WLAN中的无线入侵检测系统的应用

安全隐患在无线高速局域网的设计和应用中受到日益关注,本文对无线局域网中的安全问题进行概括,分析了入侵检测技术在无线网络中的应用,讨论了无线局域网中的入侵检测模型。     

无线mesh网络中的信道分配问题研究

在多接口无线mesh网络中使用多信道可以减少碰撞和干扰,提高系统吞吐量。因此,合理的信道分配是无线mesh网络中多信道技术的关键。用图论理论建立信道分配数学模型以及用图着色理论研究信道分配问题是无线网络中解决信道分配问题的有效方法。因此针对无线mesh网络中多接口多信道(multi-radio and multi-channel)的特点,重点介绍了无线mesh网络中信道分配的基本理论、主要约束和图论模型等,最后提出应用图着色理论解决信道分配问题的一般途径。     

无线Mesh网络技术在校园无线网络建设中的应用

在人们的生活中无线互联局域网发展越来越快,在范围比较大的区域要使用WLAN进行无线网络全覆盖具有一定的局限性。无线Mesh网络是一种新型的无线网络,覆盖范围大,容量大,效率高。在校园网的无线网络建设中无线Mesh网络发挥着重要的作用。文章对无线Mesh网络技术进行分析,并对无线Mesh网络技术在校园无线网络建设中的应用进行研究。     

射线追踪模型在无线城市网络规划中的应用

为满足无线城市数据业务需求而导致无线网络密度的增加,以及由于城市中基站周边高层建筑较多,使得传统传播模型在规划仿真中偏差较大而仿真的准确程度影响着整个规划过程的准确性和合理性的验证。本文介绍采用射线追踪模型解决城市无线网络规划中仿真精度的难题,并使用特定射线追踪模型分析其在无线城市网络规划中的应用。     

基于IP无线网络中的移动性

基于IP的无线网络将成为下一代移动网络的核心。在全IP无线网络中,移动性对多媒体应用起着十分重要的作用。文中探讨了基于IP的无线网络中的一些重要问题,包括移动IP、移动IPv6和其它相关的一些技术。还讨论了无线局域网(WLAN)、无线广域网(WWAN)、2G以及3G蜂窝网和下一代混合移动网络中关于移动性支持等问题。     

无线传感器网络中的信任管理研究现状

无线传感器网络是一种新型的无基础设施的无线网络,具有与传统网络不同的特点,且与应用高度相关.传统网络中的安全机制不能有效应用于无线传感器网络,需要建立信任管理模型来保证网络的安全性.本文首先介绍了无线传感器网络的特点和建立信任管理模型需要考虑的关键问题,然后分析了一些较为典型的信任管理模型.最后,总结了无线传感器网络中...     

基于无线CBTC数据通信系统的射频信号传播研究

研究并提出了隧道中基于无线CBTC数据通信系统的无线射频信号理论传播模型,并从理论模型和实地无线网络勘测两个角度对无线信号在隧道中的传播特性进行了仔细的研究及分析工作。     

无线网络智能优化系统及其应用

文章首先针对现有的无线信道资源分配方法进行分析,介绍了无线网络智能优化模型;然后基于该模型的优化算法和关键技术方案,开发了无线网络智能优化系统;最后以应用举例来说明该系统的研究和开发可提高无线网络优化工作的效率及质量。     

基于因子图的自适应波束形成

图模型具有广泛的应用,它为许多问题提供了一种新的表达方式和研究思路。因子图作为一类重要的图模型,尤其适用于多变量的复杂统计模型。因子图的引入可以使复杂的多变量问题得到简化。因子图理论在系统建模以及信号检测和估计算法中有着重要的应用。国内外不少学者将因子图理论应用于复杂的通信信号处理,但目前很少见到将因子图理论应用在雷达信号处理中。为了将因子图理论作为一种有效的工具应用于雷达信号处理,提出了用因子图理论实现雷达信号处理中的自适应波束形成技术（ADBF）的方法,这为用图模型研究雷达信号处理提供了一个很好的思路。     

郊区交通干道无缝覆盖解决方案

针对郊区交通干道中实现无线无缝覆盖的特点，结合在广东省数字移动通信工程无线网络中的实际应用经验，提出一些相应的解决方案。     

A factor graph approach to link loss monitoring in wireless sensor networks

The highly stochastic nature of wireless environments makes it desirable to monitor link loss rates in wireless sensor networks. In a wireless sensor network, link loss monitoring is particularly supported by the data aggregation communication paradigm of network traffic: the data collecting node can infer link loss rates on all links in the network by exploiting whether packets from various sensors are received, and there is no need to actively inject probing packets for inference purposes. In this paper, we present a low complexity algorithmic framework for link loss monitoring based on the recent modeling and computational methodology of factor graphs. The proposed algorithm iteratively updates the estimates of link losses upon receiving (or detecting the loss of) recently sent packets by the sensors. The algorithm exhibits good performance and scalability, and can be easily adapted to different statistical models of networking scenarios. In particular, due to its low complexity, the algorithm is particularly suitable as a long-term monitoring facility.     

Product Multicommodity Flow in Wireless Networks

We provide a tight approximate characterization of the n-dimensional product multicommodity flow (PMF) region for a wireless network of n nodes. Separate characterizations in terms of the spectral properties of appropriate network graphs are obtained in both an information-theoretic sense and for a combinatorial interference model (e.g., protocol model). These provide an inner approximation to the n ²-dimensional capacity region. Our results hold for general node distributions, traffic models, and channel fading models. We first establish that the random source-destination model assumed in many previous results on capacity scaling laws, is essentially a one-dimensional approximation to the capacity region and a special case of PMF. We then build on the results for a wireline network (graph) that relate PMF to its spectral (or cut) properties. Specifically, for a combinatorial interference model given by a network graph and a conflict graph, we relate the PMF to the spectral properties of the underlying graphs resulting in simple computational upper and lower bounds. These results show that the 1/radicn scaling law obtained by Gupta and Kumar for a geometric random network can be explained in terms of the scaling law of the conductance of a geometric random graph. For the more interesting random fading model with additive white Gaussian noise (AWGN), we show that the scaling laws for PMF can again be tightly characterized by the spectral properties of appropriately defined graphs-such a characterization for general wireless networks has not been available before. As an implication, we obtain computationally efficient upper and lower bounds on the PMF for any wireless network with a guaranteed approximation factor.     

Separability and topology control of quasi unit disk graphs

A deep understanding of the structural properties of wireless networks is critical for evaluating the performance of network protocols and improving their designs. Many protocols for wireless networks—routing, topology control, information storage/retrieval and numerous other applications—have been based on the idealized unit-disk graph (UDG) network model. The significant deviation of the UDG model from many real wireless networks is substantially limiting the applicability of such protocols. A more general network model, the quasi unit-disk graph (quasi-UDG) model, captures much better the characteristics of wireless networks. However, the understanding of the properties of general quasi-UDGs has been very limited, which is impeding the designs of key network protocols and algorithms. In this paper, we present results on two important properties of quasi-UDGs: separability and the existence of power efficient spanners. Network separability is a fundamental property leading to efficient network algorithms and fast parallel computation. We prove that every quasi-UDG has a corresponding grid graph with small balanced separators that captures its connectivity properties. We also study the problem of constructing an energy-efficient backbone for a quasi-UDG. We present a distributed local algorithm that, given a quasi-UDG, constructs a nearly planar backbone with a constant stretch factor and a bounded degree. We demonstrate the excellent performance of these auxiliary graphs through simulations and show their applications in efficient routing.     

基于概率图模型的音乐推荐方法

提出了一种基于概率图模型的音乐推荐方法。该方法利用歌曲相似度确定歌曲间的关系,从而建立歌曲网络,在此基础上利用主题模型得到的歌曲主题概率分布,建立包含局部属性（主题概率分布）和全局结构（歌曲网络）的概率图模型,转化为因子图后,再利用推理算法对概率图模型进行计算,最终获得歌曲在不同主题下的推荐列表。实验表明,本方法能够获得较好的推荐效果,是对音乐推荐方法的有益探索。     

On Construction of Virtual Backbone in Wireless Ad Hoc Networks with Unidirectional Links

Since there is no fixed infrastructure in wireless ad hoc networks , virtual backbone has been proposed as the routing infrastructure to alleviate the broadcasting storm problem. The virtual backbone construction has been studied extensively in {em undirected} graphs, especially in unit disk graphs, in which each node has the same transmission range. In practice, however, transmission ranges of all nodes are not necessarily equal. In this paper, we model such a network as a disk graph, where unidirectional links are considered. To study the virtual backbone construction in disk graphs, we consider two problems: Strongly Connected Dominating Set (SCDS) and Strongly Connected Dominating and Absorbing Set (SCDAS). We propose a constant approximation algorithm and discuss its improvements for the SCDS problem . We also propose a heuristic for the SCDAS problem. Through extensive simulations, we verify our theoretical analysis and also demonstrate that the SCDS can be extended to form an SCDAS with marginal extra overhead.     

基于信任度权衡的无线传感器网络安全研究

在其他人的研究基础上,总结出了无线传感器网络当前存在的安全问题,并根据自身的研究成果,提出了一种基于信任度权衡的无线传感器网络访问机制模型,详细阐述了该模型的相关原理、实验方法及结论,为无线传感器网络安全研究提供了一种新思路。     

Connected Dominating Sets in Wireless Networks with Different Transmission Ranges

Since there is no fixed infrastructure or centralized management in wireless ad hoc networks, a Connected Dominating Set (CDS) has been proposed to serve as a virtual backbone. The CDS of a graph representing a network has a significant impact on the efficient design of routing protocols in wireless networks. This problem has been studied extensively in Unit Disk Graphs (UDG), in which all nodes have the same transmission ranges. However, in practice, the transmission ranges of all nodes are not necessarily equal. In this paper, we model a network as a disk graph and introduce the CDS problem in disk graphs. We present two efficient approximation algorithms to obtain a minimum CDS. The performance ratio of these algorithms is constant if the ratio of the maximum transmission range over the minimum transmission range in the network is bounded. These algorithms can be implemented as distributed algorithms. Furthermore, we show a size relationship between a maximal independent set and a CDS as well as a bound of the maximum number of independent neighbors of a node in disk graphs. The theoretical analysis and simulation results are also presented to verify our approaches.     

Embedded trees: estimation of Gaussian Processes on graphs with cycles

Graphical models provide a powerful general framework for encoding the structure of large-scale estimation problems. However, the graphs describing typical real-world phenomena contain many cycles, making direct estimation procedures prohibitively costly. In this paper, we develop an iterative inference algorithm for general Gaussian graphical models. It operates by exactly solving a series of modified estimation problems on spanning trees embedded within the original cyclic graph. When these subproblems are suitably chosen, the algorithm converges to the correct conditional means. Moreover, and in contrast to many other iterative methods, the tree-based procedures we propose can also be used to calculate exact error variances. Although the conditional mean iteration is effective for quite densely connected graphical models, the error variance computation is most efficient for sparser graphs. In this context, we present a modeling example suggesting that very sparsely connected graphs with cycles may provide significant advantages relative to their tree-structured counterparts, thanks both to the expressive power of these models and to the efficient inference algorithms developed herein. The convergence properties of the proposed tree-based iterations are characterized both analytically and experimentally. In addition, by using the basic tree-based iteration to precondition the conjugate gradient method, we develop an alternative, accelerated iteration that is finitely convergent. Simulation results are presented that demonstrate this algorithm's effectiveness on several inference problems, including a prototype distributed sensing application.     

A Three Layered Peer-to-Peer Energy Efficient Protocol for Reliable and Secure Data Transmission in EAACK MANETs

The wireless body sensor network (WBSN) an extensive of WSN is in charge for the detection of patient’s health concerned data. This monitored health data are essential to be routed to the sink (base station) in an effective way by approaching the routing technique. Routing of tremendous sensed data to the base station minimizes the life time of the network due to heavy traffic occurrence. The major concern of this work is to increase the lifespan of the network which is considered as a serious problem in the wireless network functionalities. In order to recover this issue, we propose an optimal trust aware cluster based routing technique in WBSN. The human body enforced for the detection of health status is assembled with sensor nodes. In this paper, three novel schemes namely, improved evolutionary particle swarm optimization (IEPSO), fuzzy based trust inference model, and self-adaptive greedy buffer allocation and scheduling algorithm (SGBAS) are proposed for the secured transmission of data. The sensor nodes are gathered to form a cluster and from the cluster, it is necessary to select the cluster head (CH) for the effective transmission of data to nearby nodes without accumulation. The CH is chosen by considering IEPSO algorithm. For securable routing, we exhibit fuzzy based trust inference model to select the trusted path. Finally, to reduce traffic occurrence in the network, we introduce SGBAS algorithm. Experimental results demonstrate that our proposed method attains better results when compared with conventional clustering protocols and in terms of some distinctive QoS determinant parameters.     

温室无线测控网络信息采集分系统设计研究

把无线传感器网络技术应用于温室无线测控网络信息采集分系统的设计.通过在温室大棚部署具有自组网传输能力的无线传感器网络,结合温室智能控制系统和农业信息专家系统,实现了温室信息采集的自动部署、自组织传输和温室环境的精细化控制.其中基于PC机的优化控制站点完成温室环境控制的智能决策及温室传感信息的海量存储、实时查询、统计分析和图形化显示,系统通过集成GPRS和以太网接口,实现了温室信息的远程访问.