无线传感器网络的密钥预分配方案

为阻止恶意节点加入传感器网络,在基于身份加密的密钥分配方案的基础上,提出了在节点加入网络时增加一个认证机制,即由第三方PKG签名一个包括节点身份和时间标记的数据包。在节点接入网络时,广播这样一个数据包,通过认证该数据包不仅能识别节点的身份,而且能区分新节点和旧节点,从而有效的验证该新节点的合法性,防止恶意节点加入传感器网络,能够抵御传感器网络中大多数常见的攻击。     

六边形网格划分的混合传感器网络调度方法

在混合无线传感器网络中,如何对动态节点进行合理调度以降低能耗并延长网络寿命一直是无线传感器网络研究的一个重要课题。本文针对大型的混合无线传感器网络,提出了一个基于正六边形网格划分的动态节点分布式调度方法,即通过网格划分的方式将此调度问题转化为一个多目标规划问题,并改良了方向网格划分下的节点通信机制,在保证各个动态节点能耗尽量均衡的情况下,降低动态节点能耗,减少传感器网络中总的数据包发送量,提高网络的综合性能。与其他的分布式算法和集中式算法的仿真对比表明了本文算法的有效性。     

基于ZigBee的实验室环境监测系统设计

针对实验室环境中安全监测需求的加强,提出了一种基于ZigBee的实验室环境监测系统,使传感器节点采集的温湿度、红外线等信息能够通过上位机分类存储到数据库,再通过统计与处理,在网页上呈现出无线传感器网络拓扑图和各类数据的综合显示,最终实现远程监测。当温湿度超出阈值或探测到人体红外,传感器节点会发送特殊数据包,上位机拆包分析后,将报警数据存储到警报数据表(AlertTable),在页面显示报警信息。     

基于阈值优先分割的光通信网络冲突解决方法

针对光通信网络中不同优先级业务突发冲突问题,导致数据服务质量差与丢包率高的问题,提出一种基于阈值优先分割的光通信网络冲突解决方法,该方法根据阈值分割准则来控制偏射路径,当不同优先级数据包冲突时,首先分割优先级较低的数据包进行偏射,然后根据阈值优先分割准则在冲突路由节点寻找最优路径,最后将冲突数据包通过预置或空闲路径传输,使得不同优先级业务数据包分配更加合理,最大限度地降低了由突发冲突引起的高阻塞率与丢包率。仿真结果表明,该方法可以有效降低总丢包率并保证其服务质量,且网络延时较小,从而改善整个OBS网络的服务质量性能。     

无线传感器网络质心定位算法仿真研究

质心定位算法是无线传感器网络中一种经典的无需测距的定位算法。系统分析了锚节点个数、节点通信半径以及网络中节点总数对该算法定位性能的影响,并进行了仿真。通过对仿真结果的分析,在100m×100m的无线传感器网络区域内,当锚节点个数为总节点个数的10％时,针对不同的总节点个数,存在最优的节点通信半径,可以使节点定位率达到95％以上,同时具有较小的节点定位误差。     

物联网下任务传输中节点占用内存优化方法

在物网环境下,提出基于阻塞机制排队顺序网络的任务传输分簇调度方法,实现网络内存优化目的。运用对物联网中不同类型节点对应数据包缓存最优配置方法,基于带阻塞排队网络对节点构建数据包排队模型,并分析模型阻塞情况;在排队网络中添加一定数量保持节点,按照节点使用情况判定数据包缓存大小。以排队网络为基础,建立物网任务传输调度模型,结合分簇任务信息流,提取节点信息特征后进行时隙优化配置,形成高效时分多址协议,通过时隙分配提升任务传输中节点传送数据准确性,达到优化内存管理的目标。实验证明,利用文中方法使物网中节点传输信息准确性提升占用内存减少。     

基于近端残余能量激活的无线网络通讯算法研究

无线传感器网络中的传感器节点安装在一定的感知环境下,每个传感器有自己的感知范围,节点的死亡造成了网络的信号重复通信、网络发生冗余与资源浪费.为此,本文提出一种基于近端残余能量激活的无线网络通讯优化算法,将节点表示为近端寻优粒子,采用交叉遗传的方式对节点的性能多样性进行保持,将节点的残存能量作为目标函数进行优化,找到残存能量较大的最优节点进行通信.实验仿真结果证明,经过交叉遗传的PSO网络通信控制的优化后,无线传感器网络的通信性能比传统的方法有了明显提高,证明本算法具有很强的可行性与实用价值.     

物联网无线传感器能耗优化SIFT算法的研究

针对目前物联网系统中无线传感器网络在传播信息时能耗损失严重的问题,本文提出了一种应用于物联网无线传感器的改进SIFT算法。该算法基于传统SIFT算法,并在其基础上,进行了节点端自适应优化和全局性动态调整的优化方案。通过参考路由层和应用层信息确定节点的优先级,修正节点的退让长度,实现重要数据先行;通过对接人节点数目和数据流的统计,实现对参数组和信道竞争窗口长度的全局性动态调整。实验表明,本文提出的改进算法在能耗上比传统算法优秀,值得推广使用。     

一种基于主动网络的编程语言PLAN的研究

主动网络的出现改变了现有网络只能传递数据信息的现状,主动网络节点可以通过执行附加到数据包中的程序对数据包进行处理从而提高网络的可编程性和灵活性。PLAN语言专为主动网络设计,用其编写的程序构成了主动网络的数据包。用PLAN编写的TraceRoute程序充分展示了这门语言灵活、安全及高性能等特点。     

基于物联网的光纤应变传感器节点覆盖技术

在采用传统方法对光纤应变传感器网络节点进行覆盖时,节点部署缺乏随机性,导致覆盖漏洞、覆盖准确度低和能量消耗大等问题。提出一种基于物联网的光纤应变传感器网节点覆盖技术。通过构建3D有向感知模型,调节几何形状的主感知方向,在光纤应变网络节点的半径符合3D有向感知模型,且节点位置不再发生变化的前提下,在3D空间随机部署节点,获取3D光纤应变网络节点的覆盖率,通过计算离散点简化光纤应变传感器网络节点的覆盖率。通过调度光纤应变网络节点位置关系,提高覆盖质量,最终完成光纤应变传感器节点高效覆盖。仿真实验证明,本文研究的覆盖方法具有较高的可行性和有效性,能够很好的解决光纤应变传感器网络中节点覆盖的问题。     

Generalized pseudo-Bayesian estimator for networked control systems over UDP-like channels

This paper focuses on state estimation issues for networked control systems (NCSs) with both control input and observation packet dropouts over user datagram protocol (UDP) communication channels. For such systems, which are usually known as UDP-like systems, the computation cost of the optimal estimator is too high to afford in practice due to exponential growth of complexity. Although quite a few suboptimal estimators could be alternatives for improving the computational efficiency, yet researches on the stability of suboptimal estimators are rarely reported. Based on the generalized pseudo-Bayesian (GPB) algorithm, an efficient suboptimal algorithm is developed for UDP-like systems. More crucially, a sufficient condition is obtained, which guarantees the stability of its mean estimation error covariance. This stability condition explicitly expresses that the rate of observation packet dropout is a critical factor in determining the stability of the proposed GPB estimator, while the rate of control input packet dropout has no influence on it. The results are illustrated by numerical examples.     

Estimation fusion for networked systems with multiple asynchronous sensors and stochastic packet dropouts

This paper studies the asynchronous state fusion estimation problem for multi-sensor networked systems subject to stochastic data packet dropouts. A set of Bernoulli sequences are adopted to describe the random packet losses with different arriving probabilities for different sensor communication channels. The asynchronous sensors considered in this paper can have arbitrary sampling rates and arbitrary initial sampling instants, and may even sample the system non-uniformly. Asynchronous measurements collected within the fusion interval are transformed to the fusion time instant as a combined equivalent measurement. An optimal asynchronous estimation fusion algorithm is then derived based on the transformed equivalent measurement using the recursive form of linear minimum mean squared error (LMMSE) estimator. Cross-correlations between involved random variables are carefully calculated with the stochastic data packet dropouts taken into account. A numerical target tracking example is provided to illustrate the feasibility and effectiveness of the proposed algorithm.     

CEO最优网络规模研究

为了探讨CEO网络规模与CEO的网络中介中心性、网络联结路径、网络嵌入性之间的关系,寻求最有利于企业价值最大化目标实现的CEO最优网络规模,本文采用网络规模指数来衡量CEO网络规模大小,运用图论分析CEO与网络中其他成员的关系联结结构,通过博弈分析求解最优CEO网络规模。结果表明,在非正式制度环境下,CEO在网络中与其他成员的有效合作能够使CEO网络规模在某一水平上达到均衡,此时的最优化网络规模较小;在正式制度环境下,CEO在网络中具有高中介中心性,此时有效发挥CEO对其他网络成员的监管效力,有助于提高CEO与其他网络成员的合作效率,扩大其最优网络规模,进一步提升企业价值。     

Optimal tracking performance and design of networked control systems with packet dropouts

The optimal tracking problem for single-input–single-output (SISO) networked control system over a communication channel with packet dropouts is studied in this paper. The tracking performance is measured by the energy of the error signal between the output of the plant and the reference signal. It is shown that the optimal tracking performance is constrained by nonminimum phase zeros, unstable poles, the characteristics of the reference signal and packet dropout probability, and the optimal controller is obtained. It is also shown that when the communication constraint does not exist, the optimal tracking performance reduces to the existing normal tracking performance of the control system without a communication channel. The result shows how the packet dropouts probability of a communication channel may fundamentally constrain a control system's tracking ability. Some typical examples and simulations are given to illustrate the theoretical results.     

Destination buffer analysis for packets rejection obliteration in multi-channel networks

In this paper we study a multi-channel network, each station of which is equipped with a network interface that has a receiver buffer of multiple packets. In this way, each station is able to receive multiple packets per time instant. We adopt a synchronous access protocol which is affected by the collisions over the multiple channels and the destination conflicts. The proposed protocol performance crucially depends on the size of the receiver buffer since it determines the packet rejection probability at destination. An analytical probabilistic model based on a Markovian process is adopted for the performance measures derivation by means of closed mathematical formulas. The proposed protocol is compared to relative ones that either totally ignore the receiver collisions or assume a receiver buffer of a single packet capacity. The numerical results show that the increase of the receiver buffer size improves the performance decisively, resulting in higher throughput and lower delay and rejection probability. Also, it is shown that the appropriate receiver buffer size per station in order for the rejections at destination to be effectively eliminated is not unlimited but is limited to three packets for 0.1% accepted maximum level of rejection probability.     

On the relaxed gradient-based iterative methods for the generalized coupled Sylvester-transpose matrix equations

In this paper, we propose the full-rank and reduced-rank relaxed gradient-based iterative algorithms for solving the generalized coupled Sylvester-transpose matrix equations. We provide analytically the necessary and sufficient condition for the convergence of the proposed iterative algorithm and give explicitly the optimal step size such that the convergence rate of the algorithm is maximized. Some numerical examples are examined to confirm the feasibility and efficiency of the proposed algorithms.     

Sliding mode control for stochastic Markovian jumping systems subject to successive packet losses

In this work, the problem of sliding mode control is considered for a class of Markovian jumping systems. The packet dropout may happen when the state information is transmitted from the sensor to the controller. By means of an estimator for lost signals, an integral-like sliding function is constructed. And then, a sliding mode controller involving in dropout probability is designed such that the effect of packet losses can be effectively attenuated. Besides, the analysis on both the stability of sliding mode dynamics and the reachability of sliding surface are made. Finally, the numerical simulation results are given.     

Centralized fusion estimation over wireless sensor-actuator networks with unobservable packet dropouts

This paper studies centralized fusion estimation over a wireless sensor-actuator network, where packet dropouts cannot be observed by the fusion estimator. For such a system, we obtain an optimal linear fused estimation of system states, also known as optimal linear estimator. Then, we establish a necessary and sufficient condition for the stability of the optimal linear estimator. Finally, we show that the estimation performance is monotonically decreasing with respect to the observation packet-arrival rate. By analyzing a sequence that converges to the covariance of the optimal linear estimator, an analytical relationship between the estimation performance and the control packet-arrival rate is obtained. Simulation examples are given to illustrate the main results.     

Innovation input-output and output-lagged input relationships of the next-generation information industry in China

The input-output relationship of innovation is usually classified as the research of innovation efficiency, which is of great significance to industrial development. Considering the lack of understanding of information industry innovation ability, this paper used data envelopment analysis (DEA) and the Malmquist index to study the innovation efficiency of next-generation information (NGI) industry in China by employing data from financial statements between 2012 and 2017. Partial least squares (PLS) regression model was used to explore the causal relationship between innovation input-output and between innovation output-lagged input of NGI industry, as well as possible mediating effects in these relationships from ownership structure, ownership concentratial clusters, company size, and innovation effectiveness. Empirical results showed that: (1) The innovation input, output, and efficiency of NGI companies varied significantly. (2) The innovation input, output, and efficiency of most NGI companies varied significantly across the years. (3) The innovation efficiency and efficiency change of NGI company have grown continuously. (4) No significant causal relationships between innovation input-output, or between innovation output-lagged input were found. (5) Company size and innovation effectiveness had significant mediating effects on the input-output causal relationships. Therefore, this paper suggested that the governments may enact NGI policies that focus on the innovation input-output and output-lagged input relationships, and may take into account the differentiated needs of the NGI enterprises based on the company size and innovation effectiveness.