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.

基于local-area的Internet路由级拓扑抽象算法

通过分析Internet的本地聚集特性，给出了local-area和connect—area的定义，并基于此，为提高并行网络模拟性能，提出一种新型拓扑抽象算法——基于local—area的拓扑抽象（TABLA）算法。TABLA算法在给定的聚合粒度下，迭代搜索网络内的local-area，对拓扑进行抽象。模拟结果表明在Internet路由级拓扑上采用该算法，拓扑规模大约压缩为原先的45％，初始化内存节省约60％，模拟运行时间约缩短80％，大幅度提高了并行网络模拟性能。

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%。

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.

5G LAN应用及安全探讨

第三代合作伙伴计划(3rd Generation Partnership Project,3GPP)在R16中启动了5G局域网(Local Area Network,LAN)项目研究,该技术让5G网络具备了提供广域局域网的能力,为5G网络与工业网络的融合提供了助力。首先介绍了5G LAN的标准演进、实现原理、关键技术,重点说明了5G LAN在家庭/园区网、企业网络、工业网络等的典型应用;其次分析了5G LAN中基础平台、网络接入、信息隔离、信息传输等方面的主要安全问题,并分别从基础设备计算平台、网络和系统安全防护、系统隔离防护3个方面提出了解决思路和方法,提升5G LAN的整体安全防护能力。

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.

基于VLAN的多信道卫星通信地面系统设计

随着卫星通信技术的日益发展,系统内部多信道并存的现象越来越普遍,信道间传输的业务容易引起相互干扰,单纯运用传统路由器很难完成系统中不同信道间的业务完整隔离;同时,多信道卫星通信系统网络拓扑结构复杂,易引起控制混乱等问题。针对这些问题,提出一种基于虚拟局域网(Virtual Local Area Network,VLAN)的多信道卫星通信地面系统的设计方法。该方法充分利用网络划分VLAN技术的隔离性和安全性特征,结合多信道通信技术使用多个信道同时传输业务的特征,提升特征维度,实现高效、可靠的多信道卫星通信,具有易于硬件实现的特点,提高网络通信的吞吐量。

VLAN技术在校园网中的实际应用

VLAN技术可跨越物理边界,不仅缩小了广播域,还提高了局域网的安全性,有助于工作站实现增加、删除及修改等操作。文章选用三层交换机实现了VLAN间的路由,简化了网络管理和维护,保障了校园网络的良好运行。

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。

VLAN技术在校园网实验中的应用

虚拟局域网（VLAN）不仅可以提高网络运行的效率,而且有利于网络安全和防止网络风暴,能解决许多其他问题。第三层交换机的普及为VLAN的应用创造了条件。在实现网络构架时,采用VLAN技术可解决网络管理、扩容等问题,并可尽量发挥设备的功能,提高网络稳定性。该文详细探讨了VLAN技术在校园网建设中的应用。

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。

一种跨VLAN的网络拓扑发现算法

网络拓扑发现是图形化网络管理的基础。该文提出了一种跨虚拟局域网(VLAN)的物理网络拓扑发现算法,算法基于以太网技术,被管理设备支持SNMPv2。分别对实现了Bridge MIB、部分或没有实现Bridge MIB、服务器和路由器等节点提出了自动发现方法。算法应用于华北电力大学校园网的综合智能网络管理系统中,取得较好的成效。