Localized Coverage Connectivity Based on Shape and Area Using Mobile Sensor Robots in Wireless Sensor Networks

A wireless sensor network (WSN) is spatially distributing independent sensors to monitor physical and environmental characteristics such as temperature, sound, pressure and also provides different applications such as battlefield inspection and biological detection. The Constrained Motion and Sensor (CMS) Model represents the features and explain k-step reach ability testing to describe the states. The description and calculation based on CMS model does not solve the problem in mobile robots. The ADD framework based on monitoring radio measurements creates a threshold. But the methods are not effective in dynamic coverage of complex environment. In this paper, a Localized Coverage based on Shape and Area Detection (LCSAD) Framework is developed to increase the dynamic coverage using mobile robots. To facilitate the measurement in mobile robots, two algorithms are designed to identify the coverage area, (i.e.,) the area of a coverage hole or not. The two algorithms are Localized Geometric Voronoi Hexagon (LGVH) and Acquaintance Area Hexagon (AAH). LGVH senses all the shapes and it is simple to show all the boundary area nodes. AAH based algorithm simply takes directional information by locating the area of local and global convex points of coverage area. Both these algorithms are applied to WSN of random topologies. The simulation result shows that the proposed LCSAD framework attains minimal energy utilization, lesser waiting time, and also achieves higher scalability, throughput, delivery rate and 8% maximal coverage connectivity in sensor network compared to state-of-art works.

Application of Wireless Local Area Network Technology in Mobile Robot for Finned Tube Inspection

This paper introduces a novel robot for outer surface inspection of boiler tubes. The paper describes the hardware system, wireless communication strategy, communication procedure and system software of the robot. The WLAN technology is used in the robot. It solves the problem of shielding generated by iron boiler and 11Mbps bandwidth made it possible for video and control stream real-time transmit within the same channel. Though TCP/IP protocol is robust, serial server is a transparent channel but cannot detect error and retransmit the data. In order to improve the reliability of serial communication, a new communication protocol is proposed. Key words boiler tubes - mobile robotics - wireless local area network Project Supported by the National High-Tech Program (Grant No. 2002AA420080)

Research on the Teaching Reform of ＂Wireless Local Area Network＂ in the Background of＂Wireless Business Circle＂

This paper proposes the teaching reform of the ＂Wireless Local Area Network＂ in the background of ＂Wireless Business Circle＂ . At present, WLAN technology is becoming more and more mature, the application is then becoming more and more extensive, the campus network will grow rapidly on wireless LAN applications especially the research and higher education institutions on the wireless LAN demand is increasing with wireless LAN will have a very broad market development space. GIS business circle analysis model is to determine business enterprise location or expand their existing business outlets of information necessary to say on the map by G1S visual function of the model. This paper makes the combination of the mentioned items that will then and later influence the performance of the model.

Wireless-LAN安全及认证方法的研究与分析

首先介绍了无线局域网面临的安全问题,并对无线局域网的安全要求进行了分析;介绍了国内外Wire-less-LAN安全认证机制的研究现状,在此基础上详细分析了基于EAP的无线网络安全认证方法;最后对几种主要的认证方法进行了分析比较。

基于自发数据传输的高效双LAN太赫兹无线局域网MAC协议

针对现有的双局域网(LAN)太赫兹无线局域网(Dual-LAN THz WLAN)相关介质访问控制(MAC)协议中存在的某些节点会在多个超帧内重复发送相同的信道时隙请求帧以申请时隙资源以及网络运行的一些时段存在空闲时隙等问题,提出一种基于自发数据传输的高效MAC协议——SDTE-MAC(high-Efficiency MAC protocol based on Spontaneous Data Transmission)。SDTE-MAC通过让各节点都维护一张或多张时间单元链表,使各节点与其余节点在网络运行时间上达到同步,从而获悉各节点应该在信道空闲时隙的什么位置开始发送数据帧,优化了传统的信道时隙分配和信道剩余时隙再分配的流程,提高了网络吞吐量和信道时隙利用率,降低了数据时延,能够进一步提升双LAN太赫兹无线局域网的性能。仿真结果表明,网络饱和时,相较于AHT-MAC(Adaptive High Throughout multi-pan MAC protocol)中的N-CTAP(Normal Channel Time Allocation Period)时段时隙资源分配新机制以及自适应缩短超帧时段机制,SDTE-MAC的MAC层吞吐量提升了9.2%,信道时隙利用率提升了10.9%,数据时延降低了22.2%。

An adaptive joint source and channel coding scheme for H.264 video multicasting over wireless LAN

This paper proposes an adaptive joint source and channel coding scheme for H.264 video multicast over wireless LAN which takes into account the user topology changes and varying channel conditions of multiple users, and dynamically allocates available bandwidth between source coding and channel coding, with the goal to optimize the overall system performance. In particular, source resilience and error correction are considered jointly in the scheme to achieve the optimal performance. And a channel estimation algorithm based on the average packet loss rate and the variance of packet loss rate is proposed also. Two overall performance criteria for video multicast are investigated and experimental results are presented to show the improvement obtained by the scheme.

Radio map updated method based on subscriber locations in indoor WLAN localization

With the rapid development of wireless local area network （WLAN） technology, an important target of indoor positioning systems is to improve the positioning accuracy while reducing the online calibration effort to overcome signal time-varying. A novel fingerprint positioning algorithm, known as the adaptive radio map with updated method based on hidden Markov model （HMM）, is proposed. It is shown that by using a collection of user traces that can be cheaply obtained, the proposed algorithm can take advantage of these data to update the labeled calibration data to further improve the position estimation accuracy. This algorithm is a combination of machine learning, information gain theory and fingerprinting. By collecting data and testing the algorithm in a realistic indoor WLAN environment, the experiment results indicate that, compared with the widely used K nearest neighbor algorithm, the proposed algorithm can improve the positioning accuracy while greatly reduce the calibration effort.

A Semi-Supervised WLAN Indoor Localization Method Based on l1-Graph Algorithm

For indoor location estimation based on received signal strength( RSS) in wireless local area networks( WLAN),in order to reduce the influence of noise on the positioning accuracy,a large number of RSS should be collected in offline phase. Therefore,collecting training data with positioning information is time consuming which becomes the bottleneck of WLAN indoor localization. In this paper,the traditional semisupervised learning method based on k-NN and ε-NN graph for reducing collection workload of offline phase are analyzed,and the result shows that the k-NN or ε-NN graph are sensitive to data noise,which limit the performance of semi-supervised learning WLAN indoor localization system. Aiming at the above problem,it proposes a l1-graph-algorithm-based semi-supervised learning( LG-SSL) indoor localization method in which the graph is built by l1-norm algorithm. In our system,it firstly labels the unlabeled data using LG-SSL and labeled data to build the Radio Map in offline training phase,and then uses LG-SSL to estimate user's location in online phase. Extensive experimental results show that,benefit from the robustness to noise and sparsity ofl1-graph,LG-SSL exhibits superior performance by effectively reducing the collection workload in offline phase and improving localization accuracy in online phase.

Synchronization in Wireless Networks for Practical MIMO-OFDM Systems

In this paper a frequency offset estimation technique for Wireless Local Area and Wireless Metropolitan Ar- ea Networks is presented. For frequency offset estimation, we have applied a low-complexity frequency offset estimator for simple AWGN channels to fading channels for MIMO-OFDM systems. Simulation results have shown that the performance of the proposed estimator is better than the low complexity frequency offset estimator designed for AWGN channels.

Resource Exhaustion Attack Detection Scheme for WLAN Using Artificial Neural Network

IEEE 802.11 Wi-Fi networks are prone to many denial of service(DoS)attacks due to vulnerabilities at the media access control(MAC)layer of the 802.11 protocol.Due to the data transmission nature of the wireless local area network(WLAN)through radio waves,its communication is exposed to the possibility of being attacked by illegitimate users.Moreover,the security design of the wireless structure is vulnerable to versatile attacks.For example,the attacker can imitate genuine features,rendering classificationbased methods inaccurate in differentiating between real and false messages.Althoughmany security standards have been proposed over the last decades to overcome many wireless network attacks,effectively detecting such attacks is crucial in today’s real-world applications.This paper presents a novel resource exhaustion attack detection scheme(READS)to detect resource exhaustion attacks effectively.The proposed scheme can differentiate between the genuine and fake management frames in the early stages of the attack such that access points can effectively mitigate the consequences of the attack.The scheme is built through learning from clustered samples using artificial neural networks to identify the genuine and rogue resource exhaustion management frames effectively and efficiently in theWLAN.The proposed scheme consists of four modules whichmake it capable to alleviates the attack impact more effectively than the related work.The experimental results show the effectiveness of the proposed technique by gaining an 89.11%improvement compared to the existing works in terms of detection.

A NOVEL LINK ADAPTATION SCHEME TO ENHANCE PERFORMANCE OF IEEE 802.11G WIRELESS LAN

A novel link adaptation scheme using linear Auto Regressive （AR） model channel estimation algorithm to enhance the performance of auto rate selection mechanism in IEEE 802.11g is proposed. This scheme can overcome the low efficiency caused by time interval between the time when Received Signal Strength （RSS） is measured and the time when rate is selected. The best rate is selected based on data payload length, frame retry count and the estimated RSS, which is estimated from recorded RSSs. Simulation results show that the proposed scheme enhances mean throughput performance up to 7%, in saturation state, and up to 24% in finite load state compared with those non-estimation schemes, performance enhancements in average drop rate and average number of transmission attempts per data frame delivery also validate the effectiveness of the proposed schelne.

基于IRF-PF算法的WLAN室内定位方法

针对室内复杂环境下无线局域网接收信号强度的时变波动性,提出一种基于改进随机森林算法并融合粒子滤波的室内定位方法。首先,通过自适应滑动窗口选取接收信号强度较为平滑的信号接入点作为定位指纹特征建立决策树,从而减少特征空间的噪声;然后,利用bagging抽样后的袋外数据赋予决策树不同的投票权重等级,增大决策树类别间判别差异性,优化随机森林算法在目标位置与接收信号强度间弱映射关联性场景下定位精度低的问题,依据改进的随机森林算法建立位置坐标与接收信号强度间的映射模型,计算定位点的位置;最后,为了提高定位准确性与稳定性,将依据改进随机森林算法计算出的位置作为粒子滤波的观测量,利用粒子滤波对目标位置进行估计和预测。在Zenodo数据集上的实验结果表明:提出的算法在定位误差2 m范围内精度达到75.8%,在4 m范围内精度已经高达94.8%;相比于传统随机森林算法,能够将2 m内的定位精度提高11.5%;与K近邻、岭回归和贝叶斯等室内定位算法相比,定位精度和算法实时性也得到明显提升。

Energy efficiency aware dynamic rate and power adaptation in carrier sensing based WLANs under Rayleigh fading and shadowing

We consider the problem of energy efficiency aware dynamic adaptation of data transmission rate and transmission power of the users in carrier sensing based Wireless Local Area Networks(WLANs)in the presence of path loss,Rayleigh fading and log-normal shadowing.For a data packet transmission,we formulate an optimization problem,solve the problem,and propose a rate and transmission power adaptation scheme with a restriction methodology of data packet transmission for achieving the optimal energy efficiency.In the restriction methodology of data packet transmission,a user does not transmit a data packet if the instantaneous channel gain of the user is lower than a threshold.To evaluate the performance of the proposed scheme,we develop analytical models for computing the throughput and energy efficiency of WLANs under the proposed scheme considering a saturation traffic condition.We then validate the analytical models via simulation.We find that the proposed scheme provides better throughput and energy efficiency with acceptable throughput fairness if the restriction methodology of data packet transmission is included.By means of the analytical models and simulations,we demonstrate that the proposed scheme provides significantly higher throughput,energy efficiency and fairness index than a traditional non-adaptive scheme and an existing most relevant adaptive scheme.Throughput and energy efficiency gains obtained by the proposed scheme with respect to the existing adapting scheme are about 75%and 103%,respectively,for a fairness index of 0.8.We also study the effect of various system parameters on throughput and energy efficiency and provide various engineering insights.

CBTC系统WLAN车地无线通信网络在线监测关键技术及应用

目前国内大部分城市轨道交通车地无线通信系统仍采用IEEE 802.11 b/g协议,工作在2.4 GHz ISM开放频段,车地通信故障易造成列车紧急停车等情况。针对目前车地无线通信监测完整性和实用性不足、全链条监测手段缺乏等问题,结合无线通信系统范围广、场景多、故障现象迷惑性强等特点,融合无线场强采集、数据流监听、无线图谱定位、贝叶斯网络故障等定位技术,利用软硬件结合的方式构建全链条车地无线智能分析监测系统。采用射频处理单元+运行处理单元软硬件分离的架构模式设计无线监测终端,采用C/S架构和人工智能技术设计车地无线智能分析监测系统,实现从车载到轨旁无线场强、漫游切换、多信道监测等智能分析功能。该系统已在北京地铁亦庄线、昌平线、10号线等多条线路上应用,运用效果良好,满足现场无线监测需求,大幅提升了车地无线通信监测能力及应急处置响应效率,对保障列车运营安全具有重要意义。

WPAN/WLAN应用环境下基于PER的链路自适应算法

本文重点研究基于包错误率测量的链路自适应算法,分析了包错误率与信道参数的关系,提出了一种有别于固定门限值方案的优化门限值方案。仿真结果表明,优化门限值方案的网络吞吐量要大于固定门限值方案和基于信干比估计的链路自适应算法,最大增幅可达12Mbit/s。在系统引入重传机制后,网络吞吐量将有所损失,但最大不超过1Mbit/s,相比较服务质量的提高是值得的。需指出的是,虽然分析和仿真均以HIPERLAN/2为例,但不失一般性,它们同样适合于WPAN/WLAN等类似系统。

基于IEEE802.11g标准的WLAN性能分析与测试

分析了IEEE80 2 .11g标准,介绍了无线局域网的拓扑结构,构建了一个基于80 2 .11g标准的WLAN。采用网络传输率测试软件Qcheck ,通过无线到有线网络客户端、无线到无线客户端、混合网络模式的TCP传输性能和穿透性能4个方面的测试,对基于80 2 .11g标准的WLAN性能进行了实验验证。通过与80 2 .11b标准的性能对比。

WLAN的一种分层管理结构设计及实现

摘 要:通过分析网络管理的体系结构,讨论了一种基于SNMP的通过Community字段代理转发的方法,并给出了网络管理的具体实现。文中讨论的方法具有易于实现、扩展性强的特点。

基于无线局域网(WLAN)的油田安全监控系统研究

针对油田监控对象具有点多、面广、跨区域的特点,指出对油田进行无线监控的必要性,并对6种常见的无线通信手段的特点进行比较;根据油田安全监控的业务需求,提出基于WLAN技术的油田安全监控系统硬件结构和软件功能设计方案;并结合工程实施案例介绍系统中无线设备的选型、安装和防雷接地等方面的工程问题。该研究成果实现油田的安全监控预警,减少或避免事故发生的可能性,有利于提高油田安全管理的科学性,具有实用推广价值。

基于核直接判别分析和支持向量回归的WLAN室内定位算法

该文针对RSS信号的时变性降低WLAN室内定位精度的问题,提出了一种新的基于核直接判别分析和支持向量回归的定位算法。该算法利用核直接判别分析对原始RSS信号进行定位信息重组,去除冗余定位特征和噪声,提取最具判别力的定位特征,然后采用支持向量回归算法建立定位特征与物理位置的映射关系。实验结果表明,提出算法的定位精度明显高于传统定位算法,且大大降低了离线阶段数据采集的工作量。

基于Snort-wireless的分布式入侵检测系统研究与设计

为了解决无线局域网存在的安全隐患,该文设计了基于Snort-wireless的分布式入侵检测模型。该模型利用开源、免费和易于扩展的Snort-wireless实现客户端的网络入侵检测引擎,利用VC++开发了控制中心,并且采用加密的TCP/IP协议实现客户端与控制中心之间的安全通信。同时,该模型符合入侵检测的标准框架CIDF,使该模型在性能、重用性以及可扩展性方面得到保证。