coverage of wireless cellular networks in modern society, it is interesting to consider the shape of wireless cellular coverage. Is the shape a regular hexagon, an irregular polygon, or another complex geometrical shape? Based on fractal theory, the statistical characteristic of the wireless cellular coverage boundary is determined by the measured wireless cellular data collected from Shanghai, China. The measured results indicate that the wireless cellular coverage boundary presents an extremely irregular geometrical shape, which is also called a statistical fractal shape. Moreover, the statistical fractal characteristics of the wireless cellular coverage boundary have been validated by values of the Hurst parameter estimated in angular scales. The statistical fractal characteristics of the wireless cellular coverage boundary can be used to evaluate and design the handoff scheme of mobile user terminals in wireless cellular networks., 16 pages, 4 figures

In this paper, we first challenge the accuracy of the so-called innovative assumption that is widely adopted in delay performance analysis of network-coding-based epidemic routing (NCER) in delay-tolerant networks (DTNs). We demonstrate that this optimistic assumption severely underestimates data delivery delay and solves this problem successfully by introducing an extra encounter factor $\delta$ . Based on this, we propose a coloring process (CP)-based analytical model to evaluate the delay performance of NCER. Numerical results show that our CP-based method outperforms traditional ordinary differential equation (ODE)-based methods on estimating the delay performance under different network sizes. Furthermore, to mitigate potential competition among multiple data streams from different nodes, we propose a feedback-based recovery protocol (FRP) that takes advantage of finite buffer space and significantly reduces the number of ineffective transmissions between nodes. As a result, FRP can achieve much better delay performance compared with existing protocols in prior work.

To satisfy the requirement of high wireless transmission rate from user terminals, the multi-cell cooperative communication is an important solution for cellular networks. The selection of cooperative cells is usually depended on every wireless single cellular coverage boundary in cellular networks. In this paper, we analyze the characteristics of wireless single cellular coverage boundary based on real measured data. Moreover, the alpha-stable processes are first proposed to model the wireless single cellular coverage boundary. Simulation results indicate that probability density functions of wireless single cellular coverage boundary can be fitted by alpha-stable processes with 95% confidence interval based on the real measured data. This result provides a basis for cooperative communications considering the anisotropic fading characteristic of wireless signal propagation in wireless single cellular coverage region.

To overcome the inter-carrier interference (ICI) of orthogonal frequency division multiplexing (OFDM) systems subject to unknown carrier frequency offset (CFO) and multipath, this paper develops a blind adaptive interference suppression scheme based on independent component analysis (ICA). Taking into account statistical independence of subcarriers' signals of OFDM, the signal recovery mechanism is investigated to achieve the goal of blind equalization. The received OFDM signals can be considered as the mixed observation signals. The effect of CFO and multipath corresponds to the mixing matrix in the problem of blind source separation (BSS) framework. In this paper, the ICA-based OFDM system model is built, and the proposed ICA-based detector is exploited to extract source signals from the observation of a received mixture based on the assumption of statistical independence between the sources. The blind separation technique can increase spectral efficiency and provide robustness performance against erroneous parameter estimation problem. Theoretical analysis and simulation results show that compared with the conventional pilot-based scheme, the improved performance of OFDM systems is obtained by the proposed ICA-based detection technique.

Emotion recognition is helpful for human to enhance self-awareness and respond appropriately toward the happenings around them. Due to the complexity and diversity of emotions, EEG-based emotion recognition is still a challenging task in pattern recognition. In order to recognize diverse emotions, we propose a novel firefly integrated optimization algorithm (FIOA) in this paper. It can simultaneously accomplish multiple tasks, i.e. the optimal feature selection, parameter setting and classifier selection according to different EEG-based emotion datasets. The FIOA utilizes a ranking probability objection function to guarantee the high accuracy recognition with less features. Moreover, the hybrid encoding expression and the dual updating strategy are developed in the FIOA so as to realize the optimal selection of feature subset and classifier without stagnating in the local optimum. In addition to the public DEAP datasets, we also conducted an EEG-based music emotion experiment involving 20 subjects for the validation of the proposed FIOA. After filtering and segmentation, three categories of features were extracted from every EEG signal. Then FIOA was applied to every subject dataset for two pattern recognition of emotions. The results show that the FIOA can automatically find the optimal features, parameter and classifier for different emotion datasets, which greatly reduces the artificial selection workload. Furthermore, comparing with the binary particle swarm optimization (PSObinary) and the binary firefly (FAbinary), the FIOA can achieve the higher accuracy with less features in the emotion recognition.

The hierarchical routing protocol in the wireless sensor network (WSN) is widely applied because of its good network stability and effective communication capability. Its cluster structure and the integration process of the data have a satisfactory performance in energy consumption and data transmission. To guide the design of hierarchical routing protocol, in this paper, we review the current research on these protocols, some typical technical characteristics such as the cluster head selection, clustering, and data routing are analysed, and a suggestion on the direction of the hierarchical routing protocol research is given. The work of this paper will be beneficial to the research, design, and optimisation of the hierarchical routing protocol.

Dampers of vehicle suspension systems usually show unsymmetrical nonlinear hysteresis characteristics, which affects the control accuracy of suspension system. Automatic recognition hysteresis features of unknown vehicle dampers can reduce the burden for developing efficient control strategies for suspension systems. According to the Duhem hysteresis model, a model-based unsupervised classification approach is proposed in this paper for recognizing hysteresis features of vehicle dampers. Through constructing Duhem models for different force-displacement hysteresis loops of the same sample, significant hysteresis features are extracted for multivariate time series of vehicle dampers. In terms of model parameters of samples, the clustering method is used to group dampers into different classes. Clustering results of 700 samples show that model-based features can efficiently describe the hysteresis features of vehicle dampers. K-means and Fuzzy-C Mean (FCM) are more appropriate for clustering the damper model feature data than hierarchical agglomerative clustering (HAC).

The wide deployment of wireless industrial networks still faces the challenge of unreliable service due to severe multipath fading in industrial environments. Such fading effects are not only caused by the massive metal surfaces existing within the industrial environment but also, more significantly, the moving objects including operators and logistical vehicles. As a result, the mature analytical framework of mobile fading channel may not be appropriate for the wireless industrial networks, especially the majority fixed wireless links. In this paper, we propose a qualitative analysis framework to characterize the temporal fading effects of the fixed wireless links in industrial environments, which reveals the essential reason of correlated temporal variation of both the specular and scattered power. Extensive measurements with both the envelop distribution and impulse response from field experiments validate the proposed qualitative framework, which will be applicable to simulate the industrial multipath fading characteristics and to derive accurate link quality metrics to support reliable wireless network service in various industrial applications.

A Gaussian trusted scheme with adaptive factors defending against On-off attack for sensor networks (GTS) was proposed, with the tests between Gaussian probability distribution and Beta reputation distribution. Meanwhile, the adaptive control factor and the time slot are introduced to verify and restrict the compromised modes, which refer to those nodes' reputation value changes are caused by On-off attacks. Through some preliminary simulation results, this model is more stable to describe reputation against other distributions and easier to display the trust directly and sensitively, and it also has the powerful ability to prevent from On-off attacks.

Fog computing extends cloud computing paradigms to the edge of the network, enabling a new generation of applications and services. This paper mainly elaborates the related background and characteristics of fog computing, discusses the concept and hierarchical structure of fog computing services, compares the advantages of cloud computing and fog computing, analyzes the existing techniques and applications of fog computing, and analyzes possible security issues in fog computing and solutions to some of the security issues.

Wireless sensor network (WSN) is more and more widely used in the mine because of its flexible configuration and strong adaptability. However, due to the special environment of the mine, WSN faces with a series of challenges. Through the investigation, it is found that the routing protocols used in the mine are mainly hierarchical routing. This paper firstly discusses the main idea of hierarchical routing protocol, and summarizes the main current issues; Then, regarding present problems, such as long data transmission latency, unbalanced energy consumption and short network life cycle, I discuss the advantages and disadvantages of different optimization algorithms for the hierarchical routing protocol in clustering mechanisms from the view of optimizing cluster head election method and controlling cluster range; Finally, I summarize the problems of wireless sensor network routing protocol used in mine and point out the future directions.

The hierarchical routing protocol in the wireless sensor network (WSN) is widely applied because of its good network stability and effective communication capability. As the earliest hierarchical routing protocol, Low-Energy Adaptive Clustering Hierarchy(LEACH) had low energy efficiency without considering the state of nodes. In this paper, we propose an energy efficient LEACH-based protocol to improve LEACH. The state of the cluster heads in the previous rounds, as well as residual energy and alive nodes density, are used as indicators to measure the current round cluster head selection. The modified protocol fixes the issue that the number of cluster heads dropped rapidly with dead nodes increase. The simulation results show that the proposed protocol can prolong the network lifetime of WSN effectively, and reduce the energy consumption with the balancing energy distribution.