Distribution of Link Distances in a Wireless Network

The probability distribution is found for the link distance between two randomly positioned mobile radios in a wireless network for two representative deployment scenarios: (1) the mobile locations are uniformly distributed over a rectangular area and (2) the x and y coordinates of the mobile locations have Gaussian distributions. It is shown that the shapes of the link distance distributions for these scenarios are very similar when the width of the rectangular area in the first scenario is taken to be about three times the standard deviation of the location distribution in the second scenario. Thus the choice of mobile location distribution is not critical, but can be selected for the convenience of other aspects of the analysis or simulation of the mobile system.     

Communication Reliability Analysis of Wireless Sensor Networks Using Phased‐Mission Model

Communication reliability of wireless sensor networks (WSNs) is essential to ensure the correct and reliable operation of the network. Two distinct communication paradigms exist in WSNs: infrastructure communication and application communication, and a practical communication task typically involves both types of communications. To the best of our knowledge, no reliability studies on WSNs have been dedicated to combining the two communication paradigms. In this paper, we advance the state‐of‐the‐art by proposing a phased‐mission framework to analyze the communication reliability of WSNs considering both infrastructure communication and application communication, as well as K‐coverage requirements. WSNs containing two types of sensor nodes (energy harvesting sensor nodes and battery‐powered sensor nodes) are modeled. Corresponding to the two types of sensor nodes, two different link reliability models are first presented. Binary decision diagram (BDD) based algorithms are then developed for the phased‐mission communication reliability analysis of WSNs. Case studies are given to illustrate the application of the proposed algorithms. Copyright © 2016 John Wiley & Sons, Ltd.     

Quantum Artificial Intelligence Based Node Localization Technique for Wireless Networks

Artificial intelligence (AI) techniques have received significant attention among research communities in the field of networking, image processing, natural language processing, robotics, etc. At the same time, a major problem in wireless sensor networks (WSN) is node localization, which aims to identify the exact position of the sensor nodes (SN) using the known position of several anchor nodes. WSN comprises a massive number of SNs and records the position of the nodes, which becomes a tedious process. Besides, the SNs might be subjected to node mobility and the position alters with time. So, a precise node localization (NL) manner is required for determining the location of the SNs. In this view, this paper presents a new quantum bird migration optimizer-based NL (QBMA-NL) technique for WSN. The goal of the QBMA-NL approach is for determining the position of unknown nodes in the network by the use of anchor nodes. The QBMA-NL technique is mainly based on the mating behavior of bird species at the time of mating season. In addition, an objective function is derived based on the received signal strength indicator (RSSI) and Euclidean distance from the known to unknown SNs. For demonstrating the improved performance of the QBMA-NL technique, a wide range of simulations take place and the results reported the supreme performance over the recent NL techniques.     

A Joint Algorithm for Resource Allocation in D2D 5G Wireless Networks

With the rapid development of Internet technology, users have an increasing demand for data. The continuous popularization of traffic-intensive applications such as high-definition video, 3D visualization, and cloud computing has promoted the rapid evolution of the communications industry. In order to cope with the huge traffic demand of today’s users, 5G networks must be fast, flexible, reliable and sustainable. Based on these research backgrounds, the academic community has proposed D2D communication. The main feature of D2D communication is that it enables direct communication between devices, thereby effectively improve resource utilization and reduce the dependence on base stations, so it can effectively improve the throughput of multimedia data. One of the most considerable factor which affects the performance of D2D communication is the co-channel interference which results due to the multiplexing of multiple D2D user using the same channel resource of the cellular user. To solve this problem, this paper proposes a joint algorithm time scheduling and power control. The main idea is to effectively maximize the number of allocated resources in each scheduling period with satisfied quality of service requirements. The constraint problem is decomposed into time scheduling and power control subproblems. The power control subproblem has the characteristics of mixed-integer linear programming of NP-hard. Therefore, we proposed a gradual power control method. The time scheduling subproblem belongs to the NP-hard problem having convex-cordinality, therefore, we proposed a heuristic scheme to optimize resource allocation. Simulation results show that the proposed algorithm effectively improved the resource allocation and overcome the co-channel interference as compared with existing algorithms.     

Deployment of Polar Codes for Mission-Critical Machine-Type Communication Over Wireless Networks

Mission critical Machine-type Communication (mcMTC), also referred to as Ultra-reliable Low Latency Communication (URLLC), has become a research hotspot. It is primarily characterized by communication that provides ultra-high reliability and very low latency to concurrently transmit short commands to a massive number of connected devices. While the reduction in physical (PHY) layer overhead and improvement in channel coding techniques are pivotal in reducing latency and improving reliability, the current wireless standards dedicated to support mcMTC rely heavily on adopting the bottom layers of general-purpose wireless standards and customizing only the upper layers. The mcMTC has a significant technical impact on the design of all layers of the communication protocol stack. In this paper, an innovative bottom-up approach has been proposed for mcMTC applications through PHY layer targeted at improving the transmission reliability by implementing ultra-reliable channel coding scheme in the PHY layer of IEEE 802.11a standard bearing in mind short packet transmission system. To achieve this aim, we analyzed and compared the channel coding performance of convolutional codes (CCs), low-density parity-check (LDPC) codes, and polar codes in wireless network on the condition of short data packet transmission. The Viterbi decoding algorithm (VA), logarithmic belief propagation (Log-BP) algorithm, and cyclic redundancy check (CRC) successive cancellation list (SCL) (CRC-SCL) decoding algorithm were adopted to CC, LDPC codes, and polar codes, respectively. Consequently, a new PHY layer for mcMTC has been proposed. The reliability of the proposed approach has been validated by simulation in terms of Bit error rate (BER) and packet error rate (PER) vs. signal-to-noise ratio (SNR). The simulation results demonstrate that the reliability of IEEE 802.11a standard has been significantly improved to be at PER = 10⁻⁵ or even better with the implementation of polar codes. The results also show that the general-purpose wireless networks are prominent in providing short packet mcMTC with the modification needed.     

分布式无线传感器网络及其应用核心技术研究

提出一种分布式无线传感器网络体系结构,阐述了相关理论观点,分析其应用价值与研究现状：以减少传感器对网络的依赖为原则,增强传感器感知能力和感知精度、网络强壮性和容错性,并以传感器低功耗为研究思路;设计了以ARM体系结构32 b RISC（Reduce Instruction Computer）微处理器、uC／OS-Ⅱ嵌入式实时操作系统、轻量级TCP／IP网络协议LwIP（Lightweight TCP／IP Stack）,TR1000无线通信模块为核心的一种基于Internet的分布式微型无线网络传感器。     

Energy Optimised Security against Wormhole Attack in IoT-Based Wireless Sensor Networks

An IoT-based wireless sensor network (WSN) comprises many small sensors to collect the data and share it with the central repositories. These sensors are battery-driven and resource-restrained devices that consume most of the energy in sensing or collecting the data and transmitting it. During data sharing, security is an important concern in such networks as they are prone to many threats, of which the deadliest is the wormhole attack. These attacks are launched without acquiring the vital information of the network and they highly compromise the communication, security, and performance of the network. In the IoT-based network environment, its mitigation becomes more challenging because of the low resource availability in the sensing devices. We have performed an extensive literature study of the existing techniques against the wormhole attack and categorised them according to their methodology. The analysis of literature has motivated our research. In this paper, we developed the ESWI technique for detecting the wormhole attack while improving the performance and security. This algorithm has been designed to be simple and less complicated to avoid the overheads and the drainage of energy in its operation. The simulation results of our technique show competitive results for the detection rate and packet delivery ratio. It also gives an increased throughput, a decreased end-to-end delay, and a much-reduced consumption of energy.     

PUF-Based Key Distribution in Wireless Sensor Networks

Physical Unclonable Functions (PUFs) can be seen as kind of hardware oneway functions, who are easily fabricated but difficult to clone, duplicate or predict. Therefore, PUFs with unclonable and unpredictable properties are welcome to be applied in designing lightweight cryptography protocols. In this paper, a Basic Key Distribution Scheme (Basic-KDS) based on PUFs is firstly proposed. Then, by employing different deployment modes, a Random Deployment Key Distribution Scheme (RD-KDS) and a Grouping Deployment Key Distribution Scheme (GD-KDS) are further proposed based on the Basic-KDS for large scale wireless sensor networks. In our proposals, a sensor is not pre-distributed with any keys but will generate one by the embedded PUF when receiving a challenge from the gateway, which provides perfect resilience against sensor capture attacks. Besides, the unclonable and unpredictable properties of PUF guarantee the key uniqueness and two-way authentication. Analysis and experiment results show that our proposals have better performances in improving the resilience, secureconnectivity, and efficiency as compared to other schemes.     

An Asynchronous Clustering and Mobile Data Gathering Schema Based on Timer Mechanism in Wireless Sensor Networks

Recently, Wireless sensor networks (WSNs) have become very popular research topics which are applied to many applications. They provide pervasive computing services and techniques in various potential applications for the Internet of Things (IoT). An Asynchronous Clustering and Mobile Data Gathering based on Timer Mechanism (ACMDGTM) algorithm is proposed which would mitigate the problem of “hot spots” among sensors to enhance the lifetime of networks. The clustering process takes sensors’ location and residual energy into consideration to elect suitable cluster heads. Furthermore, one mobile sink node is employed to access cluster heads in accordance with the data overflow time and moving time from cluster heads to itself. Related experimental results display that the presented method can avoid long distance communicate between sensor nodes. Furthermore, this algorithm reduces energy consumption effectively and improves package delivery rate.     

Research on Time Synchronization Method Under Arbitrary Network Delay in Wireless Sensor Networks

To cope with the arbitrariness of the network delays, a novel method, referred to as the composite particle filter approach based on variational Bayesian (VB-CPF), is proposed herein to estimate the clock skew and clock offset in wireless sensor networks. VB-CPF is an improvement of the Gaussian mixture kalman particle filter (GMKPF) algorithm. In GMKPF, Expectation-Maximization (EM) algorithm needs to determine the number of mixture components in advance, and it is easy to generate overfitting and underfitting. Variational Bayesian EM (VB-EM) algorithm is introduced in this paper to determine the number of mixture components adaptively according to the observations. Moreover, to solve the problem of data packet loss caused by unreliable links, we propose a robust time synchronization (RTS) method in this paper. RTS establishes an autoregressive model for clock skew, and calculates the clock parameters based on the established autoregressive model in case of packet loss. The final simulation results illustrate that VB-CPF yields much more accurate results relative to GMKPF when the network delays are modeled in terms of an asymmetric Gaussian distribution. Moreover, RTS shows good robustness to the continuous and random dropout of time messages.     

An Optimized Algorithm for Resource Allocation for D2D in Heterogeneous Networks

With the emergence of 5G mobile multimedia services, end users’ demand for high-speed, low-latency mobile communication network access is increasing. Among them, the device-to-device (D2D) communication is one of the considerable technology. In D2D communication, the data does not need to be relayed and forwarded by the base station, but under the control of the base station, a direct local link is allowed between two adjacent mobile devices. This flexible communication mode reduces the processing bottlenecks and coverage blind spots of the base station, and can be widely used in dense user communication scenarios such as heterogeneous ultra-dense wireless networks. One of the important factors which affects the quality-of-service (QoS) of D2D communications is co-channel interference. In order to solve this problem of co-channel interference, this paper proposes a graph coloring based algorithm. The main idea is to utilize the weighted priority of spectrum resources and enables multiple D2D users to reuse the single cellular user resource. The proposed algorithm also provides simpler power control. The heterogeneous pattern of interference is determined using different types of interferences and UE and the priority of color is acquired. Simulation results show that the proposed algorithm effectively reduced the co-channel interference, power consumption and improved the system throughput as compared with existing algorithms.     

Three Dimensional Optimum Node Localization in Dynamic Wireless Sensor Networks

Location information plays an important role in most of the applications in Wireless Sensor Network (WSN). Recently, many localization techniques have been proposed, while most of these deals with two Dimensional applications. Whereas, in Three Dimensional applications the task is complex and there are large variations in the altitude levels. In these 3D environments, the sensors are placed in mountains for tracking and deployed in air for monitoring pollution level. For such applications, 2D localization models are not reliable. Due to this, the design of 3D localization systems in WSNs faces new challenges. In this paper, in order to find unknown nodes in Three-Dimensional environment, only single anchor node is used. In the simulation-based environment, the nodes with unknown locations are moving at middle & lower layers whereas the top layer is equipped with single anchor node. A novel soft computing technique namely Adaptive Plant Propagation Algorithm (APPA) is introduced to obtain the optimized locations of these mobile nodes. These mobile target nodes are heterogeneous and deployed in an anisotropic environment having an Irregularity (Degree of Irregularity (DOI)) value set to 0.01. The simulation results present that proposed APPA algorithm outperforms as tested among other meta-heuristic optimization techniques in terms of localization error, computational time, and the located sensor nodes.     

Pipeline Scheduling Based on Constructive Interference in Strip Wireless Sensor Networks

Strip Wireless Sensor Networks (SWSNs) have drawn much attention in many applications such as monitoring rivers, highways and coal mines. Packet delivery in SWSN usually requires a large number of multi-hop transmissions which leads to long transmission latency in low-duty-cycle SWSNs. Several pipeline scheduling schemes have been proposed to reduce latency. However, when communication links are unreliable, pipeline scheduling is prone to failure. In this paper, we propose a pipeline scheduling transmission protocol based on constructive interference. The protocol first divides the whole network into multiple partitions and uses a pipelined mechanism to allocate active time slots for each partition. The nodes in the same partition wake up at the same time for concurrent transmission. Multiple identical signals interfere constructively at the receiver node, which enhances received signal strength and improves link quality. Simulations show that the proposed scheme can significantly reduce the transmission latency while maintaining low energy consumption compared with other schemes.     

基于遗传算法的传感器网络拓扑控制研究

无线传感器网络的首要设计目标是延长网络生命期,网络的拓扑控制是实现这一目标的支撑 基础。针对传统拓扑控制方案所获拓扑的连通冗余度高或结构健壮性低等弊端,将问题转化 为多判据最小生成树模型,提出了一种基于遗传算法的拓扑控制方案。仿真实验结果 表明,该方案可获得具有网络整体功耗低、结构健壮性高和节点间通信干扰小等特点的拓扑 结构,因而能够有效地延长传感器网络生命期。     

基于神经网络的火炮射击振动衰减研究

振动对火炮的射击精度有较大的影响。建立了一种基于神经网络的火炮减振系统非线性动态模型，用位移和速度作为模型的输入，以控制量和其变化率作为输出，并给出了网络的学习算法。仿真显示，该控制器具有良好的稳定性，结构受控后振动衰减迅速，且控制器结构简单。     

基于网络传输特性的链路重要性评价方法

提出了一种基于网络传输特性的链路重要性评价方法,根据链路在网络所有节点相互通信的最短路径中的使用频度来评价链路重要性,最重要链路的使用频度最高.该方法不需要像目前的链路重要性评价方法那样进行链路收缩和删除,直接反映了链路对整个网络通信的贡献大小,可以判断通信网中任意两条链路的相对重要性.算法分析和实验仿真表明,文章算法克服了目前的评价方法存在的问题,给出了更直观合理的通信网链路重要性评价准则.     

变阻障碍物对管道内瓦斯爆炸的影响

为探究障碍物阻塞比变化率对瓦斯爆炸的影响,分别建立平均阻塞比为0.6、 0.3的受限空间物理模型,基于Charlette湍流燃烧模型,利用Fluent软件对阻塞比变化率依次为0、 0.05、 0.10、 0.15的障碍物条件下的爆炸火焰、湍流转捩、压力波耦合过程进行大涡模拟(LES)。研究结果表明：火焰经过障碍物会产生回流卷吸效应。在平均阻塞比为0.6的工况组A中,当阻塞比变化率为0.10、 0.15时,火焰锋面更加尖锐,火焰传播速度峰值更高,平均传播速度更高,到达超压所需时间更短,超压峰值更大。在平均阻塞比为0.3的工况组B中,各工况平均传播速度相同,随着阻塞比变化率的增大,到达超压所需时间更长,超压峰值更大。     

无线中继网络系统容量最大化中继选择机制

分析了基于用户频谱效率的中继选择算法的不足,基于最大流最小割定理,给出了系统容量最优化问题模型,分析了两跳中继网络接入链路和中继链路对系统容量的不同影响.基于链路权重因子,提出一种基于系统容量最大化的中继选择算法.对不同中继选择算法下的系统容量差异的理论与仿真分析结果表明,提出的系统容量最大化中继选择算法可以获得更优的系统容量性能,并对网络拓扑和节点个数具有良好的鲁棒性.     

集抄系统微功率无线通信模块检测技术研究

实现水、热、电、气"四表集抄"是发展智慧城市的必然趋势。因众多企业从事多表集抄通信模块的研究,造成生产规格和技术指标各有差异,对整个多表集抄系统互联互通建设带来困难。为了规范多表集抄系统,根据国家电网相关标准和技术规范,本文设计了微功率无线通信模块检测方法,提高了多表集抄系统的稳定性和精确性。     

自由口通讯协议在台州发电厂输煤程控半双工无线通讯系统中的实现

通过以自由口无线通讯方式实现台州发电厂输煤程控主系统和斗轮机间通讯的成功范例,阐述了无线通讯在工程实践中如何解决实时性和可靠性的方法。